peer support group research

• Research article
• Open access
• Published: 11 November 2020

The effectiveness of one-to-one peer support in mental health services: a systematic review and meta-analysis

• Sarah White 1 ,
• Rhiannon Foster 1 ,
• Jacqueline Marks 1 ,
• Rosaleen Morshead 1 ,
• Lucy Goldsmith 1 ,
• Sally Barlow 2 ,
• Jacqueline Sin 1 &
• Steve Gillard   ORCID: orcid.org/0000-0002-9686-2232 1  

BMC Psychiatry volume  20 , Article number:  534 ( 2020 ) Cite this article

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Peer support is being introduced into mental health services internationally, often in response to workforce policy. Earlier systematic reviews incorporate different modalities of peer support (i.e. group and one-to-one), offer inconsistent evidence of effectiveness, and also indicate substantial heterogeneity and issues of quality in the evidence base at that time. An updated review, focussed on one-to-one peer support, is timely given current policy interest. This study aims to systematically review evidence for the effectiveness of one-to-one peer support interventions for adults using mental health services, and to explore heterogeneity in peer support interventions.

We searched MEDLINE, PsycINFO, Embase, CINAHL and Cochrane databases from inception until 13 June 2019. Included studies were assessed for risk of bias, and meta-analyses conducted where multiple trials provided usable data.

Twenty-three studies reporting nineteen trials were eligible, providing data from 3329 participants. While seven trials were of low to moderate risk of bias, incomplete reporting of data in many studies suggested bias in the evidence base. Peer support interventions included peer workers in paraclinical roles (e.g. case manager), providing structured behavioural interventions, or more flexible support for recovery.

Meta-analyses were conducted for eleven outcomes, with evidence that one-to-one peer support may have a modest positive impact on self-reported recovery and empowerment. There was no impact on clinical symptoms or service use. Analyses of heterogeneity suggest that peer support might improve social network support.

Conclusions

One-to-one peer support in mental health services might impact positively on psychosocial outcomes, but is unlikely to improve clinical outcomes. In order to better inform the introduction of peer support into mental health services, improvement of the evidence base requires complete reporting of outcome data, selection of outcomes that relate to intervention mechanisms, exploration of heterogeneity in the implementation of peer support and focused reviews of specific types of one-to-one peer support.

Trial registration

Prospero identifier: CRD42015025621 .

Peer Review reports

Mental health and workforce policies in a number of countries advocate the introduction of large numbers of peer workers into mental health services [ 1 , 2 ]. In this context, peer workers are people with personal experience of using mental health services and/ or of mental distress, employed to make use of that experience in providing support to others currently using mental health services. Peer support more generally refers to a mutual exchange of emotional and practical support between people who identify as peers on the basis of shared or similar experiences of mental distress, with the recent origins of organised forms of peer support often ascribed to the mutual aid movement [ 3 , 4 ]. The emergence of trained peer workers, providing peer support to people using mental health services, is a comparatively newer phenomenon, stimulated perhaps in part by assumptions about economic prudence [ 5 ], and in part by suggestions that peer support aids individual recovery [ 6 ]. Peer workers have been employed in a range of roles, providing one-to-one support to individuals using mental health services, as we explore below, supporting and facilitating mutual support groups, or running services provided as an alternative to mainstream provision.

The peer support literature has been reviewed before, with Pitt and colleagues [ 7 ] finding a small reduction in emergency service use where peer workers were compared with other mental health professionals working in similar roles (primarily case management), while Lloyd Evans and team [ 8 ] found a modest positive effect of peer-provided interventions on self-reported recovery and hope. However, both reviews combined studies of individual and group-based peer support – noting substantial heterogeneity in both intervention and trial population – and in both reviews authors cautioned that the majority of trials were of low to moderate quality and that reporting bias in particular might explain these results. More focused reviews have considered peer support for people experiencing depression [ 9 ], and for those experiencing psychosis [ 10 ]. The former considered only group interventions, while the latter combined group, one-to-one and service-level modalities of peer support, and found no evidence of effectiveness of one-to-one peer support. However, a recent, informal review has indicated that a number of new trials of one-to-one peer support in mental health services have been reported [ 11 ], offering a timely opportunity for a systematic review focusing on one-to-one peer support in order to provide an evidence base for the ongoing introduction of peer workers into mental health services internationally.

Exploring heterogeneity of peer support interventions

We note that Pitt and colleagues [ 7 ] identified small differences in effect when considering ‘consumer provider [peer] vs professional staff’ in comparison to ‘consumer provider as an adjunct vs usual care alone’, warranting exploration of this aspect of intervention heterogeneity in the context of one-to-one peer support in this review. Both Pitt [ 7 ] and Lloyd Evans [ 8 ] also note that peer support is often under specified in trial papers, and that it is not always clear how peer support is different from mental health support provided by other types of mental health worker. A wider literature has identified a values-base that specifies how peer support is distinctive from other mental health support, suggesting that peer support is characterised by: a relationship grounded in a sense of connection based on shared experiences [ 12 ]; the use of experiential, rather than formal (taught) knowledge in the peer worker role [ 13 ]; the reciprocal nature of the relationship, with both parties learning from each other in contrast to the uni-directional clinician-patient relationship [ 14 ]. However, it is also noted how the formal, health services environment is not always conducive to the delivery of peer support [ 15 , 16 ].

Studies have identified a number of organisational factors that facilitate the implementation of distinctive peer support into practice, including: a clear, shared understanding of the values informing peer support in the peer worker role [ 17 ]; the importance of dedicated peer support training programmes for peer workers [ 18 ]; the need for support and supervision for peer workers [ 19 ]. Some actors in the peer support community have called for standards in the delivery of peer support in mental health services to ensure that a distinctive, values-based peer support is delivered [ 20 ]. Currently there is a lack of evidence of any association between outcomes and organisational variables supporting the delivery of peer support. There is therefore a case for exploring whether it is possible to operationalise, as a subgroup analysis, the quality of organisational support for one-to-one peer support interventions as an additional approach to exploring the heterogeneity of peer support in mental health services.

This study aims to:

systematically review all the available peer-reviewed evidence for one-to-one peer support interventions for adults using mental health services

evaluate the effects of one-to-one peer support in mental health services on a range of pre-specified outcomes

investigate, using subgroup analyses, how heterogeneity in intervention (i.e. type of peer support, quality of organisational support for peer support) is related to outcome.

This systematic review and meta-analysis adheres to PRISMA guidelines and is funded by the UK National Institute for Health Research as part of larger programme of research investigating peer support in mental health services. The review protocol is registered with the International Prospective Register Of Systematic Reviews, identifier: CRD42015025621.

Definitions

For the purpose of this review we consider one-to-one peer support in mental health services to be support delivered by an individual with personal experiences of using mental health services and/or of mental distress. We refer to the person delivering peer support here as a peer worker , noting that other terms, including peer support worker , peer specialist and consumer employee , have been used elsewhere. Peer workers are employed – whether paid or unpaid – and trained to make use of their experiential knowledge in providing support to someone who shares similar experiences, as part of or alongside the care and treatment they are receiving from mental health services.

Eligibility criteria

Studies were included where peer support was:

provided one-to-one;

intentionally provided by a peer worker;

for adults using mental health services.

Studies were excluded if peer support was:

not the primary means of delivering the intervention;

not one-to-one or intentionally provided by a peer worker;

where mental health was not the primary focus of the intervention.

Other exclusions were applied if the study was not in the English language, non-retrievable, or did not contain empirical data.

Study design

All types of randomised controlled trial (RCT) were included. Other study types were excluded.

Intervention and comparison conditions

We noted above that one-to-one peer support in mental health services has been characterised as either: an adjunctive intervention, delivered by peer workers in addition to care as usual or as an additional component to a treatment or therapy; or as peer workers delivering similar interventions to those delivered by other mental health workers (e.g. where peer workers are employed in a substitute capacity) [ 7 ]. We include both ‘adjunctive’ and ‘substitute’ peer support interventions in this review, and consider all comparator conditions in our primary analysis. Where trials had two or more intervention arms (e.g. with and without peer support) and a control arm, in all cases the comparison chosen was peer support (as intervention condition) and the other enhanced or active condition (as control condition), rather than care as usual or an attention control arm.

As noted above, a variety of outcomes have been assessed in peer support trials. Given that a number of additional trials have emerged since the publication of existing systematic reviews, it is of interest to consider whether the range of outcomes of interest remains broad or has begun to coalesce. We extract data using the set of outcomes explored in the review conducted by Lloyd-Evans and colleagues [ 8 ]. In addition, we consider use of emergency services in order to explore further findings in the Pitt review [ 7 ] and, following other published research into the mechanisms of peer support we include a small number of more socially-focused outcomes that may be impacted by peer support [ 21 ]. The full set of outcomes of interest for this review is as follows:

Hospitalisation

Emergency service use

Overall psychiatric symptoms

Symptoms of psychosis

Depression and anxiety

Quality of Life

Recovery (self-rated)

Empowerment

Satisfaction with services.

Social functioning

Social network support

Working alliance (clinician rated/ patient rated)

Self-stigma

Experienced stigma

Engagement with services

Search methods for identification of studies

The following online bibliographic databases were identified in 2015 based on then existing reviews [ 6 , 7 ] – Cochrane Central Register of Controlled Trials, MEDLINE, EMBASE, PsychINFO and CINAHL Plus – and searched initially from inception until the end of April 2015.

Existing reviews were used to provide a basis for search terms, with authors using their knowledge of the area, including service user researchers JM and RF, to add to search terms. The diagnostic manual DSM 5 [ 22 ] was consulted to provide a systematic structure to ensure mental health terms were inclusive. The search strategy was tested and refined as necessary. All databases were searched using a similar set of terms, strategies and Boolean operators, amended solely for the purposes of the research database management interface and not for content. An example of the search strategy, for MEDLINE, EMBASE and PsychINFO using the OVID interface, is given in Supplementary materials 1 .

Searches were updated on 13 June 2019, with no changes to search terms or search strategy. All papers returned by the search were imported into an Endnote library and any duplicates removed first using the software and then by manual review.

Study selection

Titles and abstracts of all studies returned in the search were independently screened for inclusion in the review by two researchers (two of JM, RF and RM). Disagreements were resolved by discussion using the full text of the paper, with remaining differences resolved by discussion with SG. Reference list and forward citation searching of included studies were used to identify additional papers for inclusion in the review.

Data extraction

Data were extracted for study characteristics from each included study by one of JM, RF or RM using a structured data extraction data sheet (see Table  1 below), with a second researcher (SG) checking for accuracy of extraction for 25% of studies.

For the purposes of exploring heterogeneity of intervention as subgroup analyses in the meta-analysis we also recorded where peer support was provided as an adjunctive intervention and where peer workers were working in a substitute role, as defined above, and in addition rated the quality of organisational support provided for peer support. To do this, studies were independently coded by two members of the team (JM and RM) where they reported any of the following indicators:

Dedicated peer support training;

Clear description of theory, processes or understanding of peer support;

Support structures for peer workers (e.g. supervision).

Discrepancies between researchers were discussed until agreement was reached. Studies were then categorised as having a ‘higher level’ of organisational support for peer support if they fulfilled at least two of the three indicators, or ‘lower level’ if they met one or less indicators.

Extraction of data for meta-analysis

One researcher (RM) extracted data for outcomes onto a bespoke extraction sheet. Data were included if they were assessed using a standardised measure or, in the case of service use data, captured in clinical records. For continuous outcomes, sample sizes, mean and standard deviations by arm were extracted, and for dichotomous outcomes, the number of events and sample size per arm were extracted. All outcome data extraction was checked by statistician SW for accuracy and completeness. If data for a particular outcome were only reported by a single paper that outcome was not included in the meta-analysis. We wrote to authors of included studies for additional information and trial data where it was not included in the published article.

Where outcome data were reported for more than one follow-up point, the longest timepoint was used. Where more than one measure was used to report the same outcome in a study, we included the measure more commonly reported by other studies in the analysis.

Assessment of risk of bias

Each included study was assessed for risk of bias by two researchers (RM, JM), with any differences in assessment resolved by a third researcher (SW), in accordance with Cochrane Collaboration Risk of Bias Tool [ 80 ]:

adequate sequence generation (selection bias)

allocation concealment (selection bias)

blinding of outcome assessment (detection bias)

incomplete outcome data (attrition bias)

selective outcome reporting (reporting bias)

It is important to note that although blinding of participants to allocation is usually assessed, in this particular instance the nature of a peer intervention means that all trial participants are unblinded. As such this particular source of bias is not assessed in this review, in line with existing reviews of peer support.

Statistical analysis

Effect sizes for continuous data were calculated as standardised mean difference (SMD), Hedges’ g, with studies weighted using the inverse variance method [ 81 ]. Risk ratios were calculated for dichotomous outcomes, and studies combined again using the inverse variance method. All pooled effect sizes are reported with 95% confidence intervals calculated using random-effects models. We used intention to treat data in all analyses.

Statistical heterogeneity was assessed through the I 2 statistic which describes the percentage of the variability in effect estimates that is due to heterogeneity rather than chance and the p -value of the χ 2 test (Q) for heterogeneity. A p-value < 0.10 and an I 2  > 50% suggests substantial heterogeneity. Where substantial heterogeneity of effect sizes across trials is observed, subgroup analyses were conducted, comparing studies where:

peer support was provided as an adjunctive intervention, against those studies where peer workers were working in a substitute role;

a higher level of organisational support for peer support were reported, against those studies where a lower level was reported.

Differences between subgroups of studies were tested using the Qint test for heterogeneity, testing if effect sizes differ across subgroups. Review Manager (RevMan 5.2 for Windows) software [ 82 ] was used to conduct the meta-analyses.

A total of 6502 records were identified in the updated search. Of these, 311 studies were potentially eligible and, after further review (as described above) 23 eligible papers were identified, reporting on 19 trials. One trial was reported across four papers [ 23 , 83 , 84 , 85 ] and another trial reported across two papers [ 45 , 86 ]. See Fig.  1 below.

Flowchart of inclusion of studies

Study characteristics

Twelve studies were conducted in the USA [ 23 , 28 , 30 , 31 , 39 , 42 , 44 , 45 , 54 , 63 , 66 , 68 ], three were conducted in the UK [ 35 , 59 , 76 ], one in Canada [ 62 ], one in Australia [ 50 ], one in Germany [ 71 ], and one in Japan [ 74 ]. Eighteen trials were individually randomised and one was a cluster randomised trial [ 54 ]. Six studies described themselves as pilot trials [ 28 , 35 , 45 , 59 , 62 , 68 ], four studies were three-arm trials [ 30 , 31 , 42 , 50 ], and one study used a waitlist control [ 68 ].

Fifteen studies fell into the ‘adjunctive’ peer support group, with eleven of those comparing peer support as an adjunctive intervention to care as usual [ 28 , 31 , 35 , 42 , 45 , 54 , 59 , 66 , 71 , 74 , 76 ]. Two of the eleven [ 31 , 42 ] were three arm trials comparing care as usual, an adjunctive intervention, and the intervention plus an additional peer support component. Another three-arm trial [ 50 ] compared an attention control, intervention, and the intervention plus an additional peer support component. Two papers reported two arm trials of an intervention, with and without adjunctive peer support [ 44 , 63 ], and one study compared the peer support intervention with a waitlist condition (i.e. no-comparator intervention) [ 68 ]. Four studies compared peer workers working in a substitute capacity compared with other mental health workers performing a similar role [ 23 , 30 , 39 , 62 ]. One of these studies was also a three-arm trial [ 30 ], with care as usual as the third arm. Further details about study characteristics can be seen in Table 1 below, with indication given of which comparators were used in the subsequent meta-analysis.

Participants in all studies were adults, although in one study participants were aged 55 or older [ 68 ]. In the majority of studies – twelve – participants were using community mental health services [ 23 , 28 , 30 , 35 , 39 , 44 , 50 , 54 , 62 , 63 , 66 , 76 ]. In three studies participants were recruited as inpatients [ 42 , 45 , 59 ], and in two studies participants were recruited as either inpatients or outpatients [ 71 , 74 ]. In two studies participants were recruited directly from depression clinics [ 31 , 68 ]. Most studies indicated diagnostic inclusion criteria, with seven studies specifying that participants would have diagnoses of either psychotic, or major depressive or mood disorders [ 23 , 30 , 39 , 42 , 45 , 54 , 66 ]. Two studies specified a diagnosis of bipolar disorder [ 44 , 50 ], one of major depressive disorder [ 31 ], one of mild to moderate depression and anxiety [ 68 ], one of either psychotic or personality disorders [ 71 ], and one of dual mental health, and drug or alcohol disorder [ 28 ]. Two studies defined eligibility by duration of mental illness with one specifying at least two years [ 71 ], and the other indicating that mental illness should be persistent [ 62 ]. A number of studies defined the population by service use history. In three studies eligibility criteria were defined by a minimum number of previous, recent psychiatric hospital admissions [ 42 , 45 , 54 ]. One study recruited participants as they approached hospital discharge [ 59 ], one study recruited participants who had been referred to specialist crisis and home treatment teams [ 76 ], and another study recruited participants who were under a court order mandating community mental health treatment [ 63 ].

Sample sizes

Samples sizes in the studies ranged from 21 [ 62 ] to 468 [ 54 ], with a total of 3329 participants in the 19 trials.

Interventions

While descriptions of peer support interventions remains thin in some studies published since the last review [ 8 ], a number of more recent studies do provide detailed descriptions of peer worker roles and what constitutes peer support. Peer workers were reported as delivering a range of different interventions. Five studies reported peer workers working in case management roles [ 23 , 30 , 39 , 42 , 54 ]. Typically, peer workers were expected to fulfil a similar, brokerage-type case management function to other mental health workers, and in addition, to role model their own strengths and experiences of recovery [ 39 ], or to provide social support by arranging social activities [ 42 ]. Three studies reported peer workers working in mentoring or coaching roles [ 44 , 45 , 50 ]. Mentoring and coaching roles varied considerably from offering a very loosely described partnership relationship that aimed to be different to a clinician-patient relationship [ 45 ], to structured online coaching to support participants in producing a detailed, behaviourally-informed recovery plan [ 44 ]. Three studies described peer workers providing support for self-management [ 31 , 62 , 76 ]; for example, in one study peer workers provided one-to-one assistance with rehabilitation goals set by occupational therapists [ 62 ], while in another peer workers supported participants to complete a structured recovery workbook [ 76 ]. Another three studies describing peer workers offering support for recovery [ 59 , 63 , 71 ]. What support for recovery entailed was generally poorly defined, with the exception of Mahlke and colleagues [ 71 ], describing in some detail how peer workers were trained and supported to reflect on and make use of their own experiences as a resource in supporting others with their recovery, but also reported that the intervention was not further manualised, and that peer workers had flexibility in the role, with an emphasis on enhancing the sense of control over their lives that people experienced. Two studies reported peer workers providing support for living independently in the community [ 28 , 66 ]. Peer support in both studies had a strong social focus and in the case of the latter [ 66 ], support was highly individualised and self-directed, involving the peer worker helping the individual to access social support that they identified themselves. Other studies described peer workers providing support for shared decision making in clinical consultations, again with a strong focus on a structured self-management approach [ 74 ], delivering a cognitive behavioural intervention using a structured workbook [ 68 ], and working in a healthcare assistant role [ 35 ].

Most peer support was provided face-to-face but in one study peer support was provided either face to face or by telephone [ 31 ], and in two studies peer support was provided online [ 44 , 50 ]. We note that in three studies peer workers were employed by peer-led organisations or agencies [ 23 , 63 , 66 ]. As noted above, four studies evaluated peer workers as a substitute for other mental health workers working in a similar role, three of those in a case management capacity [ 23 , 30 , 39 ], and in the fourth, providing support for self-management [ 62 ]. In all other studies peer support was adjunctive to care as usual or evaluated as an enhancement to another intervention.

Level of support for peer support interventions

The majority of studies – fourteen and thirteen respectively – described the support and/ or supervision provided to peer workers to deliver the peer support intervention [ 23 , 28 , 35 , 42 , 44 , 45 , 54 , 59 , 62 , 63 , 66 , 68 , 71 , 76 ], and the peer support-specific training provided to peer workers [ 31 , 35 , 39 , 44 , 45 , 54 , 59 , 62 , 63 , 66 , 71 , 76 , 85 ]. In contrast, only five studies explicitly described the theory, processes or understandings of peer support that underpinned the intervention evaluated [ 23 , 28 , 35 , 54 , 71 ].

There was variation in the degree of reporting of support given to peer workers. Reporting of training provided varied from noting that peer workers had received accredited peer specialist training prior to delivering the intervention [ 44 ], to a more detailed description of an extended, structured training program describing module content and mode of delivery [ 71 ]. Description of the support and supervision provided for peer workers also varied, from studies that simply reported that peer workers were provided with support and supervision for the duration of the study [ 59 ], to one which described in some detail the areas covered during weekly, 90 min group supervision sessions for peer workers [ 45 ]. One study said that supervision was provided by a peer support coordinator, with preference being given to employing someone with lived experience of mental illness in that role [ 62 ], while another stated that the director of the consumer case manager team was a consumer [ 23 ]. However no studies clearly stated that supervision for peer workers was provided by someone who was themselves employed to use their personal experiences of mental distress or of having used mental health services in the role. Theory, processes and understanding of peer support also varied in description, with one study [ 71 ] describing a specific peer support change model that underpinned the intervention, while others gave a more general description of the processes that characterise peer support as distinctive from other forms of mental health support [ 35 ].

Three studies did not report any of these organisational support components (dedicated peer support training; underlying theory; support for peer support) [ 30 , 50 , 74 ], and four reported just one component [ 31 , 39 , 42 , 68 ]. In contrast, four studies reported all three components [ 23 , 35 , 54 , 71 ], and eight reported two out of three [ 28 , 44 , 45 , 59 , 62 , 63 , 66 , 76 ].

Studies reported measuring thirteen of the eighteen outcomes of interest, with no studies of one-to-one peer support providing usable data assessing employment, symptoms of psychosis, self-stigma or experienced stigma, or emergency service use. Studies most often measured were hospitalisation [ 23 , 28 , 30 , 35 , 42 , 45 , 59 , 71 , 76 ] and quality of life [ 23 , 28 , 42 , 54 , 59 , 62 , 63 , 66 , 71 ], both measured in nine studies. We note that hospitalisation was variously measured as days in hospital, number of admissions or re-admissions, and community tenure (days spent living in the community, post-intervention, before hospital admission). Overall psychiatric symptoms were measured eight times [ 23 , 42 , 45 , 54 , 63 , 71 , 74 , 76 ], and both of social functioning [ 28 , 31 , 35 , 45 , 50 , 71 , 74 ] and social network support [ 23 , 28 , 35 , 42 , 45 , 63 , 76 ], seven times. Given that many studies used a more general measure of functioning - i.e. the Global Assessment of Function scale [ 29 ] – we subsequently report this outcome as General and Social Functioning. Satisfaction with services [ 31 , 35 , 42 , 45 , 76 ], empowerment [ 50 , 54 , 66 , 71 , 74 ] and working alliance [ 23 , 39 , 66 , 68 , 74 ] were all measured five times. We note that some studies reported both a participant rating of working alliance with staff and a staff rating of working alliance with the participant [ 23 , 74 ], while others only reported a participant rating of staff [ 39 ]. Self-rated recovery was measured in four studies [ 54 , 63 , 66 , 76 ], with wellbeing [ 28 , 42 , 45 ] and engagement with services [ 35 , 39 , 66 ] both measured in three studies. We grouped measures of physical health (e.g. two studies separately reported scores on the physical health subscale of the Lehman Quality of Life Scale) [ 26 ] with a more general measures of wellbeing (Life Skills Profile) [ 36 ], and so we report wellbeing as Physical Health and Wellbeing going forward. Depression and anxiety were also measured in three studies, with only Seeley and colleagues [ 68 ] using a separate measure for each, Proudfoot and colleagues [ 50 ] using a generalised measure for both, and Hunkeler and colleagues [ 31 ] measuring depression only. As a result we retain Depression and Anxiety as a single outcome for the purposes of this review. Finally, hope was measured in two studies [ 44 , 45 ]. Details of the specific tools used to measure these outcomes in each study can be found in Table 1 and are discussed further in the context of the meta-analysis reported below.

Risk of bias

The Risk of Bias ratings are displayed in Fig.  2 . Sequence generation was not sufficiently described in 7 of the 19 trials and was at high risk of bias in one trial. Concealment of the allocation sequence was not sufficiently described in 11 trials, and again at high risk of bias in one trial. Lack of blinding of assessors created a high risk of bias in 3 studies, and in 8 further trials it was unclear if assessors were blind. At the trial level, 3 were at high risk of bias for missing data (i.e. attrition bias) and 6 were unclear. Included studies may have measured but not reported outcomes that are included in this review; 10 with unclear description and 4 with high risk of reporting bias. Seven of the 19 studies [ 44 , 50 , 59 , 63 , 68 , 71 , 76 ] were at low risk of bias on at least three of the five bias categories and not high risk of bias for any category (i.e. might be described as being of low to moderate risk of bias overall), with the majority of those studies having been published since previous reviews. However on balance, overall quality of trials, when compared to previous reviews, remains low to moderate.

Summary of risk of bias of included studies

Quantitative synthesis

Data were available for the meta-analysis from fourteen of the nineteen trials included in the review (sixteen papers), with two or more trials contributing to meta-analyses of nine of our original outcomes. Because of the way data were reported in the studies, we analyse these as eleven outcomes, analysing days in hospital and hospitalised as two discrete outcomes in place of hospitalisation, and separating working alliance into staff-rated and client-rated outcomes. This analysis includes data obtained from one study after contacting study authors [ 74 ]. The number of studies contributing data to each outcome included in the analyses can be seen in Table  2 below. Median length of follow-up was 12 months post randomisation, ranging from 2.5 to 24 months. In the following analyses a positive standardised mean difference (SMD) for the following outcomes - quality of life, social network support, empowerment, recovery, service satisfaction, working alliance (client and staff rated) - indicates the peer support intervention being more effective than the control condition, the opposite being the case for the following; general psychiatric symptoms, depression and anxiety, days in hospital and hospitalised.

Five trials reported the dichotomous outcome of whether hospitalised during follow-up period or not. Follow-up ranged from 3 to 24 months with data on a total of 497 participants. The risk of being hospitalised was reduced by 14% for those receiving peer support (RR = 0.86: 95% CI 0.66, 1.13). Moderate heterogeneity (I 2  = 38%) was found across trials for this outcome. A similar result of a non-significant effect of peer support (SMD = -0.10: 95% CI -0.34, 0.14) and moderate heterogeneity (I 2  = 39%) was found for the days in hospital outcome. The five trials in this meta-analysis had follow-up ranging from 9 to 24 months and a total sample size of 453.

Six trials reported overall psychiatric symptoms with follow-up ranging from 6 to 24 months. Total sample size was 857. There was no evidence of the effect of peer support on symptoms; pooled standardised mean difference was − 0.01 (95% CI -0.21, 0.20). There was a high level of heterogeneity across trials, I 2  = 53%, χ 2 test of heterogeneity. Q = 10.7, p  = 0.057.

Quality of life

A total of 688 participants had quality of life data reported from five trials with follow-up ranging from 12 to 24 months. No effect of peer support was found on quality of life, SMD = 0.08 (95% CI -0.11, 0.26) with moderate heterogeneity across trials, I 2  = 32%.

Three trials reported appropriate recovery data with follow-up ranging from 12 to 18 months and a total sample size of 593. Peer support is shown to have a small but statistically significant benefit on recovery (SMD = 0.22: 95% CI 0.01, 0.42: p  = 0.042) (Fig.  3 ). Only moderate heterogeneity is indicated, I 2  = 38%.

Forest plot for recovery outcome

Four trials with a total sample size of 519 participants and follow-up ranging from 6 to 12 months reported empowerment related outcomes. Empowerment was significantly higher in those receiving peer support, a small effect size, SMD = 0.23 (95% CI 0.04, 0.42: p  = 0.020) (Fig.  4 ). Heterogeneity was low, I 2  = 14%.

Forest plot for empowerment outcome

Satisfaction with services outcome data was available from two trials and a total of 286 participants. Follow-up in the two trials ranged from 12 to 18 months. No effect of peer support was found (SMD = 0.19: 95% CI − 0.05, 0.42) with no heterogeneity, I 2  = 0%.

General and social functioning

Three trials provided data for the general and social functioning outcome on a total sample size of 181. Follow-up in the two trials ranged from 6 to 12 months. No effect of peer support was found (SMD = 0.01: 95% CI -0.32, 0.35) with little heterogeneity, I 2  = 21%.

Four trials reported social network support outcome data with follow-up ranging from 12 to 24 months and a total sample size of 512 participants. While the pooled SMD = 0.09 (95% CI -0.25, 0.42) indicated no effect of peer support on social network support, there is significant heterogeneity across the trials, I 2  = 67%, χ 2 test of heterogeneity. Q = 9.2, p  = 0.027.

Working alliance

Client rated working alliance about staff was reported in three trials and by a total of 213 participants. Follow-up ranged from 6 to 24 months. No heterogeneity was found across trials, I 2  = 0%, but the SMD = 0.24 (95% CI -0,03, 0.51: p  = 0.080) indicates a potentially positive outcome for peer support. The SMD = 0.15 (95% CI -0.18, 0.48) was lower for staff ratings of the working alliance, again with no heterogeneity, I 2  = 0%. This outcome was only rated in 2 trials, a total of 139 participants.

Subgroup analyses

Only two outcomes – overall psychiatric symptoms and social network support – satisfied our condition of sufficient heterogeneity in the data to warrant undertaking subgroups analyses (see Table  3 below). We conducted subgroups analyses of those outcomes as defined earlier: adjunctive peer support interventions compared to those where peer workers were working in a similar or substitute role to other mental health workers; studies reporting a higher level of organisational support for peer support compared to those studies reporting a lower level of organisational support for peer support. These analyses did not explain heterogeneity with respect to overall psychiatric symptoms. A single study [ 42 ], reporting a lower level of organisation support for peer support, found a moderate, significant increase in social network support for people in the peer support arm of the trial (SMD = 0.50: 95% CI 0.14, 0.87), compared to three other studies with a higher level of organisational support for peer support where no significant difference in social network support was found (SMD = -0.04: 95% CI -0.37, 0.28) (Fig.  5 ). It can also be seen in Table 3 that there is evidence that whether peer support is being provided as adjunctive to usual care or as a substitute role impacts the effectiveness of peer support in increasing social network support, Qint = 4.27, p  = 0.039. The effect of peer support is significantly greater when it is delivered as an adjunctive, SMD = 0.23, as opposed to substitute intervention, SMD = -0.30, a difference of 0.53 (Fig.  6 ).

Sub group analysis; social network support by level of organisational support

Subgroup analysis; social network support by type of peer support

Our review has indicated that a number of additional studies of one-to-one peer support have been published in the years following previous systematic reviews, suggesting that it has become viable to consider different modalities of peer support – e.g. group, one-to-one, peer-led services – in separate reviews. Studies remain predominantly conducted in the US, but with a gradual increase in studies being conducted in Europe and beyond. With health systems operating differently in different countries, caution does need to be taken when considering any results in the round.

While this review is focused on one-to-one peer support, we still see the heterogeneity of intervention observed by Pitt [ 7 ] and Lloyd Evans [ 8 ] across modalities of peer support. However it is interesting to note that most studies of peer workers in paraclinical roles, including case-management [ 23 , 30 , 39 , 42 ] and healthcare assistant roles [ 35 ], are now well over 10 years old, as are the majority of studies that compare peer workers to other mental health workers performing a similar role (‘substitute’ peer support) [ 23 , 30 , 39 ]. It is also worth noting that none of those studies of peer workers in paraclinical roles, or of peer workers in substitute roles, contributed data to analyses of those outcomes where a significant positive effect of peer support was found (recovery and empowerment).

Peer support interventions evaluated in more recent studies, in contrast, are almost exclusively evaluating adjunctive peer support, and tend to have either a structured, behavioural focus [ 44 , 62 , 68 , 74 , 76 ], or a more social focus, with peer workers providing a less structured, more peer-led support for recovery [ 45 , 59 , 63 , 66 , 71 ]. We suggest that there is potential, as more trials are published, of conducting focused reviews of specific groups or families of similar one-to-one peer support interventions.

We observe that a wide range of outcomes continue to be used. Of the original list of outcomes considered by Lloyd Evans and colleagues [ 8 ], we found that neither employment nor symptoms of psychosis were measured in the nineteen trials of one-to-one peer support that we reviewed. While Pitt and colleagues [ 7 ] found a small reduction in emergency service use for people receiving peer support we did not include data on emergency service use in our review as we excluded self-reported service use data from our analysis; Pitt and colleagues [ 7 ] themselves had suggested that recall bias and selective reporting of this outcome undermined the reliability of this particular finding.

While measures of general psychiatric symptoms were used in nearly half of all trials, measures of specific symptoms – of depression – were only used in those studies which exclusively recruited from a population diagnosed with depression [ 31 , 50 , 68 ]. Of our additional set of, largely, more socially-focused outcomes, neither internalised nor experienced stigma have been measured to date, although social functioning, social network support and working alliance were all measured in multiple studies, including in older trials [ 23 , 35 ]. If we consider just those outcomes used in multiple studies (outcomes included in our meta-analysis), we see a more focused outcomes-set emerging, balancing clinically-orientated outcomes of general severity of symptoms, functioning and hospitalisation with a set of self-reported, psychosocial outcomes including empowerment, recovery, working alliance and social network support.

As with previous reviews, once data from multiple studies were pooled, we found no difference between peer support and control across the majority of outcomes we considered. This included hope, where Lloyd Evans and colleagues [ 8 ] found a moderate positive impact of peer support, but we note again that their review included peer support provided to groups while we found insufficient studies of one-to-one peer support reporting measurement of hope as an outcome. However, our review does suggest that trial participants offered one-to-one peer support in mental health services experience modest but significant improvement in empowerment and self-reported recovery compared to control group participants, the latter reflecting similar findings by Lloyd Evans and colleagues [ 8 ].

Studies reporting empowerment were for the most part were published since the 2013 [ 7 ] and 2014 [ 8 ] reviews, reflecting the suggestion made by Bellamy and colleagues [ 87 ] that more recent studies indicate that new peer support initiatives might usefully be directed to interventions that, broadly speaking, support individual empowerment. We grouped assessments of empowerment and related constructs together for the purposes of this review, and the studies in the analysis variously used the Patient Activation Measure [ 57 ], the General Self-Efficacy Scale [ 73 ], and the Empowerment Scale [ 67 ]. As a construct, patient activation has a clear focus on the extent to which the individual is able to access the healthcare they need, and is a good fit for interventions that specifically address the way in which the individual engages with their mental health care [ 54 , 74 ]. Self-efficacy taps into the individual’s ability to make use of a wider range of support and care, while the Empowerment Scale has been shown to weight heavily on hope as a factor [ 67 ]. Again, these measures would seem appropriate for interventions focused on supporting recovery [ 63 ] and independence [ 66 ] respectively.

Studies reporting recovery as an outcome again used a range of measures. Salzer and colleagues [ 66 ] use the Recovery Assessment Scale [ 65 ], which measures recovery across five domains of personal confidence, hope, willingness to ask for assistance, goal and success orientation, and coping, and as such would seem particularly attuned to an intervention designed to support independent living. Johnson and colleagues [ 76 ] use the Questionnaire about the Process of Recovery [ 78 ], which comprises an ‘intrapersonal’ subscale that relates to “intrapersonal tasks that an individual is responsible for carrying out and that they complete in order to rebuild their life”, and an ‘interpersonal’ subscale relating to “individuals’ ability to reflect on their value in the external world and on how recovery is facilitated by external processes and interpersonal relationships with others”. Seventeen of the 22 items that comprise the measure load onto the ‘intrapersonal’ subscale, as would seem apposite for the evaluation of a self-management intervention. Chinman and colleagues [ 54 ] use the Mental Health Recovery Measure [ 55 ], measuring recovery in the seven domains of Overcoming Stuckness, Self-Empowerment, Learning and Self-Re-definition, Basic Functioning, Overall Well-Being, New Potentials, and Advocacy/Enrichment. This balance between functioning and wellbeing, and then moving on and realising potential seems well-suited to the case management function of the intervention.

These findings indicate what would seem to be an important relationship between positive impact on outcome, the assessment tool used and the intervention. As such we would suggest that trials exploring these, or indeed other outcomes, in the future should be cognisant of the constructs informing specific assessment tools (e.g. domains, subscales), and ensure that these relate closely to the mechanisms underpinning particular peer worker interventions. We reiterate calls in previous reviews [ 7 ] for a clearer understanding of the mechanisms of peer support, and the theory driven selection of outcomes that relate specifically to what peer workers do.

We note that one further outcome, client-rated working alliance, while not quite significant, demonstrated a similar effect size to the other positive outcomes. In two studies [ 23 , 39 ] participants rated working alliance with peer workers in the intervention arm of the trial, compared to working alliance with mental health professional in the control arm, while in the third study [ 74 ] working alliance with a mental health professional was rated in both arms of the trial, with and without additional peer support. Once data were pooled there was a relatively small sample size for this outcome; more data would produce a more precise estimate of the effect size. This finding suggests that there is merit in exploring working alliance in future studies of one-to-one peer support, especially given other research indicating a potential mechanism for peer support in bridging and enabling connection between service users and mental health professionals [ 21 ].

We note that while both measures of hospitalisation analysed were in a positive direction (i.e. a reduction in days in hospital and risk of hospitalisation), neither were significant. The lack of positive association between the offer of peer support and reduction in psychiatric symptoms also suggests that, while studies are using a balance of clinical and more psycho-socially focused outcomes, one-to-one peer support in mental health services is unlikely to impact on clinical outcomes.

There was significant heterogeneity of data for two outcomes (overall psychiatric symptoms and social network support). While our subgroup analyses did not explain heterogeneity with respect to overall psychiatric symptoms, analyses did offer insight into the relationship between peer support and social network support. Finding that a single study [ 42 ], reporting a lower level of organisation support for peer support, indicated a moderate, significant increase in social contacts, while studies reporting a higher level of support for peer support did not, appears counter-intuitive. Looking closely, authors note that the increase in positive outcome was accounted for by additional contacts with peer workers and professional staff, rather than any increase in contacts with family or friends [ 42 ].

Furthermore, peer support that was provided in addition to care as usual was significantly more likely to increase social network support than peer support provided by peer workers employed in a substitute role. At the least, these findings suggest that it is worth considering measuring social network support in future studies, while giving consideration to how the peer support intervention might be functioning to increase social contacts. In addition, we would suggest that we have demonstrated that our approach to operationalising an analysis of organisational support for peer support is feasible and might be pursued in future reviews, subject to the availability of suitable data. Continued improvement in reporting peer support interventions might usefully include good description of the organisational support provided for peer workers [ 88 ].

While cost was not one of our outcomes of interest we note that claims have been made about the potential contribution to reducing the cost of mental healthcare that peer support might make [ 5 ]. Only one of the nineteen trials included in our review considered cost, but was not sufficiently powered to draw any conclusions [ 59 ]. As such, analysis of the cost-effectiveness of one-to-one peer support in mental health services is largely absent from the evidence base to date.

Limitations

Overall quality of trials, when compared to previous reviews, remains low to moderate, although we note that, in our set of trials of one-to-one peer support, more recent trials appear less likely to have serious risk of bias and more likely to have low risk of bias on a majority of assessments, and so we tentatively suggest that the quality of studies is improving. Reporting bias, due to incomplete reporting of outcomes data, remains an issue and, as such, this downgrading of the quality of the overall evidence base does limit the strength of findings of this review. We note that for our two main positive outcomes, self-reported recovery and empowerment, all but one of the studies that reported measuring these outcomes included usable data in trial papers. However completeness of reporting of outcomes is essential to inform good quality evidence with respect to peer support in mental health services going forward.

In focusing on one-to-one peer support we have produced a more focused review than previous studies. However we acknowledge that studies remain heterogenous, especially with respect to clinical population (for example, only one study [ 71 ] specified chronicity of diagnosis). In addition, we note the range of terms used to describe peer support roles and acknowledge that our search might not have been wholly inclusive. Like all reviews, the validity of our study is defined by the strategy we describe above.

One-to-one peer support in adult mental health services has a modest, positive effect on empowerment and self-reported recovery, and might potentially also impact on measures of working alliance between service users and mental health workers, and social network support. It seems unlikely that one-to-one peer support has a positive impact on clinical outcomes such as symptoms or hospitalisation, given data available for this review, suggesting that the benefits of peer support are largely psychosocial, operating at both individual (interpersonal) and relational (intrapersonal) levels. The quality of reporting, both of trial methods and design of peer support interventions, has improved somewhat but needs to continue to do so - especially with respect to complete reporting of outcome measurements - in order to maximise the usefulness of the evidence base for service providers and policymakers. Future trials should also consider appropriate assessment of cost-effectiveness of peer support in mental health services.

While some older trials of one-to-one peer support evaluated peer workers working in paraclinical roles, and/ or in substitute roles, newer studies focus on peer workers providing adjunctive interventions; either structured, behavioural interventions, or more socially focused, self-directed, flexible support for recovery. This review suggests that future trials of one-to-one peer support in mental health services should focus on peer workers providing interventions that are additional to usual care; outcomes for peer support are no better than control where peer workers are compared to other mental health workers doing similar work, and might be worse for outcomes such as social network support, possibly because such roles do not enable peer workers to enact a more distinctive way of working.

We suggest that studies should carefully consider the specific mechanisms of action of peer support, with trials designed so that choice of assessment tools (the constructs that are measured) reflect the specific function of the peer support intervention and the distinctive way in which peers work compared to other mental health workers. If and where peer support is having a beneficial effect, there will be a greater likelihood of observing this in a more carefully designed trial. Furthermore, as the evidence base for peer support grows it would be methodologically desirable to conduct more focused reviews of groups of similar interventions (rather than continuing to review a heterogenous group of interventions as a whole). Finally, this review demonstrated the potential to explore heterogeneity in peer support, in relation to outcome, in terms of the quality of organisational support provided to peer workers.

It is of interest to compare our findings with the concurrent review of group peer support conducted by Lyons and colleagues. We similarly identified that heterogeneity of intervention remains a feature of the evidence base while noting that a small number of types or functions of peer support are emerging (with a number of trials of peer-supported self-management identified by both reviews). Both reviews are also indicative of a modest, positive effect of peer support on self-reported recovery and an absence of effect, in the evidence to date, on clinical outcomes. Again, both reviews indicate that reporting bias – incomplete reporting of outcomes – continues to undermine the quality of the evidence base as whole.

Availability of data and materials

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Abbreviations

Confidence Interval

Diagnostic and Statistical Manual

Standard Mean Difference

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This work was supported by the UK National Institute for Health Research, Programme Grants for Applied Research funding programme (grant number RP-PG-1212-20019). This paper presents independent research funded by the National Institute for Health Research (NIHR). The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care. The funder played no roll in the design of the study, the collection, analysis, and interpretation of data, or in writing the manuscript.

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SW and SG contributed to formulating the research question, designing the study, carrying it out, analysing the data and writing the article; RF, JM and RM contributed to designing the study, carrying it out, analysing the data and writing the article; LG, SB and JS contributed to designing the study and writing the article. The author(s) read and approved the final manuscript.

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White, S., Foster, R., Marks, J. et al. The effectiveness of one-to-one peer support in mental health services: a systematic review and meta-analysis. BMC Psychiatry 20 , 534 (2020). https://doi.org/10.1186/s12888-020-02923-3

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Lived experience peer support programs for suicide prevention: a systematic scoping review

• Marisa Schlichthorst   ORCID: orcid.org/0000-0003-2627-7238 1 ,
• Ingrid Ozols 2 ,
• Lennart Reifels 1 &
• Amy Morgan 1  

International Journal of Mental Health Systems volume  14 , Article number:  65 ( 2020 ) Cite this article

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Peer-led support models have gained increasing popularity in suicide prevention. While previous reviews show positive effects of peer-led support for people with mental health problems and those bereaved by suicide, little is known about the types of lived experience peer support programs in suicide prevention and whether these are effective in improving the health and wellbeing of people at risk of suicide. The aim of this paper is to provide an overview of peer support programs that aim to reduce suicidality and are led by people with lived experience of suicide.

We conducted a systematic scoping review, involving a search of three academic (Medline, PsycINFO, Embase) and selected grey literature databases (Google Scholar, WHO Clinical Trials Registry) for publications between 2000 and 2019. We also contacted suicide prevention experts and relevant internet sites to identify peer support programs that exist but have not been evaluated. The screening of records followed a systematic two-stage process in alignment with PRISMA guidelines.

We identified 8 records accounting for 7 programs focussed on peer-led support programs in suicide prevention. These programs employed a range of different designs and included a variety of settings (schools, communities, rural and online). Only 3 of the 7 programs contained data on effectiveness. With the small number of eligible programs the findings from this review are limited and must be interpreted with caution.

Conclusions

Despite the increased focus of policymakers on the importance of peer support programs in suicide prevention, our scoping review confirms an evidence gap in research knowledge regarding program design, implementation, and effectiveness. More rigour is required in reporting peer-led support initiatives to clarify the underlying definition of peer support and lived experience and to enhance our understanding of the types of current peer support programs available to those experiencing suicidality. Further, we need formal and high-quality evaluations of peer support suicide prevention programs led by people with lived experience to better understand their effectiveness on participant health across different settings and delivery modalities and to allow for comprehensive systematic reviews and meta-analysis in future.

Peer support is a subjective and context specific relationship which is based on lived experience, sharing common life experiences, circumstances, situations and values [ 1 ]. It is generally viewed as a “system of giving and receiving help, founded on key principles of respect, shared responsibility and mutual agreement of what is helpful” [ 2 ]. This mutual experience creates a deep, holistic understanding where people are able to ‘be’ with each other, without the constraints of a hierarchical (expert/patient) relationship [ 2 ] and can focus on the understanding of another’s situation empathically through the shared experience of emotional and psychological pain which can aid recovery [ 3 ]. Peer support programs have been shown to offer alternative support options in crisis and care, and an effective strategy to engage with people that traditional health services fail to reach [ 4 ].

Aiming to address restrictive psychiatric and mental health care models in the late 18th century, the ex-patient/psychiatric survivor movement advocated for mutual support, user-led activities, reduction of marginalisation and stigma and civil rights for mental health patients [ 5 , 6 ]. As such the interest in peer support by health care services and research was first focussed on mental health conditions and in line with a greater focus on recovery-based and consumer-focussed care in mental health [ 3 ]. Since the early 1990s support has come from government and policy agencies and advocacy groups for building a peer support workforce in health care across a broad range of health conditions [ 7 , 8 , 9 ]. More recently Government agencies call to incorporate peer support models within conventional health services for recovery and expand the peer support workforce [ 10 , 11 ], therefore encouraging new services to be offered to people at risk of suicide.

As such, peer-led mental health support programs both in community and services settings have steadily grown and some evidence for their effectiveness has emerged [ 12 ]. For example, studies found that peer support can improve empowerment and hope for recovery for people with severe mental health conditions [ 13 , 14 ], and reduce mental health symptoms for those individuals with severe mental health conditions (e.g. schizophrenia and clinical depression) [ 15 ].

Similarly to the recovery pathway from mental health issues, using peer specialists in suicide prevention may be crucial for constructive coping, support, empowerment, hope and rediscovering meaning in life through the experience of someone who survived suicide [ 16 ]. Some evidence on effectiveness is also available for postvention programs for people bereaved by suicide. Summarised in recent literature reviews, peer support programs were effective in reducing grief symptoms, improving psychosocial and suicide related outcomes, and increasing personal growth and well-being in bereaved suicide survivors [ 17 , 18 , 19 ]. A few qualitative studies also provide insight into how peer support can positively impact on recovery from suicidality through experiencing mutual understanding, non-judgemental environments and acceptance [ 16 , 20 , 21 ]. However, little is known about what types of peer support models exist for people who experience suicidality and whether these are effective in reducing suicidality [ 22 ]. This knowledge gap is at contrast with the growing recognition and presence of peer support programs in health service delivery today.

Addressing this knowledge gap, we undertook a systematic scoping review of literature on peer-led suicide prevention programs with a focus on reducing suicidality in individuals and supporting recovery from suicidality. Our aim was to identify what types of peer-led suicide prevention support programs exist and investigate whether these have been evaluated on their effectiveness to reduce suicide risk. For this review peer support was defined as a suicide prevention program or initiative that was delivered by peers with a lived experience of suicide to people experiencing suicidality or having personal history of suicidality in a formal or informal manner. Hereby formal delivery refers to a specifically designed service or program while informal delivery means an organically grown support initiative mostly found in peer support groups [ 10 ]. Lived experience is highlighted as essential in suicide prevention as it follows the rationale of added benefit of personal experience in recovery [ 8 ].

This scoping review was designed following a methodological framework for scoping studies developed by Arksey and O’Malley’s in 2005 and further revised by Levac et al. in 2010 [ 23 , 24 ]. The review process followed the recommended five stages: identifying the research question; identifying relevant studies; selecting studies; charting the data; and collating and summarising findings. We included key stakeholder consultations as part of our grey literature search strategy, which is described in detail below.

This review was conducted in accordance with the PRISMA recommendations for systematic reviews [ 25 ] and the review protocol was registered with PROSPERO (CRD42018109620).

Identifying the research question

A research team was convened consisting of three researchers in field of suicide prevention (MS, AM, LR) and one researcher with lived experience and consultancy roles in mental health and suicide related peer-support (IO). Using a co-design methodology, the team met to discuss the purpose of the review and was guided by IO’s experience in the peer support sector of suicide prevention in developing the review protocol and research questions [ 26 , 27 ].

Two exploratory research questions were developed: What types of suicide prevention peer-support programs delivered by people with lived experience currently exist? What do we know about their effectiveness? These broad questions allow us to generate an overview of research undertaken on this topic and to identify where the research gaps in peer-led support programs in suicide prevention lie.

Identifying relevant studies

We undertook a systematic search for peer reviewed articles, a search of grey literature databases, and a website search and expert consultations to identify eligible programs. A systematic search of the literature was conducted for articles published between 2000 and 2019 using Medline (PubMed), PsycINFO (OVID interface), and EMBASE (OVID interface). Bibliographies of previous systematic reviews and included papers were also searched. Grey literature was searched to include research that had not been peer-reviewed, including Google Scholar and the World Health Organization (WHO) Clinical Trials Registry (limited to a 5-year period from 2013 to 2018). To identify existing suicide prevention peer-led support programs, we also approached clinical and academic content experts and searched relevant internet sites including organisations known to be active in suicide prevention. See Additional file 1 : Table S1 for a list of identified and screened websites and programs.

Search terms were developed relating to the three key concepts underpinning the literature review: suicide, peer support and lived experience. These were in alignment with our definition of lived experience peer-led support programs in suicide prevention. Alternative terms for peer support were developed and refined during iterative test searches. The final search strategy was developed using medical subject headings and free text words related to peer support and suicide prevention. Search terms were adjusted to fit the requirements of different databases. A complete list of search terms by database is available in Additional file 2 : Table S2.

Study selection

All records were imported into Endnote (version X8.2) and screened for inclusion in two stages. In the first stage, one researcher (AM) screened titles and abstracts for potential inclusion. In stage 2, the full texts of retrieved articles were screened independently by two researchers (AM and MS). Discrepancies were resolved in a meeting between the two researchers. Google Scholar records were screened first by title and abstract and then by full text by MS. WHO Clinical Trials Registry entries were screened by LR. Grey literature was retrieved by IO via internet search and consultations with experts in the area and then screened for inclusion in a team meeting by IO, LR, MS and AM.

Records were eligible if they included a peer-led support program with a focus on suicide prevention for people who experience suicidality. Peer supporters had to have lived experience of suicide; they could be community volunteers, people with similar experiences, or health professionals/health care staff if they had a lived experience of suicide and this informed their support role as peer supporter. Our review was not restricted to programs with matched lived experiences. There were no restrictions on the delivery mode of the programs; for example, programs could be delivered one-on-one, in group settings, as telephone support, online, at home, or in respite care.

We excluded records if programs were not delivered by people with a lived experience of suicide or where this could not be determined from the program description; were suicide bereavement programs; were capacity building or workforce training programs such as gatekeeper training, suicide awareness raising or suicide literacy programs; were focussed on improving mental health more broadly; or were a component of a multi-component intervention and not described separately within the larger program.

Articles in academic databases and Google Scholar had to be published between January 2000 and August 2019 and trials had to be registered on the WHO Clinical Trials Registry between 2013 and 2018. Academic databases were first searched on 14 June 2018. A second search of the academic databases was run on 29 August 2019 after the authors became aware of new evidence published since the original search. Google Scholar was searched on 21 June 2018 and the Trial Registry was searched on 7 September 2018. There was no time restriction on programs and records identified through expert consultation and web searches. We included any evaluation reports of eligible programs, irrespective of study design, setting, participant age, and publication language, so long as they could be translated into English. The Flow Diagram in Fig.  1 includes the number of records at each screening stage for all data searches and data sources combined.

Flow diagram illustrating the literature search process

Following these criteria, we identified 4077 records through electronic searches and 408 through searching other sources including grey literature, websites and expert consultations. Following removal of duplicates, 3058 records were screened by title and abstract information. This led to the exclusion of 2925 records. The remaining 133 records were read in full text by AM and MS who reached consensus on the final inclusion of 8 records according to the selection criteria. Of these 8 records, two referred to the same program, and were therefore summarised as one program in the results section.

Charting the data

Records identified for final inclusion were extracted into a charting table which documented the following information: Reference, title and country of the program; program description including setting modality and lived experience mode; study aim and methodology; sample characteristics and key findings (if the program had been evaluated). Table  1 lists details on all identified programs.

Collating and summarising findings

The information in the charting table was then synthesised in accordance with the two research questions of this paper. Due to the variation in study design and the absence of evaluation data for many identified programs we focussed on a narrative summary of studies. First, we provide an overview of the types of peer support suicide prevention programs (research question 1) by briefly summarising programs by their setting, modality and the role of lived experience. Secondly, for those programs that had been evaluated we characterise the study aim and methodology and discuss key findings regarding their effectiveness for suicide prevention (research question 2) (Table  1 ).

Types of suicide prevention peer support programs

Our search identified eight records that fulfilled the inclusion criteria. These described seven programs that were from four different countries: USA [ 3 ], Germany [ 2 ], China [ 1 ], and Australia [ 1 ], and which varied in setting and design (see Table  1 ). Of the seven programs, four included an evaluation component [ 28 , 29 , 30 , 31 , 32 ] and three provided descriptive accounts of a program [ 33 , 34 , 35 ]. Four peer support programs provided group support [ 28 , 29 , 30 , 31 , 34 ], two were designed to deliver one-on-one support [ 32 , 33 ] and one program included mixed modes of support [ 35 ]. Regarding the program settings, two programs were delivered in clinical settings [ 32 , 35 ], two in the community [ 28 , 33 ], two online [ 29 , 30 , 31 ] and one in schools [ 34 ].

Salvatore [ 35 ] presented a mixed mode peer support program within a psychiatric hospital. It was offered to patients of the hospital and their families. The hospital employed two peer support staff to deliver one-on-one peer support as well as group support. While this program has been implemented as part of the Montgomery County Emergency Service, evaluation data on its effectiveness has yet to be published. The second program designed for patients in clinical settings was the Peers for Valued Life (PREVAIL) program [ 32 ]. This program is a one-on-one support service for people who had attempted suicide and were patients of a psychiatric ward. Patients were teamed up with a peer specialist with lived experience of suicide and weekly meetings were held for up to 12 weeks after discharge from the ward. Peer specialists received training on risk assessment, using suicide prevention tools, communication and relationship building and motivational interviewing. In situations of acute risk clinicians were contacted. The aim of this program was to reduce suicide risk post-discharge from a psychiatric ward.

The two community-based suicide prevention programs were designed to provide support to those in crisis or experiencing suicidal ideation. Firstly, the Alternatives to Suicide program (USA) runs peer support groups for people experiencing suicidality [ 28 ]. Open group discussions are facilitated by trained peer supporters to enable conversations around the reasons and factors that may have contributed to someone wanting to die. Reflective of the key principles of Validation, Curiosity, Vulnerability and Community the conversations are non-judgemental and free of boundaries. Groups provide a safe and comfortable space to talk and focus on offering a non-clinical environment to build trust. Secondly, the Peer CARE Companion Program (Australia) offered through the Way Back Support Service is a new program which is currently being trialled [ 33 , 36 , 37 ]. It is directed at supporting people with a lived experience of suicide (experiencing a suicidal crisis or after a suicide attempt) in one-on-one peer support settings. The program was developed through a collaboration between three mental health organisations in Australia (Beyond Blue, New Horizons and Roses in the Ocean). Two trials and a consultation process including people with lived experience in 2017 and 2018 led to a revision of the program and the results of a second trial are yet to be released.

Two programs were set online using data from online messaging boards [ 29 , 30 , 31 ]. Both aimed at better understanding the benefits and risks of participation to people experiencing suicidality by looking at the effect that using online messaging boards has on participants. These online messaging boards are best described as informal group support interventions. While meaning to support people who experience suicidality, due to their open entry format they allow both people with lived experience and non-suicidal people to participate. The content is participant/online user driven with limited control for quality and safety for people at risk.

Finally, a school-based program aimed at early detection of at-risk youth in Chinese schools, offered peer group support sessions led by students and supported by teachers and the school community [ 34 ]. Students at risk were identified by peers or teachers and invited to participate in student-led support groups that met regularly. Teachers visited the groups monthly to help address any issues if needed. Group membership was voluntary and group leadership rotated. Group members were taught how to recognise unhappy and depressive behaviour in peers. Group leaders reported to the teacher and were able to refer students further if concerned.

With the exception of the school-based peer support program, which broadened its scope to include mood, depression and self-esteem as early warning indicators of suicidality, all programs were specifically aimed at supporting people with a lived experience of suicide. It was however decided to include the school based intervention as its overall goal was described as reducing suicide risk in youth.

Effectiveness of suicide prevention peer support programs

Three of the seven identified programs contained evaluation data; two were quantitative studies [ 28 , 29 , 30 ], one was qualitative [ 31 ] (see Table  1 ).

The Alternatives to Suicide program reported early findings from internal feedback surveys with attendees of the support groups [ 28 ]. Findings indicate that attending the groups was perceived as helpful as participants felt that they could talk freely about their experiences. Attending the groups had improved at least one area in attendees’ lives. Areas of greatest improvement were increased sense of community and a better understanding of why suicidal thoughts may come up.

Kral and Eichenberg found that participation in online peer support forums decreased the intensity of suicidal thoughts [ 29 , 30 ]. The authors collected data from participants of the online forums via an online survey. Thirty-one percent of participants self-reported a decrease in intensity of suicidal thoughts as a result of their participation in the messaging boards. While 22% of respondents said they were more motivated to seek professional help, using suicide messaging boards did not increase help-seeking outside the forums. The main motivation for using online forums was for emotional support, to feel understood and receive comforting reactions.

In a qualitative analysis of threads from a suicide online forum Niederkrotenthaler and colleagues [ 31 ] found that participation in this forum can help to improve a person’s suicidality. The authors downloaded threads from seven pre-identified suicide message boards and thematically analysed a random selection of these threads. Several communicative strategies were associated with psychological improvements in online forum participants; these were receiving constructive advice, being actively listened to, receiving sympathy for one’s struggle, and provision of alternatives to suicide by other members of the forum.

While the Pilot Randomised Controlled Trial of the PREVAIL program did assess the programs feasibility and acceptability by collecting quantitative and qualitative data on peer specialist performance, this trial was unable to assess the programs efficacy in reducing suicidality in participants due lack of power [ 32 ].

Peer-led support programs are increasing in mental health and suicide prevention and are seen as worthy additions to conventional clinical care and alternative support options for community care [ 38 ]. While there is evidence for the effectiveness of peer support programs for people with severe mental illness and also for people bereaved by suicide [ 14 , 18 ], only little and mostly anecdotal data has been published on peer-led support programs with a focus on reducing suicidality. While Government organisations and peak agencies are calling for an inclusion of peer-led support into standard mental health care models, the evidence on what these support services look like, how they can be integrated into conventional care and how effective they are as a stand-alone service is lacking. This led to believe that research in this space is still in its infancy and therefore warrants further attention.

This study is the first scoping review of published literature on peer support programs for people experiencing suicidality. We systematically searched academic databases, grey literature databases, searched the web and consulted experts in the field, strictly focussing on peer-led support programs that set out to reduce suicidality in participants. We strictly excluded programs with a broader focus on mental health and also excluded bereavement programs. Our search identified 8 records accounting for 7 programs that focussed on peer-led support programs in suicide prevention. The 7 eligible programs employed a range of different designs and included a variety of settings (schools, communities, rural and online). Only three programs provided evaluation data, and this data was descriptive on all accounts. This small number of eligible programs highlights a general scarcity of publications on peer-led suicide prevention programs and their evaluation. While the little data available indicates some positive and promising results for peer-led support in suicide prevention, it remains anecdotal at this stage. Despite the increased recognition of peer-led support programs this review highlights that the evidence gap on effective designs and efficacy of programs persists.

Our findings hint at the potential for online forums as a support hub for people with lived experience of suicide and the potential for increased research for peer-led support in this setting, keeping in mind the risk that these unmoderated environments can carry. During the screening of records we identified a large number of community driven initiatives, yet none of them had been evaluated and many focussed on awareness raising and training of support workers and were therefore not included here. In essence there is an evidence gap for peer-led community-based suicide prevention programs regarding their effectiveness to reduce suicidality in the community.

On an exciting note, our consultations with experts suggests there are signs for new peer-led community-based peer support programs to be developed and future evaluations of some of these programs are planned. The pilot trial of the PREVAIL peer support program shows that it is possible and feasible to integrate peer support into the care program for people who experience suicidality, yet formal evaluation of these kinds of programs is needed to determine their effectiveness to reduce suicidality [ 32 ]. Since the potential for peer-led support in suicide prevention has increasingly been acknowledged by policy makers [ 39 ] we anticipate that this in turn will positively influence program development and evaluation in the future and that we will continue to expand our knowledge and understanding of peer-led suicide prevention.

Challenges and limitations

In screening the literature, we identified that 84 records had to be excluded in the full-text review stage due to either not providing enough information on the nature of the lived experience of peer supporter workers or because lived experience was defined more broadly and not specific to suicidality. For example, it was frequently unclear if a peer support program was in fact peer-led or led by a clinician, and when the program was peer-led it did not specify if the peer supporter had lived experience of suicide or whether this was defined more broadly in the context of mental health. It is possible that the lack of clarity in the definition of peer support may have led to the exclusion of otherwise eligible programs during the screening process of this review.

Further, we found that in some programs the definition of peers was not aligned with our selection criteria. Some programs described their intervention as peer group support, yet the group was led by a health professional [ 40 ]. Others had a peer supporter as co-facilitator alongside a leading health professional, therefore not qualifying as a peer-led program [ 41 ]. In particular, school-based programs working with students tended to select peers on the basis of age or belonging to the same social group but did not make suicidal experiences part of the condition for becoming a peer supporter [ 42 , 43 ].

Despite the effort that has gone into defining peer support and lived experience in the context of suicide prevention in recent years [ 2 , 10 ], this seemingly has not yet translated into research designs and publications. The findings from this review highlight that authors follow varying definitions for peer-led support and often fail to provide adequate detail in the description of their program about what constitutes peer-led support in their respective program. This limits our understanding of the nature of peer support within existing programs and ultimately affects what implications we can draw from existing literature on the effectiveness of peer-led support suicide prevention programs.

Implications for future research, policy and practice

To advance knowledge on peer-led support programs in suicide prevention we suggest a few areas for future investment. Firstly, the development of a framework for standard reporting on peer support initiatives would greatly improve our understanding of the breadth and depth of current peer support programs [ 44 ]. In addition, improved quality of reporting on peer support roles in suicide prevention programs would help to clarify the underlying definition of peer support. Secondly, we need high-quality evaluations of peer support suicide prevention programs and of peer-led components within larger programs to better understand their effectiveness on participant health across different settings and delivery modes and to allow for comprehensive systematic reviews and meta-analysis in the future. This evidence can help enhance our efforts to better integrate peer-led support with conventional crisis support and find mutual benefit in both. Thirdly, while peer support is generally accepted as a positive addition to care by legislative bodies, we currently lack models for the efficient and effective integration of these programs alongside conventional care [ 38 , 45 ]. Addressing this issue would facilitate peer support to become a care component in its own merit.

It should also be noted what is already known about the positive effects of peer-led support in other related areas. While the knowledge is scarce on peer-led suicide prevention programs, it could be beneficial to revisit evidence from mental health peer support and investigate whether similar approaches could be adapted to suicide prevention. This practical approach could then be subject to further testing and refining to cater to specific needs in suicide prevention.

While peer support programs are seeing greater support in the community, in health care and by policy makers, very little is known about their effectiveness in the context of suicide prevention. This scoping review set out to review the evidence available to date. Yet, we identified very few peer-led support suicide prevention programs and even fewer evaluations. To improve our understanding in this field we encourage greater clarity in the reporting of key program characteristics and components and highlight the need for formal program evaluation. This will greatly assist in creating a vital evidence base to inform future program development and implementation which is much needed in this space.

Availability of data and materials

All data generated or analysed during this study are included in this published article and its supplementary information files. The literature compiled through this search is available through publications and the internet.

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Acknowledgements

We would like to acknowledge the support of the National Leadership in Suicide Prevention Research Project, led by Prof. Jane Pirkis at the Centre for Mental Health, the University of Melbourne, and its Steering Group members who provided valuable feedback on this review.

This study was supported through funding from the Australian Government Department of Health.

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AM designed the study in consultation with LR, MS and IO. AM and MS finalised the search terms, conducted the search and screened entries from academic literature databases. MS carried out the search and screening of Google Scholar entries. LR carried out the search and screening of entries from the WHO Clinical Trials Registry. IO searched websites and consulted with content experts in the field, whilst discussing findings with MS, AM and LR. MS compiled the charting table, summarised the findings, and drafted the manuscript. All authors read and approved the final manuscript.

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Additional file 1: table s1..

Search strategies by data bases.

Additional file 2: Table S2:

Programs identified through web search and expert consultations and screened for inclusion.

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Schlichthorst, M., Ozols, I., Reifels, L. et al. Lived experience peer support programs for suicide prevention: a systematic scoping review. Int J Ment Health Syst 14 , 65 (2020). https://doi.org/10.1186/s13033-020-00396-1

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• Main Section

Portions of this section adapted from The Self-Help Leader's Handbook: Leading Effective Meetings by Adrienne Paine-Andrews, Yolanda Suarez-Balcazar, Stephen B. Fawcett, and Leslie Borck Jameson, with the collaboration of Melody G. Embree, published by the Research and Training Center on Independent Living at the University of Kansas.

Did you know that there are over 500,000 support groups in the United States? Because they are both inexpensive and effective ways to offer assistance to people dealing with a variety of concerns, support groups have become a common method of serving the needs of people who are experiencing problems in their lives.

Support groups can be found in big cities, small towns, and even rural areas, dealing with anything from substance use and gambling addiction to surviving domestic violence to gender issues. 

If your group or initiative does service work with people who might benefit from talking to others who have similar experiences to their own, perhaps you should consider adding a peer support group to the services you offer.

What are peer support groups?

Support groups - also often referred to as self-help groups - are groups of people who gather to share common problems and experiences associated with a particular problem, condition, illness, or personal circumstance. In a support group, people are able to talk with other folks who are like themselves - people who truly understand what they're going through and can share the type of practical insights that can only come from firsthand experience.

Some of the common characteristics of support groups include:

• They are made up of peers - people who are all directly affected by a particular issue, illness, or circumstance
• They usually have a professional or volunteer discussion leader or facilitator
• They tend to be fairly small in size, to better allow everyone a chance to talk
• Attendance is voluntary (although sometimes people are required to attend support groups by employers or the court system, especially if criminal or destructive behavior has been involved)

Why create and facilitate a peer support group?

There are many benefits to peer support groups:

• When someone doesn't know many - or any - other people who are going through what he is coping with, he can feel isolated and stigmatized. Support groups help people with a problem or illness feel less alone and more understood.
• Support groups don't cost much to run - advertising for the group and maybe some refreshments are all you'll probably need to pay for. Another cost might be meeting space, but you can usually get someone to donate it.
• Support groups empower people to work to solve their own problems.
• Members can share information, keeping one another up to date on news of interest to them.
• Among people who are experiencing similar problems, there is a unique emotional identification that is different from the type of support that can be gotten from professionals.
• Members act as role models for each other. Seeing others who are contending with the same adversity and making progress in their lives is inspiring and encouraging.
• A support group is a safe place for someone who needs to talk about intensely personal issues, experiences, struggles, and thoughts.
• Talking to a counselor or doctor can be very intimidating for some people, because those relationships tend to place more power with the professional. In a support group, members are equals; this can make people feel much more comfortable opening up about their problems.
• Talking to others in support groups reduces anxiety, improves self-esteem, and helps members' sense of well-being overall.

Who can be served by peer support groups?

Almost anyone! At any given time, over 6.25 million Americans are using self-help groups, and about 15 million have participated in such a group at some time in their lives. Support groups are used to address a myriad of concerns, such as:

• Diseases, injuries, or chronic medical conditions
• Eating disorders
• Sexual identity questions
• Physical disabilities
• Bad or unhealthy habits
• Emotional problems
• Bereavement

Besides serving people directly affected by a problem, support groups often welcome family members or friends of those experiencing illnesses or difficulties. Also, many independent support groups exist just for family members or friends: for example, one such group is Al-Anon, a group for families and friends of alcoholics.

How do you create a peer support group?

Think about what you want to accomplish.

Decide what your group's purpose will be and who you want to reach. You might find it helpful to write vision and mission statements for your support group.

Find out whether there are existing national, regional, or local groups your group can be involved with

There are several benefits to setting up your support group under the auspices of a larger organization, if you can. A larger organization can often offer resources and assistance in setting up a new support group. The name recognition that comes with affiliating with a big, well-known organization can give your group more credibility. It can also make it easier for people who need your support group services to find you. Finally, working with a larger organization keeps you from having to "reinvent the wheel" in deciding how the group will operate - you can take advantage of a tried and true model.

Using a fictional example, let's look at how someone might set up a support group with the help of a larger organization.

Yoshiko's support group Yoshiko's sister was recently diagnosed with muscular dystrophy. Feeling frustrated and isolated, Yoshiko wanted to start a support group for the disease's sufferers and their families. After carefully studying this section of the Community Tool Box, Yoshiko decided to find out whether the Muscular Dystrophy Association , a national organization, sponsored a support group in her town. She visited the MDA's website and found out that they offered a group in a nearby town, but there wasn't one in her city. After Yoshiko called the organization's national office and found out the many ways that they could help her new support group, Yoshiko decided to start a local MDA support group rather than an independent one.

Consider whether the group will meet for a specific period of time or for an indefinite period of time

Support groups can be long-running, or they can be restricted for certain periods of time. For example, the local crisis center may offer a six-week support group twice yearly for people who have lost a family member to suicide, rather than a single, year-round group. This type of time-limited format is best suited to crisis situations, such as bereavement or divorce. A drawback of this format is that the group may not be available at a time that someone needs it. Problems that are more long-term in nature - a chronic disease, for example - are better served by ongoing, long-term support groups.

Decide whether the group will be open or closed

Open support groups are those in which new members are welcome to join at any time during the life of the group. This may also mean that anyone can join the group - friends, family members, etc.

In closed groups, people are only allowed to join the group at certain times (e.g., for the first three weeks only) or under certain circumstances (e.g., groups that are only for women). Some organizations offer both types of meetings - open meetings, which anyone can attend, and closed meetings, which are only for people going through the program.

If you plan on working on a very specific issue and want the entire group to go through the process at the same time, you may want to consider having a closed group. However, open groups are best for most kinds of support groups.

Set a time and place for your support group to meet

Decide on a time that will make it possible for the most people to be there; for example, if your group members are likely to be church-goers, it wouldn't be a good idea to schedule meetings for Sunday mornings. Mid-afternoon on weekdays won't be good for most people who work during the day. Usually, early evenings on weekdays are the best times for the most people.

Picking a good location is far more crucial than you might think. If you work with an organization or coalition that has meeting space of its own, you might want to have your support group meet there, but don't automatically assume that this is the best space for it. You might find that a school, church, restaurant, library, or some other public building is better suited to your needs. Depending on the type of group, members may want to be discreet about their attendance, and may therefore be less likely to come if the group meets in some heavily-traveled place where they might be seen. A support group for former child molesters might want to be as nearly invisible as possible, for instance. While that's a particularly outrageous example, the same might be true for Al-Anon or a group for pregnant teens.

First and foremost, the location should be easily accessible for the people who will be coming to the support group. Is the building in an easy place to find? Is it accessible to people who use wheelchairs, canes, or service dogs? Is there adequate parking nearby?

The location should also be somewhere where people can feel comfortable enough to talk about their problems and able to offer each other support. If you're working with survivors of violent crimes, meeting in a high crime section of town or next door to the county jail might make people in your group uneasy or reluctant to even show up.

While the location you decide on should be accessible and comfortable, it also needs to fit the type of group you want yours to be. For example, meeting in a member's home can add an element of comfort, but groups are much more accessible to newcomers if held in public places; therefore, meeting in somebody's home should probably only be done if it's a closed group.

When you finally have a location picked out, make any needed room reservations or other arrangements, and you're ready to move on!

Select a group leader or facilitator

Picking the right person to lead your support group is of utmost importance. The group leader or facilitator opens and closes the meetings, sets the tone for the discussion, helps members learn how to listen and offer support to each other, and deals with any problems that come up during the meeting. The ideal facilitator will possess the following qualities:

• Flexible schedule : He should have enough time to perform the required tasks and commit to be there for every meeting.
• Lots of energy : He should have a positive attitude, be in generally good health, and be able to work after hours if necessary.
• Ability : Ideally, he should have experience in facilitating such groups. He should also be responsible, articulate, fair, organized, and able to work well with others.
• Support : Your facilitator needs to have access to needed resources to run the group (a phone, a car, etc.), and people he can rely on for assistance, if necessary.
• The desire to do the job : He should have an interest in the topic or at least a commitment to helping others. It helps if the facilitator has some sort of affinity for the group and its topic. For example, if your support group is for survivors of breast cancer, then a good facilitator might be someone who has survived breast cancer herself, has been close to someone who experienced it, or at least has had similar experience with other types of disease. This isn't to say that people who haven't been personally touched by the topic can't be great facilitators. You might try folks who have done a lot of volunteer work or have an interest in counseling, such as a graduate student in social work or counseling psychology.

The details of the facilitator's job - running the meetings - are explained later on in this section; you may wish to refer to that when selecting somebody for the position.

Decide on any remaining details

Going back to step one, think about what you want this group to be like. This can help you make up your mind about whatever other ins and outs of the group are left, such as:

• How often should we meet? Most support groups meet every week or two.
• How long should meetings last? Most support groups meet for between one and two hours; you may want to have shorter meetings if you end up having a small group or if members' physical problems make sitting through a long meeting uncomfortable.
• Should we serve refreshments? Refreshments help make everyone feel at home and encourage socializing among members; unless they aren't allowed by your location or you run a group that focuses on food issues (such as an overeaters or eating disorder groups), it's a good idea to have refreshments. If you're on a strict budget, you may have to be creative to get it set up. People can take turns providing cheap refreshments, with some discreet help if someone simply doesn't have the resources to do so. Or perhaps someone knows a merchant or restaurant who has some connection to the purpose of the group, and would be willing to donate refreshments.

Recruit members for your support group

Consider how large you want the support group to be before you start recruiting. Generally, it's best to have a group that's large enough to function well even when some of the members are absent, but small enough for all the members to feel comfortable. As a rule, 5 to 15 people is a pretty good number; anything larger too easily becomes unmanageable and impersonal.

There are many ways to get the word out about your group, and the most successful support groups usually use some combination of all of them.

Use referrals

• Network with other groups and professionals in your area. Let local clergy, doctors, administrators, agency directors, social workers, media personnel, nurses, and other such people know about your group, and encourage them to tell people about it. Send out letters and, if you have them, brochures or flyers to the offices of local organizations that address your group's area of concern -- e.g., the local mental health agency or chapter of the American Cancer Society. You might also do presentations to some agencies and organizations
• If your city or county has any community information and referral hotlines, be sure that they have information on your support group
• If the support group is related to a health matter, be sure to send information to your local hospital's social services and community health education departments
• Find out which agencies or organizations publish community or social service directories and request that your group be included in the next one

Use the media

• Posters and flyers : These can be posted at clubs, shops, hospitals, churches, libraries, schools, post offices - just about anywhere that you think interested people might see them
• Press releases : Sending information about your support group to the local press might interest them in doing stories on your group, which can generate interest
• Paid advertising : Ads in the local newspaper, as well as those in publications or newsletters put out by agencies or businesses that reach the same folks you want to are a good idea, if you can afford them.
• Letters to the editor : These can be used to tell the public about your group. They're more likely to be printed if they're in response to a story the paper has published about a related topic
• Public service announcements : Getting these aired on local radio or television stations can get the word out to large numbers of people

Use personal invitations and word-of-mouth

• This is the most informal method of recruiting people for support groups, but it's the most effective. The "people chain" happens when one person tells another person about a group, and then that person tells another, and so on. Tell everyone you can about the group, and ask them to tell others. When your group starts meeting, encourage members to tell others about the support group.

Once you have enough members, contact them to let them know the date and time of the first meeting. Give them a couple of weeks' advance notice so they can make any necessary adjustments in their schedule, and follow up with a postcard or telephone reminder a few days before the meeting.

How do you facilitate a peer support group?

You've put in a lot of hard work in preparing for your support group to begin, and now the day has arrived. If you are the group's facilitator, here are some helpful guidelines for running these meetings.

Prepare yourself for the meeting

Take a few minutes to think about possible topics for discussion. If this isn't your first meeting, review the topics that were talked about last time. Go over any notes you took. This can help you remember to bring up things that members might want to revisit or give updates on. If you plan to make any announcements of community events or activities that may be of interest to the group, make sure you have them ready.

Prepare the room for the meeting

Arrive 20 to 30 minutes early to arrange the room. Put the chairs in a circle large enough for latecomers to fit in, with enough room for folks who use wheelchairs to easily join. If you're going to have refreshments, set them up on a table to the side or back of the room. If you're going to use name tags, have them ready. Have a pen and paper to take notes.

Start the meeting

As people begin arriving, be sure to make eye contact and say hello, greeting them by name if you've met them before. Call the meeting to order on time, or at least within five minutes of the designated time. This encourages other members to be prompt. It also rewards those who are punctual; if you always start the meeting late because you're waiting for that one person who shows up 15 minutes late every time, you risk alienating those who made the effort to be there on time. A simple "Let's get started," or "Well, it's five minutes after seven o'clock, why don't we begin the meeting," is adequate.

Give preliminary introductions and information

Introduce yourself briefly; if you have some experience with the group topic, be sure to mention it. Make any announcements and ask the group if they have anything to add.

Opening a support group meeting At the first meeting for Yoshiko's MD support group, she was pleasantly surprised to see that 15 people showed up. Opening the meeting, Yoshiko introduced herself: "Hello everyone. My name is Yoshiko Hatori and my sister Miho has been living with muscular dystrophy for over a year now. I'm happy to see so many of you came tonight." She had only one announcement: "By the way, there'll be a car wash fundraiser for the local chapter of the MDA next Saturday from noon to four p.m. at First Baptist Church, so tell as many people as you can about it."

If this is a new group or there are new members present for the first time, explain the ground rules. The most common ground rule for support groups is that everything discussed in the group must be kept confidential. Reminding the group of this from time to time is very important. Explain whether the group is open or closed and what that means. Be sure that everyone understands the rules.

Have everyone introduce themselves, stating their names and a little bit about why they were interested in the group. Then begin the discussion, either by touching on something that was mentioned by one of the members or by bringing up a prepared topic.

Starting a discussion When members of Yoshiko's group were introducing themselves, one young man named Brian mentioned that his family was planning a trip to the Rockies and that he was concerned about his ability to withstand the higher altitudes. She had planned to talk about family issues in general, but Brian's comment gave Yoshiko an idea. When introductions were finished, she began the discussion this way: "Brian, you mentioned your apprehension about this upcoming family trip. Could you tell us more about your concerns?" After the group discussed Brian's trip for a while, Yoshiko said, "I found that Christmas with my family was overshadowed by Miho's MD diagnosis. We were all worried about her, and it really made it hard to just enjoy being together as a family. Would anyone like to talk about what effect MD has had on their own family gatherings?" This prompted several members to jump into the discussion.

Encourage members to listen to each other

Being a good listener - and acting as an example to group members in this regard - means being an active listener, one who is obviously listening and understanding what is being said. How do you let people know that you're listening?

• Body language (leaning slightly towards the speaker, not fidgeting)
• Eye contact (looking in the speaker's eyes, not looking around the room)
• Brief encouraging statements, also sometimes called nonverbal encouragers ("Uh-huh" or "Mmm-hmm")
• Repeating or rephrasing the speaker's last phrase to let him know you understood. ("I can't believe my mother was so cold about it," could be responded to with, "So you were really hurt by what your mother did," for example)

Encourage members to offer support to one another

While being supportive yourself, you must also help others in the group learn how to be so as well. Demonstrate the active listening skills listed above while the member is speaking. Wait 10 seconds or so and then, if no other members have done so, offer support. Group members will usually pick up on this and start offering support themselves. If they don't you may have to ask them questions about how they are affected by the discloser's experience.

For example, Yoshiko might say the following things in her group:

• "Shawna, what can you say to Brian that might help?"
• "How can we give Brian some support now?"
• "What do you think about what Brian is going through, Annie?"

Encourage members to talk about themselves

One advantage of support groups is that they can create an atmosphere in which members feel comfortable talking about and working through very personal issues and experiences. Disclosure - the act of revealing personal information - gives other members a chance to offer support, ideas, and assistance. It also encourages other members to share their own experiences and fosters an atmosphere of trust in the group. To maintain that trust, facilitators may find that they also need to disclose information from time to time.

When a member discloses information, the facilitator may have to guide the discussion to make the member comfortable or encourage others to join the discussion. Asking open-ended questions - those which cannot be answered with a simple "yes" or "no" - is very useful at this point.

Asking open ended questions Camilla, a single mother in Yoshiko's support group, talked about how hard it's been for her to take care of her three children over the past few months. She was having a hard time expressing herself, so Yoshiko coaxed her with these open ended questions: "What's it like for you when you're trying to get your kids ready for school in the morning?" "What have you told your children about what's going on with your health right now?" Yoshiko wanted to get other members to offer support, and she wanted to use Camilla's disclosure to encourage further disclosure from other members. She asked the following open-ended questions: "What sorts of things in your own lives make you feel the way Camilla feels about this?" "How do you all manage it when you have to be a caretaker for others while dealing with your own illness?"

You can also plan topics ahead of time. Some support groups do things like have their members do reading or keep journals of their experiences to help spark discussion.

Offer support

This is the main reason your group exists! Fortunately, offering support is one of the simplest things to do in the course of running a support group. Giving members support can help them realize that reaching their goals is possible, give them hope, or just let them know that you empathize with what they're going through.

Support consists of making statements that show your understanding, sympathy, and concern. Listen for the feelings expressed by the member, and address those feelings. Support can also be expressed through body language (such as making eye contact or smiling) or touch (hugging, patting the member's arm). Care should be taken in using touch as a form of support - in some circumstances, such as a support group for survivors of child sexual abuse, touch may be threatening and uncomfortable instead of comforting.

Usually, members will offer support to each other on their own, or they will quickly pick up on how to do so by following your example. However, you may have to ask questions to coax them into offering support by asking questions.

Providing support When Brian said, "I feel bad because I think I'm becoming a burden to my family," Yoshiko could have offered support by saying: "I know things are really tough for you, but I hope you can take some comfort from how much your family obviously loves you," or "I'm sorry to hear that. But I know that I don't mind the extra time I put into taking care of my sister since she's gotten sick - as a matter of fact, I really cherish that we've been able to spend more time together. You might find that the same is true for your family. Yoshiko could also encourage other members to offer support by saying: "How can we support Brian now?" "Has anyone been through similar experiences with their families?"

Help members solve problems

While solving problems shouldn't be the only goal of a support group, it is something that many members hope for and expect. All members should take part in the problem -solving process so that no single person is seen as the solution to their difficulties. It's the facilitator's job to help members learn how to help each other with problem solving.

Here are the steps to problem solving:

• Clarifying the problem : Make sure everyone fully understands the problem. If you aren't sure what the problem is, ask questions to get more information.
• Talking about the alternatives : Bring up possible solutions to the problem, but be very careful to word them in a way that doesn't give advice. For example, instead of "You should do this," a better wording could be "I wonder what it would be like for you to try this" or "Maybe you could do this." Telling people what to do is not the purpose or responsibility of a support group. It takes away a person's feeling that he can handle his own problems and can make people feel attacked and uncomfortable. Try asking members to tell what's worked well for them in similar situations. You can also ask the person with the problem what he thinks might work.
• Choosing which option(s) to take : Have the group discuss the pros and cons of each suggestion. You can then let the person with the problem come to a decision, or he may want to take some time on his own to consider the possibilities. Let him know that the group cares and wants to know how things turn out.
• Offering help : Sometimes members may offer to assist each other. For example, if the problem being discussed is a member's problems with transportation to the meetings, other members might offer to give that person a ride.

Problem-solving Clarifying the problem: Yoshiko asked some questions to find out more about Camilla's problem: "What parenting duties do you find to be the hardest to keep up with?" "Do you find that these things are consistently hard to get done, or is it more difficult at particular times?" Talking about the alternatives: Yoshiko used open ended questions to gently make suggestions and get members to offer them as well: "What would it be like to ask your kids to help out with chores around the house?" "What has helped you get through hectic times with your kids in the past? " "Would any of you like to suggest things Camilla could do to make things run more smoothly around her house?" Choosing which option(s) to take: Camilla's problem centered around transportation (getting her kids to and from school and soccer practice) and household chores. Camilla decided on the following solutions: Another member's children were part of the same soccer team, so she offered to let Camilla's children ride with them to and from practice One member's sister had children at the same school as Camilla's children. She offered to call her sister and arrange for Camilla's children to carpool with them to school in exchange for help with gas money. Another single mother in the group shared some ideas on using incentives to get her children to help out more with household chores that Camilla decided to try Offering help: As you can see above, two of the three solutions that Camilla decided on involved help from other members.

Close the meeting

Most support group meetings last between an hour and two hours. If the group is caught up in a particularly intense discussion or in helping a member solve a problem, you might go a few extra minutes, but generally it's best to stop before everyone is tired and eager to leave. When the discussion is winding down or when a previously agreed-upon ending time has arrived, wrap things up. Here are some ways you can close the meeting:

• Make a summary statement : Summarize the topics that were discussed and alternatives that were chosen. Highlight any positive observations or solutions that came up.
• Ask for additional comments or questions : Check to see if anyone in the group has anything to add.
• Remind members about the next meeting : Let everyone know the time and place for next time.
• Request volunteers, if necessary : If you need help with donations, refreshments, transportation, or other group needs, this is the best time to ask for it. Asking for help from members encourages them to take leadership responsibilities and fosters a sense of personal investment in the group's success.
• Give a final greeting : Thank everyone for coming, say goodbye, and encourage them to come again.
• Make final notes : Shortly after the meeting, make some brief notes about what was discussed while it's fresh in your mind. This information can be used to jump-start the next meeting. Keep any notes on the group in a safe place to insure confidentiality.

 Closing the meeting After the discussion had wound down, Yoshiko followed the above steps in this way: Making a summary statement: "I see it's getting to be about the time we'd agreed that we'd stop, and I know many of you would like to get home, so I think we'd better wrap up for the evening." Asking for additional comments or questions: "We talked a lot about our families tonight. Are there any last thoughts anyone would like to add?" Reminding members about the next meeting: "Our next meeting will be on Wednesday the 23rd at 7:00 p.m. I hope you can all be there." Requesting volunteers: "Can someone volunteer to call everyone on the phone list a couple of days before the meeting to remind them about it?" Giving a final greeting: "I'm so glad you all came, and I think we got into some really interesting subjects tonight. I hope to see you on the 23rd!" Making final notes: After she got home, Yoshiko sat down with a cup of coffee and wrote some notes on the meeting: "Brian talked about his concerns about how MD will affect his upcoming family trip; Camilla talked about how tough it is to be a single mom with MD. Next time maybe we should focus more on issues that affect the people who are single or not close to their families."

Tips on Keeping a Support Group Going

• Keep track of your group's progress . From time to time, ask members for their feedback on how the group is going. Find out how useful they find it, how comfortable they feel, and their likes and dislikes about the group. Use this information to make adjustments.
• Share responsibility for the group . Letting others take leadership roles helps them feel more committed to and invested in the group. Make sure members know their help is appreciated. Since you may find it's often easier to do things yourself, asking others in the group to take over some responsibilities can be trying. However, no one person should have to do everything, and sharing responsibilities will help you avoid burnout.
• Be sure everyone has a chance to talk . Some people are naturally more talkative than others. Asking questions to get quiet members to speak up is important. It's also crucial to keep the more vocal members on-topic and gently remind them to let others have a turn at times.
• Emphasize the importance of confidentiality . In order for your members to feel safe enough in your support group to self-disclose and work through problems, they need to feel sure that nobody is going to be telling people outside of the group about the group's discussions. Make sure this is well understood by everyone.
• Encourage outside contact among members . Members can offer support to each other outside of meetings. The "buddy" system, used by groups like AA, encourages members to take interest in one another's well-being and form relationships outside the group.
• Keep recruiting . If you have an open group, make sure you continue to get the word out. Groups can stagnate when the membership remains the same all the time, and if members who leave are never replaced your group will not survive.
• Share rewards and failures . Let members know that you appreciate their contributions. When people make mistakes, don't place blame. Don't heap all of the praise when something goes well on any one person - or all of the guilt when things go badly.
• Keep a realistic perspective . Don't idealize the support group. There may sometimes be people that your group won't be able to help; this doesn't mean your efforts are futile. Also, when members leave, it doesn't mean you've failed them. Usually it means that they have used the group as much as they think is useful and moved on with their lives.
• Remember that this is a support group . The dynamics of a group may change over time - for example, it could become more social in function, or it could change focus in terms of topic. No matter how the group changes, your group's primary purpose is to provide support and understanding to its individual members.

Tips on Handling Difficult Group Members

In dealing with difficult group members, support group facilitators must learn a delicate combination of control mixed with kindness. This sort of assertive caring directly addresses problems with the group without insulting or offending members. You may use assertive caring during a meeting to get the discussion back on track, or you may wish to speak to the member in private after the meeting.

Times to use assertive caring:

• When a member is often late to meetings
• When a member talks too much, monopolizing the discussion
• When a member rejects every suggestion that others make - the "yes, but" phenomenon
• When a member appears to have problems that are more than the group can handle - such as someone who's had a change in health and should seek medical attention, or someone who may have psychological problems needing professional attention
• When a member interrupts others or brings up inappropriate or irrelevant subjects
• When a member's problem doesn't match up with what the group is meant to address

The steps to assertive caring:

• Show that you understand the member's position or dilemma : State that you understand the reason(s) behind the member's negative behavior. Use "I" or "we" statements, which show how his behavior affects you and the group. For example, "I know things are difficult for you, but right now we're trying to figure out what Camilla can do about child care."
• Set limits : Gently but firmly correct the behavior. Explain your reasons; letting the member know why you need to change the situation will make him more likely to cooperate. For example, "I know things are difficult for you, but right now we're trying to figure out what Camilla can do about child care, and it's hard to do when you keep interrupting."
• Suggest an alternative : Explain what you'd like to see the member do instead of the negative behavior. For example, "I know things are difficult for you, but right now we're trying to figure out what Camilla can do about child care, and it's hard to do when you keep interrupting. I wonder if we could wait to talk about your problem until after we've come to some conclusions about what Camilla can do."
• Get the member's agreement on the alternative : Make sure the member understands what is being asked of him and agrees to do it. For example, "I know things are difficult for you right now, but we're trying to figure out what Camilla can do about child care right now, and it's hard to do when you keep interrupting. I wonder if we could wait to talk about your problem until after we've come to some conclusions about what Camilla can do. Is that okay with you?"

Support groups are a great way to provide a service to the people your organization or initiative works with, without a huge investment of time or money. Moreover, running a support group is a good way to reach out and get people interested in the other things your organization or initiative does. It's also a way to give back to the community - improving or supporting a good public image for your group. Finally, it's just a good thing to do. With relatively little effort and cost, a support group can make a significant impact in the lives of people dealing with a problem. What better reason can there be?

Online Resources

Center for Community Support and Research. (1995).  Helpful hints for a successful first meeting .

Center for Community Support and Research. (1995).  Keeping a support group going: Five things you should remember .

Center for Community Support and Research. (1995).  Starting a support group: Important Decisions

Center for Community Support and Research. (1995).  Self-help groups: Are they effective?

Self-help Sourcebook Online

Print Resources

Boyd, F., Morris, T., & Bry, B. (1997). Parent and family support groups with African American families: The process of family and community empowerment. Cultural diversity and mental health . Vol. 3, No. 2, pp. 63-92.

Jacobs, M., & Goodman, G. (1989). Psychology and self-help groups: Predictions on a partnership.  American psychologist , Vol. 44, No. 3, pp. 536-545.

Paine, A., Suarez-Balcazar, Y., Fawcett, S., & Jameson, L., & Embree, M. (1990). Self-help leader's handbook: Leading effective meetings . Lawrence, Kansas: Research and Training Center on Independent Living.

Roberts, F., & Associates, and Developmental Research and Programs, Inc. (1988).  Preparing for the drug free years: A family activity book . Seattle, WA: Comprehensive Health Education Foundation.

Organizations

National Self-Help Clearinghouse Graduate School and University Center City University of New York 33 West 42nd Street, Room 1227 New York, NY 10036 (212) 840-7606

OHSU Trauma Center

• Enter keyword Search

Trauma Center

Virtual support group for trauma survivors, “renewal and growth: nurturing healing in springtime”, virtual support group for trauma survivors - “renewal and growth: nurturing healing in springtime”, wednesday, april 24, 5:30-7:00pm est.

Flyer for Virtual Support Group for Trauma Survivors - April 2024 download

Virtual Support groups are free, 90 minute online groups to support survivors of physical injury. Groups are co-led by TSN Trauma Professionals and TSN Peers.

Peer Support Groups

The traumatic injury impacts not only the physical functioning of the individual but the psychosocial health of the patient and their family. Trauma survivors – the patients and the families – may face social isolation, financial upheaval, and continuing feelings of anger, depression, or guilt. A survivor’s sense of self is challenged, and social support systems can be exhausted before recovery is complete. The TSN Peer Support Group is a key component of the Trauma Survivors Network. It offers survivors an opportunity to connect with other survivors and receive and give support. The support group is well suited for easing trauma survivors’ emotional stress, including feelings of isolation, loneliness, depression, helplessness and hopelessness. Groups enable discussions of central concerns of patients and families, such as anger, loss, and mourning, in a supportive, growth-promoting environment. By normalizing the experience of recovery and increasing the survivor’s self-efficacy through education and resource sharing, support groups have the potential to strengthen the survivor’s coping, as well as reduce isolation.

Every support group is facilitated by a trauma survivor.  Some support groups also have a group leader who is a health processional involved in the care of trauma patients.  Most groups meet monthly and often include guest speakers who can talk about topics of interest to the group.

WHAT ARE THE BENEFITS OF JOINING A PEER SUPPORT GROUP?

Some benefits of a peer support group include:

• Gaining support and hope from others facing similar experiences
• Feeling less anxious, afraid or alone
• Sharing experiences and helping others
• Learning new skills for coping and enhancing your life
• Becoming more self confident
• Feeling more in control
• Developing new friendships

HOW TO JOIN A PEER SUPPORT GROUP

If you wish to join a support group, please visit your trauma centers website or the TSN's website to register for upcoming virtual sessions.  You can also go to our online community forum to link up with other survivors and their families for information, support and hope.

Trauma Survivors Network Survive. Connect. Rebuild

• Open access
• Published: 12 April 2024

Participatory methods used in the evaluation of medical devices: a comparison of focus groups, interviews, and a survey

• Kas Woudstra 1 , 2 ,
• Marcia Tummers 1 ,
• Catharina J. M. Klijn 3 ,
• Lotte Sondag 3 ,
• Floris Schreuder 3 ,
• Rob Reuzel 1 &
• Maroeska Rovers 2  

BMC Health Services Research volume  24 , Article number:  462 ( 2024 ) Cite this article

Metrics details

Stakeholder engagement in evaluation of medical devices is crucial for aligning devices with stakeholders’ views, needs, and values. Methods for these engagements have however not been compared to analyse their relative merits for medical device evaluation. Therefore, we systematically compared these three methods in terms of themes, interaction, and time-investment.

We compared focus groups, interviews, and an online survey in a case-study on minimally invasive endoscopy-guided surgery for patients with intracerebral haemorrhage. The focus groups and interviews featured two rounds, one explorative focussing on individual perspectives, and one interactive focussing on the exchange of perspectives between participants. The comparison between methods was made in terms of number and content of themes, how participants interact, and hours invested by all researchers.

The focus groups generated 34 themes, the interviews 58, and the survey 42. Various improvements for the assessment of the surgical procedure were only discussed in the interviews. In focus groups, participants were inclined to emphasise agreement and support, whereas the interviews consisted of questions and answers. The total time investment for researchers of focus groups was 95 h, of interviews 315 h, and survey 81 h.

Conclusions

Within the context of medical device evaluation, interviews appeared to be the most appropriate method for understanding stakeholder views since they provide a scope and depth of information that is not generated by other methods. Focus groups were useful to rapidly bring views together. Surveys enabled a quick exploration. Researchers should account for these methodological differences and select the method that is suitable for their research aim.

Peer Review reports

Medical devices form an intricate part of the healthcare system. Novel medical devices like robots, nano-technologies, and e-health platforms carry the promise of improving healthcare systems [ 1 ]. As medical devices become more pervasive and complex, it is essential to develop and apply these technologies so that they solve the most pressing medical problems in global healthcare systems. Multiple guidelines and regulations exist that stimulate a practice of medical device research and development that is aimed at solving critical health problems [ 2 , 3 , 4 ]. In these documents, one of the recommendations is to actively involve a diverse selection of stakeholders in the research and development process of medical devices. This should lead to better informed decisions during evaluation: aligning devices with the views, needs, and values of stakeholders like medical professionals or patients. This, in turn, can optimise the use of resources spent on research, development, implementation, or use [ 5 ].

There are several methods for stakeholder involvement but these have not been compared against the background of their suitability for medical device evaluation purposes. Studying methods within this context is important, because there are some typical requirements in medical device evaluation. Methods should yield relevant information for research or development choices, preferably foster agreement among stakeholders regarding the future development and implementation of the medical device, and be feasible in terms of resources. By relevant information we mean: any information that helps to understand what features a device should have or how research into a device should be conducted to meet the needs and values of stakeholders. This could involve effectiveness, functionalities, ease of use, affordability, or possible spill overs. By analysing stakeholder needs and practices and making consequent design changes, medical devices can become more valuable [ 6 , 7 ]. Fostering agreement is important to ensure that a device is sufficiently endorsed to make implementation successful. This requires interaction between stakeholders to find common ground [ 8 ]. In entrepreneurial settings where resources are limited and the life-cycle of medical devices is relatively short, development trajectories generally cannot be too long and costly [ 9 ]. Participatory methods can—on the other hand – give insights into development, evaluation, and implementation issues that can occur, and therefore possibly save costs. Due to these unique conditions, it is important to specifically analyse participatory methods in the context of medical device evaluation or development. Some general comparisons of interviews, focus groups, and surveys exist terms of effect on outcomes exist, but these comparisons are not directly applicable to medical devices, nor are they compared all three together [ 10 , 11 , 12 ].

Interviews and focus groups are the most often-used methods in participatory research of medical devices and therefore we compare these in this study [ 13 ]. Surveys are chosen because they are also used in qualitative research and because they methodologically differ on various aspects from interviews and focus groups [ 13 ]. Qualitative surveys offer open text boxes and therefore researchers cannot ask follow-up questions, and there is no direct interaction between researchers and participants. Therefore, we aimed to investigate how focus groups, interviews, and a survey compare in terms of the number of relevant themes they provide, interaction between stakeholders, and time-investment, when conducted in the context of the evaluation of a medical device.

Comparison in one clinical case

We simultaneously employed and compared three participatory methods: focus groups, interviews, and a survey, in an empirical case-study on minimally-invasive endoscopy-guided surgery for patients with intracerebral haemorrhage (ICH). ICH is the deadliest stroke subtype, with a 30-day case fatality of 40%, and of the patients surviving many live with severe disability [ 14 ]. To improve outcome of patients with ICH, an innovative endoscopic device has been developed that has the potential of removing the haemorrhage by minimally-invasive surgery. A systematic review and meta-analysis of randomised trials investigating surgical treatment of ICH showed that minimally-invasive surgery was associated with a reduction in mortality and an increase in good functional outcome, particularly when performed early after symptom onset [ 15 ]. The Dutch Intracerebral haemorrhage Surgery Trial (DIST) pilot study (NCT03608423) has recently demonstrated in 40 patients with ICH that minimally-invasive endoscopy-guided surgery within 8 h of symptom onset using the novel endoscopy-guided approach was feasible, safe, and technically effective for hematoma removal (Sondag, personal communication). At the time of our research, members of our team (CK, LS, FS) were preparing a phase 3 randomised clinical trial to evaluate effectiveness on functional outcome using early minimally-invasive endoscopy-guided surgery in patients with ICH (NCT05460793). Against this background we employed focus groups, interviews, and a survey to elicit [ 1 ] views of stakeholders on the new endoscopic device and (2) the quality of the (received) hospital care for ICH-patients.

Selection procedure participants

We selected participants who are involved in hospital care for ICH and involved in the use of the new endoscopic device. Three stakeholder groups were identified: patients and relatives, healthcare professionals (HCPs), and policy experts. The number of participants that were determined for each method was guided by the concept of information power, which helps to establish how many participants are needed to acquire a reliable dataset [ 16 ]. Patients, relatives, and HCPs were approached by KW, LS and FS. LS and FS had a physician–patient relationship with the invited patients and relatives, or knew patients and relatives because they had participated in a previous studies related to ICH. HCPs were approached via the network of the neurologists involved in this research (CK, LS, FS), which spans over various ICH care institutions across the Netherlands. Policy experts were approached through networks of CK and MR. In the initial invitations, participants were assigned at random to one of the three methods. Participants that were invited for one method were not allowed to participate in other methods, so there were no cross-overs between methods. Subsequently, all potential participants were contacted via e-mail or by phone. After expressing their willingness to participate, they received an information letter and an informed consent form. In these documents, the aim, conditions, practical details, advantages, and disadvantages of participation were explained. All participants were given two weeks to consider participation, and the conditions of participation were again discussed or presented before each interview, focus group, or survey started. All participants gave written or verbal consent on audio tapes. The local certified ethics committee approved the research protocol.

Data collection method 1: focus groups

We organised five 45-min focus groups, all planned on one evening. The first three focus groups were homogeneous: one for patients, one for HCPs, and one for policy experts. These three focus groups were conducted simultaneously. In these sessions, patients and relatives, HCPs, and policy experts convened in their own groups to discuss their views on the intervention with the new endoscopic device and the quality of hospital care. The participants were first placed in homogeneous groups to familiarize and become comfortable with people with a comparable perspective and make participants at ease. They were also placed in these groups to mirror the first round of interviews that was not primarily aimed at interaction but at constructing the different views of participants. The last two focus groups were also planned simultaneously, fifteen minutes after the first three focus groups. In these focus groups the patients and relatives, HCPs, and policy experts who participated in the first round of focus groups were mixed into two heterogeneous groups to discuss findings from the earlier homogeneous focus groups and to discuss how the different perspectives could be brought together. A number of four to twelve participants per focus groups is advised in literature, so we aimed to include six persons in the homogeneous focus groups, and nine persons in the ensuing heterogenous focus groups [ 17 ]. A minimum number of participants for qualitative research has been proposed of 12, so we aimed to include a higher number than that and tried to include a number that was comparable to the interviews [ 18 ]. Each focus group was led by one moderator, who probed for more in-depth answers if needed, and ensured that every participant was able to participate. All moderators were experienced in moderating group discussions and not in any way involved in ICH-care. Two moderators who participated in the first round moderated the second round. We used semi-structured focus groups protocols (see Appendix 1 ). All focus groups were audio-recorded and transcribed verbally. The audio tapes and transcripts were stored in accordance with European data safety requirements [ 19 ]. Due to the COVID-19 pandemic, the focus groups were organised online via a video call platform. The literature on online or ‘synchronous’ focus groups and interviews indicates that there can be some methodological specificalities to online data collection. It might improve the representation of certain groups, e.g. geographically dispersed people and people with disabilities, and it might be easier to generate richer data on sensitive topics. However, visual ques are harder to read [ 20 , 21 , 22 ]. Altogether, online focus groups might therefore be a useful way of data collection, especially for patients with ICH that encounter many mobility issues and social obstacles.

Data collection method 2: interviews

For the interviews, we used fourth-generation evaluation methodology with some minor modifications [ 23 , 24 , 25 ]. All participants were interviewed twice: in the first round they were asked to share their views on the new endoscopic device and the quality of hospital care, and in the second round they were invited to respond to rival claims of other participants. We aimed to include a number that was comparable to the focus groups and above the minimum number of 12 participants that has been proposed [ 18 ]. All interviews were conducted by KW (3 years of interviewing experience). For both interview rounds, a semi-structured interview protocol was used (see Appendix 2 ). All opinions were processed and presented to other participants anonymously. Due to the COVID-19 pandemic, all interviews were taken via a video call platform, or by phone. As described above, online or synchronous data collection has distinctive features and might be a valuable method of data collection. All interviews were audio recorded and transcribed. The audio tapes and transcripts were stored in accordance with European data safety requirements [ 19 ].

Data collection method 3: qualitative survey

The survey started with information about the study, then asked questions about characteristics of the person filling out the survey, including age, gender, education level, profession, and subsequently questions about improvements in the hospital treatment for ICH and the minimally invasive intervention with the new device. Patients and HCPs were asked to list unmet needs of patients and relevant outcome measures. The questions were closed, answer categories limited, but always followed by an opportunity to provide additional information in an open text field. We invited 78 participants, above the number of participants that proposed as a minimum in qualitative research (which is 12) and above the number of participants that is proposed for qualitative surveys (which is 25 to 50) [ 18 , 26 ]. The survey was conducted via Castor, a digital survey platform. The data were stored in accordance with European data safety requirements [ 19 ].

Units of comparison

The three methods were compared on three outcomes: the number of themes, interaction, and the time-investment of the methods, which are described below.

Number and type of themes

The analysis of the number and type of themes was supported by Atlas.ti software (V.9) and performed by one author (KW) to increase consistency. Following the six steps of thematic analysis by Braun and Clarke [ 27 ], the analysis started with reading and coding the transcripts and survey answers. In later phases these codes were arranged and grouped into themes. This process was discussed with MT and RR to check the credibility of the codes and the themes to ensure consistency and minimise a possible bias. We compared the number of themes provided by each method, and determined what themes were constructed in only one of the methods. Counting themes may not be a conventional approach in qualitative research. However, we aim to provide insight into the breadth and thus comprehensiveness of information collected. Because the coding method was consistent along the three methods, we believe counting themes is an adequate unit of comparison.

Interaction

To assess interaction, we performed three analyses to determine: (i) what themes were addressed by multiple stakeholder groups, (ii) which participants interact with each other, and (iii) how participants interact. All these analyses were performed after the data were collected, and supported by Atlas.ti software (V.9). For the first analysis, we calculated the percentage of the themes that was addressed by two or three stakeholder groups in each data-collection method. For example, if both HCPs and policy experts addressed theme X, this theme was marked as ‘shared’, and consequently the percentage of shared themes of the total amount of themes could be calculated. For this comparison, all methods were taken into account, even though participants did not directly interact in surveys. For the other two analyses, we examined how participants interact. To this aim, we adapted coding schemes by Morgan & Hoffman [ 28 ] and Keyton [ 29 ], which can be applied on verbatim transcripts to code how people react. Our main aims for this analysis were to identify how extensive topics were addressed, and to identify whether stakeholders could reach forms of agreement while interacting. The codes as described by Morgan & Hoffman [ 28 ] were most applicable for these aims so we have used their code book, whereas Keyton [ 29 ] more concisely describes how different turns in an interaction can be coded, so we have adapted her coding process. The main change in the coding book that we made, is that we distinguished who interact from the ways how people interact, which was not clearly incorporated in Morgan & Hofmann’s code book (see Appendix 3 ). We coded who the speaker is and to whom this speaker addresses the message, which will be referred to as turn . When a moderator asked a question to participants, or vice versa, this is coded as a ‘moderator-participant’ turn, and when participants ask and answer questions to each other, these are coded as ‘turn between participants’. When a moderator presented views of other participants, and when participants reacted, these were separately coded as a ‘turn between moderator and participant where moderator presents view of others’. Besides turns we also coded how participants interact in the conversation, using the codes ‘question’, ‘answer’, ‘expansion: sharing new aspect of previous topic’, and ‘agreement’, which will be referred to as acts . Acts are mutually exclusive, but multiple acts could be assigned to one turn in a conversation and vice versa, for example when a participant gives an answer to a moderator and directly poses a question the moderator. KW performed the coding process. These analyses were discussed in-depth with MT and RR, to ensure consistency and minimise a possible bias.

Time-investment

We have operationalised time-investment as the absolute number of hours that all the involved researchers and moderators spent on preparing and performing data-collection and analysing the data. We chose not to analyse the investment from the perspective of the participants, because in this paper aims to compare participatory methods from the perspective of the person or organisation conducting them. Time-investment was based on the researchers’ (KW) agenda, supplemented by sources in the literature, to establish the average time that is needed to transcribe a one-hour audio-tape [ 30 , 31 ]. Because the focus groups and interviews were conducted online, travelling time for researchers and moderators was not taken into account. The calculation of time-investment is set out in detail in Appendix 4 .

Researcher characteristics and reflexivity

The research team partially consists of researchers developing qualitative evaluation methods (KW, MT, MR, RR), and partially of neurologists (CK, FS, LS). There was a doctor-patient relationship between FS and some of the participants. RR is an expert on interactive interviews.

Participants

We invited 24 persons for the focus groups of whom 18 participated, 23 for the interviews of whom 17 participated, and 79 for the survey of whom 43 participated (see Table  1 ). In the focus groups, we had equal numbers of patients or relatives, HCPs, and policy makers: 6 participants in each group. The 17 participants in the interviews were patients ( n  = 7 and n  = 3 in round 1 and 2), HCPs ( n  = 8 and n  = 6 in round 1 and 2), and policy makers ( n  = 2 in both rounds). In the survey, we included 21 patients, 18 HCPs, and 4 policy makers. See Appendix 5 for an overview of the types and number of enrolled participants per data-collection methods that is completed with the total number of invited participants. The majority of interviews lasted an hour, but the duration varied from 30 to 90 min. All focus groups lasted 45 min.

The number of themes varied between the different methods (see Fig.  1 ). In the explorative round 31 themes were constructed. In the interactive round 19 themes were constructed and 16 of these were also discussed in the first round, so 34 themes were constructed in all focus groups. The first interview round generated 58 themes, the second 40, and all themes in the second round of interviews had already been discussed in the first round. The survey generated 42 unique themes. An overview of all the themes generated can be found in Appendix 6 .

Number of themes constructed in three data collection methods

All methods generated themes about research improvements for the innovation and care experiences in the hospital but there were some unique themes that specifically came up in one of the methods and not in the others. In the focus groups, four themes were constructed that were not generated in the other methods, two of which related to communication between HCPs and patients and relatives. In the interviews 19 themes were generated, that addressed various aspects of the assessment of the new treatment, such as the characteristics of the study population that ideally should undergo the new treatment in a subsequent research phase, and the informed consent procedure of that research phase. In the survey, 9 unique themes were present, ranging from ‘trust in HCPs’ to ‘outcome measure: feasibility’.

Percentage of themes that is addressed by multiple groups of stakeholders

Figure 2 shows that some themes were addressed by multiple stakeholder groups, whereas other themes were mentioned by one stakeholder group only. In the first explorative round of the focus groups, 16 percent of the themes was addressed by two or three stakeholder groups. In the second interactive round the percentage of themes addressed by multiple groups was 35 percent. In the first round of interviews the percentage of themes addressed by multiple groups was 25 percent in the first round and 58 percent in the second round. In the survey, 21 percent of the themes was addressed by multiple stakeholder groups, and these shared themes are all based on the numeric answers. None of the open-text box answers led to themes that were addressed by multiple stakeholders.

Percentage of themes addressed by multiple stakeholder groups in three data collection methods in round 1 (exploration) and round 2 (reaction)

Which participants interact with each other: turns

Figure 3 depicts which participants interacted with each other. In the first round of the focus group the moderators and participants primarily interacted, whereas in the second interactive round, participants more often interacted directly with each other. In the first interview round, 98% of the turns consisted of direct interaction between participants and the moderator and 2% of the turns consisted of interactions about other participants’ perspectives. In interview round 2, 20% of the turns consisted of direct interaction, and 80% percent of the turns entailed other participants’ opinions. The total number of turns in focus groups round one is 89, in round two 115. The total number of turns in interview round one is 1472 and in round two 894.

Which participants interact with each other: presented as percentage of total number of interactions

How participants interact: acts

Figure 4 presents how participants and moderators interacted in each of the rounds in the focus groups and interviews. In the first round of the focus groups, 93% of the acts consisted of questions, follow-up questions, answers, and expansions on topics, whereas concrete expressions of agreement (18 percent) and support (8 percent) were more prevalent in the second round. In interview round one, 99% of the acts consisted of questions, follow-up questions, answers, and expansions upon previous answers. In round two this was 98%.

Form of interaction as percentage of total number of interactions

Figure 5 provides insight in the time-investment of each of the methods, operationalised as the number of hours that needs to be worked by all researchers. The preparation, data-collection, and analysis of the focus groups took 26, 15, and 54 h within in an overall time span of seven months. Of these 54 h of analysis, 19 consisted of transcribing interviews. The recruitment of participants for the interviews and setting a date took a preparation time that spanned over 5 months. The interviews took 26 h, 45 and 244 h for preparation, data-collection and analysis in a time span of 5 months and 10 months for the first and second round. Of these 244 h of analysis, 140 were dedicated to transcribing. The survey took 57 h to prepare and was completed over the course of nine months, as all questions had to be carefully integrated, checked, and piloted using a digital survey platform.

Accumulative number of hours worked by researchers

Summary main findings

This comparison of focus groups, interviews and a survey in an empirical case study on minimally-invasive endoscopy-guided surgery in patients with ICH showed considerable differences in themes, interaction, and time-investment. In the focus groups relatively few themes were discussed, in the survey slightly more themes occurred, and in the interviews the largest number of themes was constructed. Many improvements for the assessment of the minimally invasive procedure were only discussed in the interviews, such as in- and exclusion criteria for the randomised clinical trial. We assume this is due to the extended time that can be dedicated to data collection, so that more detailed topics can be discussed in-depth. In other respects, there were no clear patterns of topics that occurred in specific methods. In terms of interaction, the focus groups where characterised by relatively much agreement and support. In the interviews agreement and support were seldomly expressed: nearly only questions and answers occurred. In terms of time-investment, the survey required the lowest total time investment: a total of 81 h, followed by focus groups with 96 h, and interviews required the highest time investment with a total of 315 h. There were no significant differences in time investment between the two rounds, neither for the focus groups nor for the interviews. The time allocated for preparation, data collection, and analysis was proportional to the number of interviews and focus groups conducted in each round.

Taking these results together, we can conclude that interviews generated the most useful data within the clinical case because they generated the highest number of relevant themes. They did however require a high-time investment. Focus groups appeared to be a technique that can better be employed to generate agreement and support instead of generating many relevant themes. Surveys do not generate the most comprehensive overview of themes, but can be useful if researchers want to map themes in a quick way without asking follow-up questions. It is important to be aware that we analysed these differences in the context of medical device evaluation, where the aim of participatory methods is to inform the research or development process, rather than merely describing stakeholder views.

Comparison literature

Our results are in agreement with other studies that show that focus groups generate fewer themes compared to interviews, and that focus groups are relatively time efficient [ 32 , 33 , 34 ]. Other studies, however, report that focus groups and interviews generate a comparable large number of themes, whereas our results clearly show that interviews generate more themes [ 10 , 35 , 36 , 37 ]. The discrepancy might be explained by the large number of focus groups that were held and the number of participants that participated in these latter studies. Namey et al. [ 35 ] for example assigned 310 participants to 40 focus groups and 40 participants to interviews. Because these authors include such high numbers in focus groups, they also state that focus groups require a lower time-investment. Based on our findings and the findings in the literature, we can assume that with equal inclusion numbers, focus groups take less time at the expense of generating less data.

Strengths and limitations

The major strength of our study is that we compared three participatory methods in one single empirical case study on the development and evaluation of a medical device. With rigorous control of many contextual and methodological factors we can conclude that the differences in the three outcomes of this study are mainly caused by the characteristics of the data collection methods. Another strength is that we have embedded the comparison in an actual participatory assessment of an innovative minimally-invasive surgical treatment, increasing the ecological validity of the results. Patients and their relatives were involved, they interacted with different physicians and policy makers, and the findings were used in later assessments of the new procedure. Therefore, the results of this study are representative for interactions between these groups. The insights have also informed subsequent quantitative studies on the surgical treatment. Albeit our study is focussed on medical device evaluation, it also has consequences for comparisons of qualitative methods in a broader perspective, because we have adopted conventional focus group, interview and survey methodologies. Our results can therefore be compared with those from related studies outside the domain of medical device evaluation. Finally, we performed an analysis of interaction. The analysis of interaction is rarely done, probably because it is laborious. However, this analysis is crucial because interaction between participants and between participants and moderator(s) is one of the primary aims of focus groups and interviews. By showing who interacts with whom and how, we offer insights in the processes of these methods, which can be of use in the selection of one of these methods by others.

Some limitations should also be addressed. First, there are still some variations in the three research designs that could have influenced the outcomes. Different moderators and stakeholders were involved in each method, and their specific characteristics could have affected the results. Using different moderators and participants was a considerate choice, however, since the use of the same moderator or participants in all methods would have influenced the outcomes, as they would have taken their experiences from one activity to the other. Second, a substantial proportion of themes was found in only two or one of the methods, which indicates that none of the methods generated a complete set of data. This implies that the concept of information power might not have been the most suitable technique to determine the number of participants. Saturation might be a better point to close the data collection phase, especially when a diverse range of participants is included, such as in this study. Third, in the survey a relatively low number of participants were enrolled. The data may therefore not be representative of surveys with higher inclusion numbers. Yet, the survey in this study was constructed for qualitative research aims and not intended to produce quantitatively significant results. Fourth, the data of all three methods were collected digitally, because the data-collection was performed during the COVID-19 pandemic. Therefore, the results may not be directly applicable to face-to-face interactions. As work is increasingly being digitalised and organised remotely, it is likely that in the future qualitative data more often are being collected by means of video consulting applications.

Implications

Our results help researchers and innovators to choose a method that is most suitable for their research aim, both in- and outside the domain of medical device evaluation. First we will place the methodological findings in the clinical context in which we worked. Next, we will discuss contextual factors that are relevant for medical device evaluation in general.

As described in the methods section, three methods were compared against the background of the design of a phase 3 randomised clinical trial to evaluate early minimally-invasive endoscopy-guided surgery in patients with ICH (NCT05460793). The clinical results of our research were used to inform different aspects of this randomised clinical trial, such as the selection of relevant outcome variables and the process of acquiring informed consent in this acute intervention trial. The results were also used to see how hospital care for ICH could be improved in general. All methods generated relevant insights in the context of this study, but interviews generated the most comprehensive body of relevant results for the trial and were thus most useful in the specific clinical context.

As described, there are some implications that are relevant for all types of researchers or innovators that want to employ participatory methods. Elucidating needs of stakeholders might especially be relevant in early development stages since they can be translated in the further development and evaluation of a device. It is thus relevant to have a comprehensive, in-depth assessment of these needs and interviews appear to be most appropriate for that aim. If in later stages more specific development issues need to be resolved, stakeholders could be brought together in a small focus group to make a joint decision. Since financial investments are required for participatory evaluations, the question arises whether the benefits live up to these investments. In the literature, stakeholder involvement is generally considered to be beneficial, but an important caveat is that low budgets and small-scale involvements can lead to flawed stakeholder representation and reproducing existing power differences [ 38 ]. We strongly recommend to invest in participatory development and evaluation as this is likely to be highly beneficial, because the perspectives of stakeholders are embedded in the innovation process.

Furthermore, we posit the existence of overarching methodological implications pertinent to participatory research at large, and delineate some considerations. The body of results generated by focus groups was not as comprehensive as in the interviews. This is possibly due to the social dynamic that is at play between participants and the limited time that each individual speaker is talking, which makes expansive questioning by a moderator on all relevant topics hard to realize. This implies that for comprehensively answering a research question, focus groups are not the most suitable method. Nevertheless, topics can be discussed and resolved relatively quickly in a focus group if the participants are more or less on the same page, which implies that focus groups can be a useful decision-making technique. Interviews can best be used for in-depth analyses of different perspectives, to generate much data, and therefore comprehensively answer a research question. Researchers or innovators may shorten the time-investment of interviews by speeding up the analysis, for example by not transcribing full interviews but writing summaries directly after an interview. Surveys might be suitable if researchers or innovators want to carry out a fast exploration of themes, and do not require interaction or an in-depth explication of topics. Qualitative surveys lack the option for inductive questioning, so they are not suitable if researchers want to apply an open research design. Methods presented in this paper could also be combined, or integrated in a stepwise manner in a research of development process. A researcher might first use a survey to explore multiple stakeholders’ wishes, and subsequently arrange a round of interactive focus groups when fast and definite decision needs to be made. An evaluation trajectory of medical devices is hard to plan in advance and unforeseen issues might arise, and these issues might demand specific participatory methods.

Focus groups, interviews, and surveys have clear methodological differences and provide different results within the context of medical device evaluation. Focus groups can best be used to bring views together, but do not enable a comprehensive analysis. Interviews enable an in-depth analysis of stakeholder views and can best be used to comprehensively answer an explorative research question, but are time-intensive. Surveys can be used for a rapid exploration of perspectives. Researchers should account for these methodological differences and select the method that serves their research aim.

Availability of data and materials

No data are available. All relevant data are presented in this study.

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Acknowledgements

We wish to express our gratitude to Leon Bijlmakers and Anke Oerlemans for their valuable help in guiding the focus groups.

This work was sponsored by a Vici fund by the Nederlandse organisatie voor gezondheidsonderzoek en zorginnovatie (ZonMw) (grant number 91818617). CK and LS are supported by the Netherlands Cardiovascular Research Initiative, which is supported by the Dutch Heart Foundation, CVON2015-01: CONTRAST and the support of the Brain Foundation Netherlands (HA2015.01.06). CK is supported by ZonMw (ASPASIA grant, 015008048). FS is supported by the Dutch Heart Foundation (senior clinical scientist grant, T2019T060).

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KW, RR, MR, MT contributed to the conception and design. KW, CK, LS, RR and MT contributed to the acquisition, analysis and interpretation of data. KW, RR, MR, MT, CK, LS and FS have been drafting the manuscript. MR has obtained funding.

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Woudstra, K., Tummers, M., Klijn, C.J.M. et al. Participatory methods used in the evaluation of medical devices: a comparison of focus groups, interviews, and a survey. BMC Health Serv Res 24 , 462 (2024). https://doi.org/10.1186/s12913-024-10887-3

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Efficacy of a virtual nursing simulation-based education to provide psychological support for patients affected by infectious disease disasters: a randomized controlled trial

• Eunjung Ko 1 &
• Yun-Jung Choi 1  

BMC Nursing volume  23 , Article number:  230 ( 2024 ) Cite this article

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Virtual simulation-based education for healthcare professionals has emerged as a strategy for dealing with infectious disease disasters, particularly when training at clinical sites is restricted due to the risk of infection and a lack of personal protective equipment. This research evaluated a virtual simulation-based education program intended to increase nurses’ perceived competence in providing psychological support to patients affected by infectious disease disasters.

The efficacy of the program was evaluated via a randomized controlled trial. We recruited 104 nurses for participation in the study and allocated them randomly and evenly to an experimental group and a control group. The experimental group was given a web address through which they could access the program, whereas the control group was provided with a web address that directed them to text-based education materials. Data were then collected through an online survey of competence in addressing disaster mental health, after which the data were analyzed using the Statistical Package for the Social Sciences(version 23.0).

The analysis showed that the experimental group’s disaster mental health competence (F = 5.149, p  =.026), problem solving process (t = 3.024, p  =.003), self-leadership (t = 2.063, p  =.042), learning self-efficacy (t = 3.450, p  =.001), and transfer motivation (t = 2.095, p  =.039) significantly statistically differed from those of the control group.

Conclusions

A virtual nursing simulation-based education program for psychological support can overcome limitations of time and space. The program would also be an effective learning resource during infectious disease outbreaks.

Clinical trial registration

This Korean clinical trial was retrospectively registered (21/11/2023) in the Clinical Research Information Service ( https://cris.nih.go.kr ) with trial registration number KCT0008965.

Peer Review reports

The last two decades have confronted the world with a variety of infectious diseases, such as severe acute respiratory syndrome, which first occurred in Asia in 2003 before spreading worldwide, including Korea, in only a few months. Since then, infectious disease outbreaks began to be recognized as severe disasters. Other examples include the 2009 H1N1 influenza outbreak, which caused more than 10,000 deaths worldwide and 140 deaths in Korea; the proliferation of the Ebola virus, which resulted in a fatality rate of more than 90% in Africa in 2014; and the outbreak of Middle East respiratory syndrome in 2015, Zika virus disease in 2016, and coronavirus disease (COVID-19) in 2019 [ 1 ]. The COVID-19 pandemic, in particular, has caused infections among approximately 64 million people and the deaths of 1.5 million individuals as of December 2020 [ 2 ].

Direct victims of infectious disease disasters, infected patients, and quarantined individuals suffer from a fear of stigma or social blame and guilt, but even people who are unexposed to sources of infection experience psychological distress from anxiety and fear of disease or possible death [ 3 ]. They also blame infected people and harbor hatred toward them [ 3 ]. This assertion is supported by an examination of web search behaviors and infodemic attitudes toward COVID-19, which identified superficial and racist attitudes [ 4 ]. Additionally, in research using a health stigma and discrimination framework related to communicable diseases, the authors found that people exhibit negative stereotypes, biases, and discriminatory conduct toward infected groups owing to fears of contagion, concerns about potential harm, and perceptions that individuals violate central values [ 5 ]. Stigmatized individuals experience adverse effects on their health because of both the stress induced by stigma and the decreased use of available services [ 5 ].

Severe and prolonged anxiety, fear, blame, and aggression can lead to mental health problems, including depression, anxiety, panic attacks, somatic symptoms, post-traumatic stress disorder, psychosis, and even suicide and life-threatening behaviors [ 6 ]. Therefore, recovery from the psychological trauma caused by a disaster should be regarded as equally necessary as physical recovery, with emphasis placed on psychological support activities that prevent the deterioration of mental health [ 7 ].

Disasters pose a significant threat to mental health support systems, wherein the lack of healthcare professionals or psychologists trained to address these conditions exacerbates the psychological distress and psychopathological risk experienced by society [ 8 ]. When training at clinical sites is restricted due to infection risks and a lack of personal protective equipment (PPE), an emerging solution is virtual simulation [ 9 ].

A virtual simulation is a simulation modality developed on the basis of video or graphic recordings featuring virtual patients and delivered via either a static or mobile device. It replicates real-world clinical situations and affords learners an interactive experience [ 10 ]. Virtual simulation-based education provides an immersive clinical environment, as virtual patients respond to a learner’s assessments and interventions [ 11 , 12 ]. It enables two-way communication, and allows medical professionals to practice making clinical decisions [ 10 ]. Virtual patients are equipped with voice, intonation, and expressions that reinforce the educational narrative within the virtual environment, thereby enhancing the effectiveness of the learning experience [ 13 ]. One of the primary advantages of virtual simulation-based education is its provision of a safe and non-threatening environment in which learners can practice. It also offers flexible and reproducible learning experiences, thus catering to the diverse needs of learners [ 14 ].

Self-assessment is the most commonly used competence evaluation tool, as it is cost-effective and helps nurses improve their practice by identifying their strengths and weaknesses for development [ 15 ]. Self-assessed competence is also related to the quality of patient care because nurses promote continuous learning by determining educational needs through such evaluations [ 16 ]. The competence perceived by a nurse is inherently subjective given its self-reported nature and poses a challenge in establishing a direct correlation with the actual care of patients [ 17 , 18 ]. However, studies have indicated that increased levels of self-perceived competence are associated with a significant increase in core competencies related to patient care and frequent use of clinical skills [ 19 , 20 ]. Perceived competence likewise influences the job satisfaction and organizational citizenship behavior of nurses and is significantly related to absenteeism, one of the deterrents to the delivery of quality care [ 21 , 22 ].

Competence refers to the possession of qualifications and abilities to satisfy professional standards, as well as the capability to perform tasks and duties in a suitable and effective manner [ 23 ]. Competencies for disaster mental health are crucial for enhancing disaster response capabilities. These competencies encompass a range of skills, knowledge, and attitudes necessary for mental health professionals to effectively support individuals and communities affected by disasters [ 24 ]. Such competencies and how they are affected by simulation-based training have been explored in some studies, which reported a significant increase in competence after exposure to the aforementioned education [ 25 , 26 ].

The simulation education defined in mock training designs based on real situations provides opportunities to exercise problem-solving through various strategies. Problem-solving process is considered key competency through which learners are expected to enhance their relevant knowledge and clinical performance abilities [ 27 ]. In particular, problem-solving processes for identifying and assessing problems and finding solutions are psychological strategies that help people cope and recover after a disaster [ 28 ]. A scoping review on the effect of simulation-based education on the problem-solving process indicated that out of 32 studies reviewed, 21 demonstrated statistically significant improvement in people’s ability to resolve problems [ 29 ].

Simulation training can also address self-leadership, which is an essential self-learning quality that aids individuals in staying motivated and focused on their learning goals. It is also required as a basic qualification of professional nurses, who must be able to take initiative and make responsible decisions [ 30 , 31 ]. Previous studies have reported statistically significant improvements in self-leadership following simulation training [ 32 , 33 ].

Another aspect that benefits from simulation-driven education is learning self-efficacy, which plays a crucial role in predicting learners’ levels of engagement and academic success in online education. It reflects learners’ confidence in their ability to manage their own learning process. It is a significant predictor of both learners’ participation levels and their academic achievements in online education settings [ 34 , 35 ]. Several studies have demonstrated virtual simulation- or online education-induced significant improvements in learning self-efficacy [ 36 , 37 ]. Finally, virtual simulation-based education can also improve the motivation to transfer new knowledge and skills learned through education to clinical practice [ 38 ]. This motivation is considered an essential measure of effective learning for nurses working in the clinical field [ 38 ]. A previous study reported that psychiatric nursing simulation training combined with post-course debriefing significantly increases participants’ level of motivation to transfer [ 38 ].

On the basis of the discussion above, this study evaluated a virtual nursing simulation-based education program on disaster psychology designed to provide psychological support to patients affected by infectious disease disasters.

Study design

This study conducted a randomized controlled trial (RCT) to test the virtual nursing simulation-based education program of interest. The RCT protocol used was based on CONSORT guidelines.

Participants

We recruited nurses working at general hospitals in South Korea. With permission from the nurse managers of these hospitals, a participation notice was posted on the institutions’ internet bulletin boards for nurses for a week. The two-sided test criterion, with a significance level (α) of 0.05, a power (1-β) of 0.80, and a medium effect size of 0.6, dictates that the minimum number of participants per group be 90. The effect size was based on a virtual simulation intervention study conducted by Kim and Choi [ 36 ]. Taking the dropout rate into consideration, we recruited 104 nurses, who were assigned to an experimental group and a control group using the random sampling functionality of the Statistical Package for the Social Sciences (SPSS version 23.0). Out of the initial sample, 11 participants were excluded because they were on vacation, could not be contacted, or provided incomplete responses during data collection (Fig.  1 ).

Flowchart of the randomized controlled trial

The virtual nursing simulation-based education program

This study probed into the virtual nursing simulation-based education program developed by Ko [ 39 ]. The program is implemented using an e-learning development platform, Articulate Storyline, whose operating environment is compatible with all web browsers (Internet Explorer, Microsoft Edge, Firefox, Google Chrome, etc.). It is a mobile-friendly application that can run in devices with Android and iOS operating systems. When an individual uses their smartphone or personal computer to access the server via the web address corresponding to the education program, the content functions execute. Ko’s [ 39 ] program involves five stages of learning completed in 100 min: (1) preparatory learning (30 min), (2) pre-test (5 min), (3) pre-briefing (5 min), (4) simulation game (30 min), and (5) structured self-debriefing (30 min) (Fig.  2 ).

Preparatory learning comes with lecture materials on guidelines for providing psychological support to victims of infectious disease disasters, administering psychological first aid, donning and doffing PPE, and exercising mindfulness through videos and pictures. In the pretest stage, a learner answers five questions and can immediately check the correct responses, which come with detailed explanations. In the prebriefing stage, an overview of a nursing simulation scenario, patient information, learning objectives, and instructions on using the virtual simulation are provided. During the simulation game, a video of the simulation is presented. It starts with a 39-year-old female, a standardized patient who is age- and gender-matched to the scenario, confirmed to have contracted COVID-19 and transferred to a negative pressure isolation room. The patient presents with extreme anxiety and feeling of tightness in her chest. During the game, learners are expected to complete 12 quizzes. In the debriefing stage, a summary of the simulation quiz results and self-debriefing questions are provided, and the comments made by learners are saved in the Naver cloud platform.

The evaluated virtual nursing simulation-based education program (examples are our own work)

Measurements

Disaster mental health competence.

Disaster mental health competence was measured using the perceived competence scale for disaster mental health workforce (PCS-DMHW), which was developed by Yoon and Choi [ 40 ]. This tool consists of 24 questions related to knowledge (6 questions), attitudes (9 questions), and skills (9 questions). Each item is rated using a five-point Likert scale (0 = strongly disagree, 4 = strongly agree), and the responses are summed. The higher the score, the greater the perception of competence in a relevant area [ 40 ]. The Cronbach’s α values of the PCS-DMHW were 0.95 and 0.94 at the time of tool development and the present study, respectively.

Problem solving process

Problem solving process was determined using a tool modified and supplemented by Park and Woo [ 41 ] on the grounds of the problem solving process and behavior survey developed by Lee [ 42 ]. This tool is composed of 25 questions on five factors, namely, problem discovery, problem definition, problem solution design, problem solution execution, and problem solving review [ 41 ]. The reliability of the tool was 0.89 at the time of development [ 41 ], but the Cronbach’s α found in the current research was 0.94.

Self-leadership

Self-leadership was measured using a tool developed by Manz [ 43 ] and modified by Kim [ 44 ]. The tool consists of 18 questions distributed over six factors (three questions each): self-defense, rehearsal, goal setting, self-compensation, self-expense edition, and constructive thinking. The reliability of the tool at the time of development and the present research was (Cronbach’s α) 0.87 and 0.82, respectively.

Learning self-efficacy

To ascertain learning self-efficacy, we used the tool developed by Ayres [45] and translated by Park and Kweon [ 38 ]. This tool consists of 10 questions, and it had a reliability (Cronbach’s ⍺) of 0.94 and 0.93 at the time of development and the current study, respectively.

Motivation to transfer

We used Ayres’s [45] motivation to transfer scale, which was translated by Park and Kweon [ 38 ]. Its reliability at the time of development and the present research was (Cronbach’s ⍺) 0.80 and 0.93, respectively.

Data collection

The experimental and control groups were administered a pretest through an online survey. The web address through which the evaluated virtual simulation-based education program could be accessed was provided to the experimental group, whereas text-based education materials on psychological support for victims of infectious disease disasters were given to the control group. The groups were simultaneously sent the program’s instruction manual, and their inquiries were answered through chat. After the interventions, each participant was administered a posttest through another online survey.

Data analysis

The collected data were analyzed using SPSS version 23.0. The homogeneity test for general characteristics between the experimental and control groups was analyzed using a t-test, a chi-square test, and Fisher’s exact test. The normality of the dependent variables was analyzed using the Kolmogorov-Smirnov test. Changes in the dependent variables between the pretest and posttest were analyzed using a paired t-test. Differences in the dependent variables before and after the groups’ use of the interventions were examined via a t-test and ANCOVA.

Ethical considerations

We completed education in bioethics law prior to the research and obtained approval of the research proposal and questionnaire from the Institutional Review Board of the affiliated university (IRB approval number 1041078-202003-HRSB-070-01CC). A signed consent form was also obtained from each participant after the purpose and methods of the research, the confidentiality of personal information, and the voluntary nature of participation or their right to withdraw from the study were explained to them. All collected data were kept in a lockable cabinet, and electronic data were encrypted and stored. These data are to be discarded after three years.

A total of 93 participants (45 in the experimental group and 48 in the control group) were left after the exclusion of unsuitable respondents. of the between-group comparisons of the subjects indicated no significant differences between them (5% significance level) in terms of general characteristics, such as gender, age, work unit, and clinical experience (Table  1 ).

The score of the experimental group on disaster mental health competence increased from 48.13 in the pretest to 70.51 in the posttest (+ 22.38), whereas that of the control group increased from 53.33 in the pretest to 68.38 in the posttest (+ 15.04). These findings reflect a statistically significant difference in competence between the groups (F = 5.149, p  =.026). The scores of the experimental and control groups on problem solving process increased from 73.07 in the pretest to 88.24 in the posttest (+ 15.18) and from 75.75 in the pretest to 83.77 in the posttest (+ 8.02), respectively. As with the competence findings, these point to a significant difference between the groups in terms of the ability to resolve problems (t = 3.024, p  =.003) (Table  2 ).

The score of the experimental group on self-leadership increased from 54.87 in the pretest to 59.58 in the posttest (+ 4.71), and that of the control group increased from 57.48 in the pretest to 60.10 in the posttest (+ 2.63). These results denote a statistically significant difference in this ability between the groups (t = 2.063, p  =.042). The scores of the experimental and control participants on learning self-rose from 55.40 in the pretest to 58.84 in the posttest (+ 3.44) and from 56.81 in the pretest to 57.13 in the posttest (+ 0.31), respectively. Again, a statistically significant difference was found between the groups (t = 3.450, p  =.001). Their scores on motivation to transfer rose from 49.31 in the pretest to 54.29 in the posttest (+ 4.98) (experimental group) and the score increased from 50.50 in the pretest to 51.85 in the posttest (+ 1.35) (control group), pointing to a significant difference between the groups (t = 2.095, p  =.039).

As previously stated, this research was evaluated a virtual nursing simulation-based education program designed to provide psychological support to patients affected by infectious disease disasters. The results showed statistically significant increases in the experimental group’s pretest and posttest scores on disaster mental health competence, problem solving process, self-leadership, learning self-efficacy, and motivation to transfer.

The experimental group achieved more statistically significant improvements in disaster mental health competence than did the control group. This finding is similar to the statistically significant increase in the average disaster mental health competence shown by providers of disaster mental health services providers and non-expert groups after PFA training involving lecture and practice [ 46 ]. It is also consistent with the significant increase in the scores of school counselors on disaster mental health competence after a lecture and simulation on PFA [ 25 ]. In their study on disaster relief workers, Kang and Choi [ 26 ] measured the participants’ performance competence in PFA after the delivery of a lecture and simulation-based education using a standardized patient. The authors found a significant increase in PFA performance competence, consistent with the present research. Since there are currently no other virtual simulation-based education programs for disaster psychological support available, we compared the effectiveness of various PFA training methods with the program assessed in the present work.

In the current research, the posttest scores of the experimental group on problem solving process significantly increased, similar to the results of Kim et al.’s study on virtual simulation- and blended simulation-based education on asthmatic child nursing [ 47 ]. Both the control and experimental groups (virtual simulation only and blended simulation featuring high-fidelity and virtual simulations, respectively) showed an increase in their problem solving process scores. These results and those derived in the present work are similar because reading and pretest phases were incorporated into the design of the previous study. Given that researchers have used commercial virtual simulations featuring avatars rather than standardized patient videos available through English-based platforms, user experiences may differ, thus requiring a qualitative analysis to identify differences. However, Kim et al. [ 47 ] did not implement a debriefing after the virtual simulation program, rendering comparison impossible. Another research reported that a multimodality simulation education that combines such methods as virtual simulation, the use of mannequins, and part-task training increase increased the scores of hospital nurses’ on problem solving process [ 48 ].

In the present work, the experimental group’s self-leadership scores increased after they used the program, and these scores were higher [ 49 , 50 ]. This difference can be explained by the fact that our respondents voluntarily participated in our research given their interest in self-learning programs for disaster psychological support; even in the comparison studies, participants with stronger interest in leadership education typically exhibited heightened degrees of self-leadership [ 51 ]. The increase in self-leadership scores in the current research is consistent with a previous study involving a two-hour simulation education about PPE donning and doffing, medication administration, and medical specimen treatment in a scenario of patients suspected of having infectious diseases [ 32 ]. Another research showed that simulation education on high-risk pregnancy enhances nursing students’ problem-solving processes and self-leadership [ 52 ].

Learning self-efficacy is a key variable that enables the prediction of learners’ degrees of participation in online education and the prediction of their academic achievements, as it points to the ability to manage their learning processes [ 34 , 53 ]. The results of the current research in this regard are consistent with those of a study on the online practice of basic nursing skills, which increased participants’ learning self-efficacy [ 54 ]. The researchers included an online quiz about basic nursing skills and feedback sections for learners’ self-evaluations of their performance as avenues through which to encourage autonomy in learning. A similar approach was used in the present study, which involved both a pretest for self-evaluation, direct feedback on the virtual simulation, and a self-debriefing session, enabling the participants to reflect on their simulation experiences while reviewing other participants’ answers during self-debriefing. These functions of the evaluated program were expected to factor importantly in the significant increase in the participants’ learning self-efficacy scores.

Many studies on practice education have examined participants’ motivations to transfer knowledge and skills alongside their learning self-efficacies. In the current research, the motivation to transfer scores of the experimental increased, and the difference between the two groups was statistically meaningful. This result is consistent with the findings of Park and Kweon on the simulation education about psychiatric nursing, during which post-course debriefing increased the participants’ average scores on motivation to transfer and learning self-efficacy [ 38 ]. Conversely, Kang and Kim found that a six-week simulation program for alcoholic patient care did not generate a significant increase in the participants’ motivation to transfer and learning self-efficacy scores [ 55 ]. This finding was attributed to the unfamiliarity of the local community scenario used in the research to the participants, who were in their senior year of nursing school [ 55 ]. This limitation was overcome in the current research by administering a qualitative survey of nurses’ actual demand for education on psychological support for infectious disease patients. That is, the survey presented scenarios that the participants needed.

As with other studies, the present research was encumbered by several limitations. First, the self-assessment measures used in this study may be unreliable, because they are based on individuals’ subjective perceptions and interpretations of their abilities. There is also the possibility of respondent fatigue given that the participants were compelled to answer numerous questions. Future studies should incorporate both subjective and objective measures into data collection and consider as concise an evaluation method as possible to prevent respondent fatigue. Second, this study did not establish a direct link between the obtained results and actual changes in practice or improvements in patient outcomes. We propose a follow-up study to investigate the impact of the education program examined in this study on either the mental health of patients or the quality of patient care. Third, simulation-based education tends to be accompanied with more guidance than text-based program because the former has diverse components, including quiz games, and participants are predisposed to allocate more time to simulation-based education. These may potentially influence the results. In the future, we propose to conduct research by modifying education under the same time and guided condition.

This study proposed that a well-designed virtual nursing simulation-based education program can be an effective modality with which to satisfy the educational needs of nurses in the context of infectious disease outbreaks. Such programs can be easily used by nurses anywhere and anytime before they are deployed to provide psychological support to patients with infectious diseases. They are also expected to contribute to enhancing competence in addressing disaster mental health and improving the quality of care of patients afflicted with infectious diseases.

Data availability

The datasets used and/or analyzed in this study are available from the corresponding author upon reasonable request.

Abbreviations

Coronavirus disease 2019

Randomized controlled trial

Personal protective equipment

Statistical Package for the Social Sciences

Analysis of covariance

Psychological first aid

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Acknowledgements

The authors would like to thank Eun-Joo Choi and Dong-Hee Cho for their contributions to the development of the simulation program.

This work was supported by the National Research Foundation of Korea (NRF) through a grant funded by the Korean government (Ministry of Science and ICT) (NRF-2020R1A2B5B0100208).

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This study was conducted in accordance with the Declaration of Helsinki (Association World Medical, 2013) and was part of a larger study. It was approved by the Institutional Review Board of Chung-Ang University (IRB approval number 1041078-202003-HRSB-070-01CC) and retrospectively registered (21/11/2023) in the Clinical Research Information Service ( https://cris.nih.go.kr ) with trial registration number KCT0008965. All the participants provided written informed consent and were informed of the right to withdraw from participation at any time during the research until publication. Data confidentiality was ensured, and the results were provided to the participants at their request.

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Ko, E., Choi, YJ. Efficacy of a virtual nursing simulation-based education to provide psychological support for patients affected by infectious disease disasters: a randomized controlled trial. BMC Nurs 23 , 230 (2024). https://doi.org/10.1186/s12912-024-01901-4

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Title : Active carbons as nanoporous materials for solving of environmental problems

However, up to now, the main carriers of catalytic additives have been mineral sorbents: silica gels, alumogels. This is obviously due to the fact that they consist of pure homogeneous components SiO2 and Al2O3, respectively. It is generally known that impurities, especially the ash elements, are catalytic poisons that reduce the effectiveness of the catalyst. Therefore, carbon sorbents with 5-15% by weight of ash elements in their composition are not used in the above mentioned technologies. However, in such an important field as a gas-mask technique, carbon sorbents (active carbons) are carriers of catalytic additives, providing effective protection of a person against any types of potent poisonous substances (PPS). In ESPE “JSC "Neorganika" there has been developed the technology of unique ashless spherical carbon carrier-catalysts by the method of liquid forming of furfural copolymers with subsequent gas-vapor activation, brand PAC. Active carbons PAC have 100% qualitative characteristics of the three main properties of carbon sorbents: strength - 100%, the proportion of sorbing pores in the pore space – 100%, purity - 100% (ash content is close to zero). A particularly outstanding feature of active PAC carbons is their uniquely high mechanical compressive strength of 740 ± 40 MPa, which is 3-7 times larger than that of  such materials as granite, quartzite, electric coal, and is comparable to the value for cast iron - 400-1000 MPa. This allows the PAC to operate under severe conditions in moving and fluidized beds.  Obviously, it is time to actively develop catalysts based on PAC sorbents for oil refining, petrochemicals, gas processing and various technologies of organic synthesis.

Victor M. Mukhin was born in 1946 in the town of Orsk, Russia. In 1970 he graduated the Technological Institute in Leningrad. Victor M. Mukhin was directed to work to the scientific-industrial organization "Neorganika" (Elektrostal, Moscow region) where he is working during 47 years, at present as the head of the laboratory of carbon sorbents.     Victor M. Mukhin defended a Ph. D. thesis and a doctoral thesis at the Mendeleev University of Chemical Technology of Russia (in 1979 and 1997 accordingly). Professor of Mendeleev University of Chemical Technology of Russia. Scientific interests: production, investigation and application of active carbons, technological and ecological carbon-adsorptive processes, environmental protection, production of ecologically clean food.   

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Developing ash-free high-strength spherical carbon catalyst supports

• Domestic Catalysts
• Published: 28 June 2013
• Volume 5 , pages 156–163, ( 2013 )

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• V. V. Gur’yanov 1 ,
• V. M. Mukhin 1 &
• A. A. Kurilkin 1  

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The possibility of using furfurol for the production of ash-free high-strength active carbons with spheroidal particles as adsorbents and catalyst supports is substantiated. A single-stage process that incorporates the resinification of furfurol, the molding of a spherical product, and its hardening while allowing the process cycle time and the cost of equipment to be reduced is developed. Derivatographic, X-ray diffraction, mercury porometric, and adsorption studies of the carbonization of the molded spherical product are performed to characterize the development of the primary and porous structures of carbon residues. Ash-free active carbons with spheroidal particles, a full volume of sorbing micro- and mesopores (up to 1.50 cm 3 /g), and a uniquely high mechanical strength (its abrasion rate is three orders of magnitude lower than that of industrial active carbons) are obtained via the vapor-gas activation of a carbonized product. The obtained active carbons are superior to all known foreign and domestic analogues and are promising for the production of catalysts that operate under severe regimes, i.e., in moving and fluidized beds.

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Original Russian Text © V.V. Gur’yanov, V.M. Mukhin, A.A. Kurilkin, 2013, published in Kataliz v Promyshlennosti.

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Gur’yanov, V.V., Mukhin, V.M. & Kurilkin, A.A. Developing ash-free high-strength spherical carbon catalyst supports. Catal. Ind. 5 , 156–163 (2013). https://doi.org/10.1134/S2070050413020062

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Received : 08 December 2011

Published : 28 June 2013

Issue Date : April 2013

DOI : https://doi.org/10.1134/S2070050413020062

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Peer support interventions for parents and carers of children with complex needs

Parents and family carers of children with complex needs experience a high level of pressure to meet children's needs while maintaining family functioning and, as a consequence, often experience reduced well‐being and elevated psychological distress. Peer support interventions are intended to improve parent and carer well‐being by enhancing the social support available to them. Support may be delivered via peer mentoring or through support groups (peer or facilitator led).

Peer support interventions are widely available, but the potential benefits and risks of such interventions are not well established.

To assess the effects of peer support interventions (compared to usual care or alternate interventions) on psychological and psychosocial outcomes, including adverse outcomes, for parents and other family carers of children with complex needs in any setting.

Search methods

We searched the following resources.

• Cochrane Central Register of Controlled Trials (CENTRAL; latest issue: April 2014), in the Cochrane Library.

• MEDLINE (OvidSP) (1966 to 19 March 2014).

• Embase (OvidSP) (1974 to 18 March 2014).

• Journals@OVID (22 April 2014).

• PsycINFO (OvidSP) (1887 to 19 March 2014).

• BiblioMap (EPPI‐Centre, Health Promotion Research database) (22 April 2014).

• ProQuest Dissertations and Theses (26 May 2014).

• metaRegister of Controlled Trials (13 May 2014).

We conducted a search update of the following databases.

• MEDLINE (OvidSP) (2013 to 20 February 2018) (search overlapped to 2013).

• PsycINFO (ProQuest) (2013 to 20 February 2018).

• Embase (Elsevier) (2013 to 21 February 2018).

We handsearched the reference lists of included studies and four key journals ( European Child and Adolescent Psychiatry : 31 March 2015; Journal of Autism and Developmental Disorders : 30 March 2015; Diabetes Educator : 7 April 2015; Journal of Intellectual Disability Research : 13 April 2015). We contacted key investigators and consulted key advocacy groups for advice on identifying unpublished data.

We ran updated searches on 14 August 2019 and on 25 May 2021. Studies identified in these searches as eligible for full‐text review are listed as "Studies awaiting classification" and will be assessed in a future update.

Selection criteria

Randomised and cluster randomised controlled trials (RCTs and cluster RCTs) and quasi‐RCTs were eligible for inclusion. Controlled before‐and‐after and interrupted time series studies were eligible for inclusion if they met criteria set by the Cochrane Effective Practice and Organisation of Care Review Group. The comparator could be usual care or an alternative intervention. The population eligible for inclusion consisted of parents and other family carers of children with any complex needs. We applied no restriction on setting.

Data collection and analysis

Inclusion decisions were made independently by two  authors, with differences resolved by a third  author. Extraction to data extraction templates was conducted independently by two authors and cross‐checked. Risk of bias assessments were made independently by two authors and were reported according to Cochrane guidelines. All measures of treatment effect were continuous and were analysed in Review Manager version 5.3. GRADE assessments were undertaken independently by two review authors, with differences resolved by discussion.

Main results

We included 22 studies (21 RCTs, 1 quasi‐RCT) of 2404 participants. Sixteen studies compared peer support to usual care; three studies compared peer support to an alternative intervention and to usual care but only data from the usual care arm contributed to results; and three studies compared peer support to an alternative intervention only.

We judged risk of bias as moderate to high across all studies, particularly for selection, performance, and detection bias.

Included studies contributed data to seven effect estimates compared to usual care: psychological distress (standardised mean difference (SMD) ‐0.10, 95% confidence interval (CI) ‐0.32 to 0.11; 8 studies, 864 participants), confidence and self‐efficacy (SMD 0.04, 95% CI ‐0.14 to 0.21; 8 studies, 542 participants), perception of coping (SMD ‐0.08, 95% CI ‐0.38 to 0.21; 3 studies, 293 participants), quality of life and life satisfaction (SMD 0.03, 95% CI ‐0.32 to 0.38; 2 studies, 143 participants), family functioning (SMD 0.15, 95% CI ‐0.09 to 0.38; 4 studies, 272 participants), perceived social support (SMD 0.31, 95% CI ‐0.15 to 0.77; 4 studies, 191 participants), and confidence and skill in navigating medical services (SMD 0.05, 95% CI ‐0.17 to 0.28; 4 studies, 304 participants). In comparisons to alternative interventions, one pooled effect estimate was possible: psychological distress (SMD 0.2, 95% CI ‐0.38 to 0.79; 2 studies, 95 participants). No studies reported on adverse outcomes.

All narratively synthesised data for psychological distress (compared to usual care ‐ 2 studies), family functioning (compared to usual care ‐ 1 study; compared to an alternative intervention ‐ 1 study), perceived social support (compared to usual care ‐ 2 studies), and self‐efficacy (compared to alternative interventions ‐ 1 study) were equivocal. Comparisons with usual care showed no difference between intervention and control groups (perceived social support), some effect over time for both groups but more effect for intervention (distress), or mixed effects for intervention (family function). Comparisons with alternative interventions showed no difference between the intervention of interest and the alternative. This may indicate similar effects to the intervention of interest or lack of effect of both, and we are  uncertain which option is likely.

We found no clear evidence of effects of peer support interventions on any parent outcome, for any comparator; however, the certainty of evidence for each outcome was low to very low, and true effects may differ substantially from those reported here.

We found no evidence of adverse events such as mood contagion,  negative group interactions, or worsened psychological health.

Qualitative data suggest that parents and carers value peer support interventions and appreciate emotional support.

Authors' conclusions

Parents and carers of children with complex needs perceive peer support interventions as valuable, but this review found no evidence of either benefit or harm. Currently, there is uncertainty about the effects of peer support interventions for parents and carers of children with complex needs. However, given the overall low to very low certainty of available evidence, our estimates showing no effects of interventions may very well change with further research of higher quality.

Plain language summary

Review question

This review assessed whether peer support interventions improve outcomes for parents and others caring for children with a wide range of complex needs (such as chronic or severe acute illness, disability, or delayed development).

Parents and other family carers who care for children with complex needs may experience increased distress and reduced well‐being. Peer support interventions are intended to assist people caring for children to find social support from others who understand their situation. Peer support can be provided in groups, which sometimes are led by a facilitator, or can occur when people are matched with individual parents who have experience caring for a child with a similar condition.

Study characteristics

We included research up to 21 February 2018. Randomised controlled trials (RCTs), cluster RCTs, quasi‐RCTs, controlled before‐and‐after studies, and interrupted time series studies were all eligible for inclusion. Studies were included if they measured distress, confidence, feelings of coping, quality of life, how families functioned, feelings of support, or confidence in dealing with services among parents or any other family carers. Children being cared for could have any condition (for example, chronic or severe acute illness, disability, any kind of delayed or atypical development).

We found 22 studies of 2404 participants who were caring for children with a wide range of conditions. All studies were RCTs or quasi‐RCTs and compared peer support to usual care (comparison 1) or to another intervention (comparison 2). Peer support was delivered in hospitals and in the community. Although we found studies that evaluated effects of peer support on all outcomes in comparison 1, and several outcomes in comparison 2, we did not see any benefit from peer support compared to usual care or compared to another intervention. We found no studies that reported on adverse effects (such as stress from hearing others' stories or conflicts with group members). Feedback from parents and carers suggests that they value emotional support, validation of their experiences, and access to knowledge that they find in peer support groups. More information is needed about training and supervision of peer support leaders, and about whether many participants withdraw from groups (and if so, why).

The overall quality of evidence for each outcome was low to very low, and because of this, our certainty about these findings is low. This means that further research is likely to change these findings while making clearer the possible benefits or harms of peer support interventions.

At the moment, we are uncertain about whether peer support helps or harms parents and carers of children with complex needs.

Summary of findings

Many studies have found that parents and other family carers of children with complex needs, such as disability, developmental delay or learning difficulties, or other chronic or complex conditions such as autism spectrum disorder, experience exceptional pressure to meet the emotional and physical needs of the affected child or children, while at the same time maintaining family functioning ( Cheshire 2010 ;  Lee 2007 ;  McGuire 2004 ;  Resch 2010 ;  Strunk 2010 ). (In this review, we use 'carers' to refer to family carers only,  not paid professional carers). 

Parents (and carers in a parenting role) of children with complex needs often show poor results on markers of psychosocial well‐being such as quality of life and life satisfaction, and they show elevated levels of psychological distress such as depression, anxiety, or stress ( Cheshire 2010 ;  McGuire 2004 ;  Resch 2010 ).

The daily caregiving activities and responsibilities of parents of children with complex needs can be more time‐consuming than parenting a typically developing child, and can be physically and emotionally demanding ( McGuire 2004 ;  Resch 2010 ). These demands on the parent’s/carer’s time and energy can reduce the resources available for other meaningful and health‐protective activities such as employment, social activities, exercise, and hobbies. Family and social relationships can be disrupted and parents (or carers) left feeling overwhelmed, isolated, and lacking support ( McGuire 2004 ;  Resch 2010 ;  Strunk 2010 ).

Description of the condition

Families of children with complex needs report experiencing more stress than families of children who do not have complex needs, regardless of the child's particular condition ( Tak 2002 ; Van Riper 1992 ).

Demands of caregiving

Parents caring for children with complex needs experience anxiety about their child's diagnosis and prognosis, and may experience short‐term emotional distress, loneliness, uncertainty, and symptoms of depression ( Barlow 2006 ). Physical caregiving activities, supporting provision of therapy, and advocating for the child can prove extremely time‐consuming ( McGuire 2004 ). Parents may have difficulty gaining access to the services and resources they need ( Banach 2010 ).

Behavioural problems may cause stress for families regardless of the underlying condition. For example, in families where children have developmental delay, behavioural problems resulting from the delay were reported to be a greater contributor to increased parenting stress than the developmental delay itself ( Baker 2002 ). Parents may lack confidence in dealing with behavioural issues and may experience difficulty finding or accessing support services ( Twoy 2007 ).

Changes to family life

Reviews have found that chronic diseases in children interfere with daily family life, increasing parents' burden of care ( Barlow 2006 ). Balancing the healthcare needs of the affected child against other family needs, with reduced time for other necessary or enjoyable activities, is a source of family stress ( Banach 2010 ). In addition to stresses directly related to the child's condition, families of children with complex needs must adapt to new roles, adjust their lives to cope with the needs of the child, and accommodate increased strain on family resources. As well as managing the needs of the affected child and of any other children in the family, parents must cope with their own chronic stress and periodic family crises ( Bourke‐Taylor 2010 ; Dellve 2006 ).

Social stigma and isolation

Families that include a child with a chronic illness are at increased risk of isolation from formal and informal social support mechanisms ( Tak 2002 ). Challenging behaviours and those due to emotional or cognitive conditions, which are seen by others as 'odd', may make social outings difficult ‐ a problem exacerbated by lack of understanding of the underlying condition among members of the community ( Twoy 2007 ). This means that parents may choose isolation over the frustrations of taking their child out in public ( Tak 2002 ). Physical frailty of the child, which may limits the child's ability to travel beyond the home, may similarly restrict parents' ability to maintain social networks.

Parents often feel the need to assist family and friends in handling their feelings about their child's condition, and to educate them and others such as workmates and acquaintances about the condition ( Dellve 2006 ). Parents may feel stigmatised, either through the direct actions and comments of others, or indirectly through their own attributions and anxieties about what others might be thinking. As a result, they may restrict social activities or may socialise only with other families whose children have a similar diagnosis. In some cases, families may be excluded by others from social gatherings ( Gray 2002 ).

Positive outcomes for families

Although families of children with complex needs face a range of challenges, in recent decades the benefits and rewards of raising a child with challenging behaviours or complex needs have been increasingly recognised. Families report feeling an enhanced sense of meaning or purpose and personal growth, and their positive perceptions of their role may be as high or higher than that of families of typically developing children ( Blacher 2007 ; Hastings 2002 ). Social‐cultural constraints (such as service inefficiencies, perceived stigma, financial hardship, and low levels of support) have been found to contribute more to the negative impact of raising a child with complex needs than demands strictly associated with raising the child ( Green 2007 ; Mas 2016 ; McConnell 2014 ).

Description of the intervention

The intervention of interest is peer support in the form of networks or groups for parents and carers of children with complex needs. Peer support may encompass peer‐led or facilitator‐led interventions, where the focus is on fostering peer‐to‐peer interactions and increasing social support. Peer support can be provided one‐to‐one or in a group, and may be given face‐to‐face or may be technology‐assisted (e.g. conducted by telephone or internet).

The aims of peer support interventions vary. However, for the purposes of this systematic review, we were interested in interventions intended to enhance the social support (perceived and/or actual) available to participants and to improve the well‐being of parents and carers across a range of psychological and psychosocial indicators.

How the intervention might work

Peer support interventions are assumed to work by increasing the amount of social support available to parents and carers of children with complex needs and providing that support in a form that is most useful and acceptable to families. It has been suggested that families of children with complex needs who display similar levels of function to families of children without such needs do so because they had current or prior affiliation with a support group (together with time and resources to adjust to the diagnosis) ( Van Riper 1992 ). The perceived availability of support may play as great a role in determining stress levels in affected families as the actual support provided ( Duarte 2005 ).

Peer support interventions are intended to supplement parents' existing social networks and to reduce feelings of isolation and stigma by introducing individuals who otherwise might not meet to others who can appreciate and understand their experiences ( Shilling 2013 ). Participants' circumstances should be similar but need not be identical ( Dale 2008 ). For example, parents who are in the early stages of adjusting to a diagnosis may benefit from the expertise of parents who have been coping longer with a diagnosis; parents who have been living with their child's condition for some time benefit from feeling that their experiences have meaning for others and from taking on an expert role.

Given the complexity of the emotional experience of raising a child with complex needs, peer support may work not by decreasing the negative impact or difficulties that parents experience, but rather by enhancing or encouraging the development of a new sense of meaning and purpose, opportunities for growth, and positive appraisals of their child and their caring role ( Green 2007 ; Hastings 2002 ; Mas 2016 ; McConnell 2014 ). Although social support is the primary goal, peer support interventions may additionally increase instrumental (tangible) support for parents by increasing access to local social and health services, and may improve parents' knowledge about and confidence in managing their child's illness and other family issues.

Benefits of social support

Social support, defined as a combination of emotional concern, instrumental (tangible) aid, information, and appraisal, may mediate the stress experienced by families of children with serious physical, emotional, or behavioural challenges by contributing to coping resources ( Coppola 2013 ; Dunkel‐Schetter 1987 ; Lazarus 1987 ). Social support may be of benefit for those who provide it as well as for those who receive it ( Ignaki 2017 ). Such support has been found to reduce stress, for example, among parents of children with severe learning difficulties ( Quine 1991 ). Social integration and support protect against the potentially harmful effects of stressful family circumstances and have beneficial effects on well‐being, whether or not a person is currently under stress ( Armstrong 2005 ).

Emotional support and hope

Reports from practitioners working with parents of children with complex needs reveal that these parents want emotional support (e.g. someone to listen and understand), want to know of others in a similar situation who are doing well, and want to hear stories from others that give them hope for the future and make them feel less alone ( Kirk 2015 ; Santelli 1996 ).

Reduction of isolation and stigma

Stigma, whether experienced or feared, can lead parents to avoid contact with others. Combined with the time‐consuming care tasks undertaken by these parents, this may mean increased risk of isolation for the families of children with complex needs. Social support can be an effective buffer against isolation ( Kerr 2000 ).

Incidental learning

As well as buffering against stress, social support can have a direct effect on parenting stress by increasing exposure to incidental learning opportunities and competence‐promoting social interactions. Parents can benefit from the experience and knowledge of their peers without taking part in overt training and information sessions. A general survey of interactions between socio‐economic status, positive and negative parenting behaviours, and child difficulties recommended interventions to strengthen parents' social relationships with the goals of reducing stress and creating opportunities for parents to learn from and affirm one another ( McConnell 2011 ).

Advocacy and self‐efficacy

Social support has been linked with enhanced advocacy skills and confidence in parents of children with complex needs ( Banach 2010 ).

Instrumental support

Instrumental (tangible) support that parents and carers value includes information about specific disabilities and caring for children with complex needs, as well as ways to find and gain access to services and community resources ( Santelli 1996 ).

Reciprocity

Social support provided by peers is suggested to provide reciprocal benefits: those receiving support gain the advantages described above, and people providing support report enhanced quality of life and validation of their previous experiences ( Santelli 1997 ; Schwartz 1999 ). It has been suggested that social support must be reciprocal (or the possibility of reciprocity must at least exist) to be maximally effective ( Hogan 2002 ). A group of peers of similar status provide a plausible arena for this egalitarian give‐and‐take of mutual support, in contradistinction to the power imbalance that may exist between service provider and service recipient.

Why it is important to do this review

A large number of self‐help and peer support groups and programmes target parents and carers of children with complex needs ( Canary 2008 ;  Davies 2005 ;  Hastings 2004 ;  Law 2001 ). These groups aim to provide “social support, practical information, and a sense of shared purpose or advocacy” ( King 2000 , p. 226). It is widely believed that these groups and programmes improve parental well‐being through social support mechanisms and peer support provided through sharing of experiences, information, and understanding, and provision of adaptive and credible models of coping ( Davies 2005 ;  King 2000 ;  Lee 2007 ;  McGuire 2004 ). However, despite anecdotal reports that these benefits are derived from participation in such groups and programmes ( Ainbinder 1998 ;  Davies 2005 ;  Hartman 1992 ;  Law 2001 ), little research has been undertaken to investigate the outcomes of participation in these groups and programmes for the parent/carer and the family in general.

Social support networks are not always uniformly positive in effect ( Ortega 2002 ). Peer support groups have the potential to damage self‐esteem by reinforcing parents' self‐image as a member of a stigmatised group, and social comparison can lead to negative affect ( Hogan 2002 ); so it is important to find out if, when, and how peer support interventions help, what barriers might exist to people's access to peer support, and if negative effects are known.

Some reviews in this general area already exist. We identified seven Cochrane Reviews relevant to this topic, but all were concerned with peer support for adult participants who were directly experiencing a condition or were supporting another adult with a condition, rather than supporting a child with a condition; some assessed interventions for which peer support was one component.  Doull 2005  and  Doull 2004  are protocols only. They have been withdrawn and will not be proceeding.  Dale 2008  assessed the effectiveness of peer support telephone calls in improving physical, psychological, and behavioural health outcomes among adults;  Lavender 2013  investigated telephone support for women during pregnancy and six weeks postpartum; and  Chamberlain 2017  investigated psychosocial interventions for smoking cessation among pregnant women.  Treanor 2019  assessed psychosocial interventions designed to improve quality of life and other outcomes for caregivers of people living with cancer; some of those interventions included a peer support component.  González‐Fraile 2021  assessed the effectiveness of psychoeducational interventions (including remotely delivered support interventions promoting interactions with peers) in preventing or reducing caregiver burden among family members of people with dementia.

Some interventions examined were similar to those considered in this review, although we are considering a potentially broader range of groups and settings. However, there is only limited overlap with our population ‐ adults, but adults considered in their role as carers of children ‐ and with our conditions and outcomes of interest, which are sequelae to caring for children with complex needs rather than conditions directly affecting adults.

We also identified two recent non‐Cochrane reviews that are relevant to this review.  Niela‐Vilén 2014  conducted a review of internet‐based peer support for parents. This is a highly relevant type of intervention, but the population (any parents, not only parents of children with complex needs) is less relevant.

Shilling 2013  conducted an integrative review of parent‐to‐parent (mentoring) support interventions. Again, this is a relevant intervention type, and unlike the other reviews we identified was of interventions for parents of children with chronic disabling conditions.   However, the current review considers a broader range of intervention types including face‐to‐face and online parent support groups.

• To assess the effects of peer support interventions (compared to usual care or alternative interventions) on a range of psychological and psychosocial outcomes, including adverse outcomes, for parents and other family carers of children with complex needs in any setting
• Given that caring and financial demands on these parents and carers are high, to collect and report data related to barriers to participation, as evaluated in any qualitative research on intervention effectiveness

Criteria for considering studies for this review

Types of studies.

Randomised controlled trials (RCTs) and cluster RCTs, controlled before‐and‐after (CBA) studies, and interrupted times series (ITS) studies were eligible for inclusion in this review. Quasi‐RCTs (trials in which random allocation was attempted, but a method of allocation that was not strictly random, such as alternation, day of the week, or date of birth, was used) were also accepted.

To be included in this review, CBA and ITS studies had to meet the Cochrane Effective Practice and Organisation of Care Review Group (EPOC) criteria ( Ryan 2011 ). These specify, for CBA designs, at least two intervention sites and two control sites, comparable timing of measurements for control and intervention groups, and comparable key characteristics for control and intervention groups; and for ITS designs, a clearly specified intervention time point and at least three data collection points before and after that intervention.

We included studies with a broad range of control groups, including no‐treatment, wait list, and usual care controls. When a study compared peer support with an alternative intervention (with or without a usual care control), the study was included but could not be included in meta‐analyses with studies in which peer support was compared with a no‐treatment control.

We incorporated evidence from quantitative studies that also had a qualitative component ( Noyes 2011b ). We did not conduct a separate search for qualitative studies and therefore could neither include qualitative‐only studies nor conduct an exhaustive review of mixed‐methods studies.

Types of participants

Participants were parents and other family carers of children with complex needs (as reported in the included study) for whom complex needs include chronic or severe acute illness, disability, or delayed/atypical development or an enduring condition in the physical, psychological, developmental, or intellectual domain. 'Parents' could be encompassed in studies where participants were biological, adoptive, or foster parents; mothers only; fathers only; or both parents. 'Family carers' could include any adults acting in a parenting role, including grandparents. Studies in which participants were professional (paid) carers were excluded from this review.

'Children with complex needs' was defined in the broadest possible terms to include children with any acute or chronic medical or psychological condition with a relatively long‐lasting course or sequelae.

Children were defined as individuals aged 18 years or younger.

Types of interventions

The target intervention was provision of peer support through networks or groups. Peer support was defined in this review as the existence of a community of common interest where people gather (in person or virtually by telephone or computer) to share experiences, ask questions, provide emotional support, and gain self‐help ( Eysenbach 2004 ;  Iscoe 1985 ). This is consonant with definitions used in published Cochrane Reviews (e.g.  Dale 2008 ;  Kew 2016 , with the additional stipulation that specific knowledge possessed by the peer group is concrete, pragmatic, and derived from personal experience rather than through formal training; and that the group consists of individuals who are perceived to be equal ( Dale 2008 ). Peer support interventions can range from purely emergent, informal, and member‐driven approaches to those that are mandated, professionally driven, and formal ( Doull 2005 ).

Peer support encompasses a continuum of interventions of various degrees of formality, all of which emphasise the role of personal experience in the provision of peer support. Interventions that utilise a formal or professional facilitator were included, provided the facilitator's role was to manage group interpersonal processes rather than solely to provide counselling or psychoeducation.

We included one‐to‐one mentor (also known as peer‐to‐peer) and group parent/carer support interventions and both face‐to‐face interventions and those that were technology‐assisted (i.e. conducted over the telephone or internet). This range of intervention types were classified into two categories: (1) support groups for parents and/or carers, with or without a facilitator, that were conducted online or face‐to‐face; and (2) mentor arrangements, in which a 'novice' parent or carer was matched with a more experienced parent or carer.

We included the following comparisons in this review.

• Any peer support intervention delivered to parents or carers of children with complex needs versus control (no‐treatment, wait list, or usual care).
• Any peer support intervention versus another psychosocial intervention.

We excluded studies if we judged that effects of the peer intervention could not be separated from those of other intervention components, or if peer support was a 'side effect' of participation in some other intervention. Thus, we excluded studies in which the primary focus was something other than developing and supporting peer networks (e.g. where professionals deliver an educative component or formal therapy) and in which improved peer networks were an incidental outcome.

If the peer support intervention was used as an active control for a trial evaluating a more intensive intervention (e.g. a non‐directive peer support group versus a psychoeducation or therapy group), we included the study; however, such studies could not be included in meta‐analyses unless there was also a no‐treatment control condition.

We included studies in which the client or the focus of the intervention is the child only if direct outcomes for parents and carers were measured. For example, interventions for which the child is the primary client (such as play groups and early intervention programmes) and in which parent peer support is an incidental assumed outcome were excluded from the review, unless this support and other parental outcomes were directly measured.

Types of outcome measures

Primary outcomes.

The primary outcome of interest was the psychosocial well‐being of parents and carers, as measured by a range of psychological, psychosocial, and skills acquisition outcomes for participants.

As social support (the target of the intervention) and psychosocial well‐being (the primary intervention outcome) are somewhat nebulous concepts, we operationalised the primary outcome using constructs developed by the Cochrane Consumers and Communication Review Group ( CHCP 2012 ).

We used the following parent outcome categories.

• Psychological distress.
• Confidence and self‐efficacy.
• Perception of coping.
• Quality of life and life satisfaction.
• Family functioning.
• Perceived social support.
• Confidence and skill in navigating medical services.

When a study used both sub‐scales and full scales related to the same outcome (e.g. a full psychiatric distress scale and anxiety and depression sub‐scales from other measures), we followed advice from Cochrane Australia and used the full, and most general, scale in analyses. In one case in which a study used both depression and anxiety sub‐scales but no more general scale, we chose the sub‐scale that led to a more even distribution of depression versus anxiety sub‐scales across all studies.

• Mood contagion.
• Increased feelings of stigma from identifying with the group.
• Negative group interactions.
• Any decrease in psychological health on the measures listed above.
• As the measures for adverse outcomes fit the same broad categories as those for beneficial outcomes, we adopted the strategy outlined in the Cochrane Handbook for Systematic Reviews of Interventions of assessing beneficial and adverse effects together by the same method, with common eligibility criteria for included studies ( Higgins 2011a ).

The Cochrane Handbook for Systematic Reviews of Interventions suggests grouping outcomes into short‐term, medium‐term, and long‐term, and taking no more than one of each from each study ( Higgins 2011a ). We have preferred longer‐ over shorter‐term outcomes when conducting meta‐analyses.

Secondary outcomes

• Satisfaction with the intervention (when data were available)
• Incidental learning/improved knowledge (when data were available)

Process factors

Process factors that may influence outcomes include the following.

• Facilitators of and barriers to uptake of peer support interventions.
• Participant and provider satisfaction or dissatisfaction with peer support interventions.

Search methods for identification of studies

Electronic searches.

We searched the following databases and resources.

• Cochrane Central Register of Controlled Trials (CENTRAL; latest issue: April 2014), in the Cochrane Library.
• MEDLINE (OvidSP) (1966 to 19 March 2014).
• Embase (OvidSP) (1974 to 18 March 2014).
• Journals@OVID (22 April 2014).
• PsycINFO (OvidSP) (1887 to 19 March 2014).
• BiblioMap (EPPI‐Centre, Health Promotion Research database) (22 April 2014).
• ProQuest Dissertations and Theses (26 May 2014).
• metaRegister of Controlled Trials (13 May 2014).
• MEDLINE (OvidSP) (2013 to 20 February 2018) (search overlapped to 2013 to ensure subsequent additions to 2013‐2014 were captured).
• PsycINFO (ProQuest) (2013 to 20 February 2018).
• Embase (Elsevier) (2013 to 21 February 2018).

Our search strategy was developed with the assistance of John Kis‐Rigo, Information Specialist at the Cochrane Consumers and Communication Review Group, and is presented in Appendices 1 through 6.

A further search update was conducted on 14 August 2019, and again on 25 May 2021, by Anne Parkhill of the Cochrane Consumers and Communication Review Group, using the existing search strategy.

• The Cochrane Library (2015‐).
• Embase Classic + Embase (2018‐).
• MEDLINE (2018‐).
• PsycINFO (2018‐).

We placed no restrictions on publication date, publication status, or language. We sought unpublished studies, and we translated abstracts of potentially relevant studies to determine suitability for inclusion.

Searching other resources

• ClinicalTrials.gov (13 May 2014).
• World Health Organization Clinical Trials Registry (13 May 2014).
• SCOPUS (13 May 2014).
• Evidence in Health and Social Care (15 May 2014).
• New York Academy of Medicine (8 May 2014).
• OpenGrey (15 May 2014).

We conducted handsearches of the reference lists of included studies and relevant journals to identify other potentially eligible studies.

• European Child and Adolescent Psychiatry (31 March 2015).
• Journal of Autism and Developmental Disorders (30 March 2015).
• Diabetes Educator (7 April 2015).
• Journal of Intellectual Disability Research (13 April 2015).

We consulted advocacy and support groups via our existing professional connections with disability support and early childhood agencies to request information on any studies they were aware of: Down Syndrome Victoria, the Cerebral Palsy League, Tresillian Family Care Centres, and Women's and Children's Health Network. We contacted key investigators identified through other searches for advice on identifying other unpublished data and studies.

Selection of studies

Bibliographic details of all search results were consolidated and duplicate records removed using EndNote. These were exported to Excel and were rated for potential inclusion independently by two review authors (GS/AP and GS/VL) based on title and abstract review. Differences were resolved by a third review author (VL or AP). Decisions about inclusion and exclusion were recorded in Excel.

We retrieved full texts for all studies assessed as possibly relevant on the basis of title and abstract review. The same two review authors (GS/AP) assessed studies for inclusion using Criteria for considering studies for this review , with the third review author (VL) also assessing studies on which the first two review authors disagreed. If decisions still were not clear, differences were resolved by discussion amongst all three review authors. Any studies examined in full text but excluded are listed in the Characteristics of excluded studies table along with reasons for exclusion. When several papers were related to the same trial, the trial ‐ not the papers related to it ‐ was counted. The unit of reporting is the trial ‐ not the number of papers.

Data extraction and management

For included studies, two review authors (GS/AP) independently extracted data, using the data extraction template provided by the Cochrane Consumers and Communication Review Group for quantitative data related to intervention effectiveness (see Appendix 1 ) ( Ryan 2011 ). Any qualitative data associated with included studies were recorded on a template adapted from the qualitative data extraction template used by Noyes and Popay (2007, cited in Noyes 2011a ), with modifications to enable extraction of data related to the process outcomes described above ( Types of outcome measures ) (see Appendix 2 ).

When details were not included in the published study or were unclear, we attempted to contact study authors for further information (see Appendix 3 for details of contacts attempted).

Data extracted by one review author were cross‐checked and confirmed by another; any discrepancies were resolved by discussion. All data were pasted from the checked data extraction sheets directly into RevMan software ( Review Manager 2014 ).

Assessment of risk of bias in included studies

We assessed and reported the risk of bias of included studies using the guidelines listed in the Cochrane Handbook for Systematic Reviews of Interventions ( Higgins 2011b ), in keeping with advice provided by the Cochrane Consumers and Communication Review Group ( Ryan 2011 ). These guidelines assess the following domains: random sequence generation; allocation sequence concealment; blinding (participants, personnel); blinding (outcome assessment); completeness of outcome data (attrition), selective outcome reporting; and other sources of bias (e.g. pre‐existing significant differences in characteristics likely to affect parent outcomes; aspects of treatment as usual that may have been a confound; issues with agency recruitment). We judged each item as being at high, low, or unclear risk of bias, as set out in the data extraction template adapted by the Cochrane Consumers and Communication Review Group ( Ryan 2011 , adapted from  Higgins 2011a ).

RCTs were deemed to be at highest risk of bias if they were scored as being at high risk of bias in the sequence generation, allocation concealment, or incomplete outcome data domain. RCTs were assessed as at unclear risk of bias if they were rated as unclear in at least one of these three domains. Low risk of bias studies were defined as those receiving a low risk of bias rating in all three of the sequence generation, allocation concealment, and incomplete outcome data domains of the tool.

Quasi‐RCTs were rated as being at high risk of bias on the random sequence generation item of the 'Risk of bias' tool.

No CBA or ITS studies were identified as eligible for inclusion.

Two review authors (GS/AP) independently assessed the risk of bias of included studies, with any disagreements resolved by discussion and consensus. When necessary, we attempted to contact study authors for clarification of methods (see  Appendix 3 ).

All studies meeting inclusion criteria were included in our data synthesis, regardless of the outcome of the 'Risk of bias' assessment. If future updates of this review include non‐randomised studies (such as CBA or ITS designs), we will assess risk of bias with regard to selection bias, performance bias, detection bias, attrition bias, and reporting bias, as suggested in Section 13.5.2.1 of the Cochrane Handbook for Systematic Reviews of Interventions ( Higgins 2011b ).

Assessment of qualitative data

The qualitative data extraction template given as an example in  Noyes 2011a  was adapted for use in this review, with quality assessed for the domains of credibility, transferability, dependability, and confirmability.

Measures of treatment effect

All outcomes from studies included in meta‐analyses were continuous. We used final values scores in preference to change‐from‐baseline scores.

There was variability in the types of measures used to assess outcomes. For example, psychological distress was measured on the Psychiatric Symptom Index (total and sub‐scales) the Center for Epidemiologic Studies Depression Scale, the Parenting Stress Index, and the Profile of Mood States (short form). We calculated the standardised mean difference (SMD) and the 95% confidence interval (CI) for each outcome using mean, standard deviation, and numbers of people assessed in control and intervention groups via the inverse variance method in Review Manager 5 software (Section 9.4.3.2; Higgins 2011a ; Review Manager 2014 ).

When standard deviations were not available, we calculated them from reported confidence intervals using the RevMan calculator.

Some outcomes were assessed on scales with differing directions (e.g. on the Caregiver Strain Questionnaire, a reduction in score indicates an improved outcome; on the Parent Coping Efficacy Scale, an increased score represents a better outcome). In these instances, the method outlined in Section 9.2.3.2 of Higgins 2011a was used to ensure that all scales had the same direction.

Qualitative data

When qualitative outcomes were reported in the studies included in this review, we performed a qualitative evidence synthesis to supplement our main quantitative data synthesis.

We extracted qualitative data on process factors affecting implementation, such as facilitators and barriers to participation in peer support interventions.

Unit of analysis issues

We considered the level at which randomisation occurred (e.g. individual, cluster, cross‐over) in included studies. We identified no cluster‐randomised trials for inclusion; therefore we did not need to perform corrections for inappropriate units of analysis.

Dealing with missing data

When data were missing, we attempted to contact study authors as described above. When missing data could not be obtained, we imputed these, following consultation with staff at Cochrane Australia, with appropriate adjustments to the standard error to account for added uncertainty in the results. Meta‐analyses did not include a significant quantity of imputed data: for  Ireys 1996  we imputed standard deviations (SDs) from two other studies using the same scale; and for  Preyde 2003 ,  Flores 2009 , and  Swallow 2014 , we calculated SDs using confidence intervals (CIs). Generally, when study data were insufficient for inclusion, the data were so incomplete as to make it impossible to include the study in the meta‐analysis. When a study was omitted from an outcome meta‐analysis due to lack of data, we have noted this in the narrative synthesis for that outcome.

Assessment of heterogeneity

When we considered studies similar enough, based on consideration of populations and intervention settings, to allow pooling of data using meta‐analysis, we assessed the degree of heterogeneity by visually inspecting forest plots and by examining the Chi² test for heterogeneity. We quantified heterogeneity by using the I² statistic. We considered an I² value of 50% or more to represent substantial levels of heterogeneity, but we also interpreted this value in light of the size and direction of effects and the strength of evidence for heterogeneity, based on the P value from the Chi² test ( Higgins 2011a ).

Assessment of reporting biases

We intended to assess the existence of reporting bias by testing for asymmetry of the funnel plot of intervention effect estimates against the standard error of intervention effect estimates. However, this was not appropriate, as there were no outcomes for which at least 10 studies were included in the meta‐analysis ( Higgins 2011a ; Sterne 2011 ).

Data synthesis

Although we noted some heterogeneity in participants, settings, and interventions, this was expected, and we considered that they were sufficiently similar to allow for meta‐analyses when data were available. For the one outcome (psychological distress) for which there were enough included studies to allow meta‐analysis by intervention type, we checked this, but it did not lead to different assessments of effectiveness by intervention type. Outcomes did differ across studies, and we present meta‐analyses and narrative syntheses separately by broad outcomes. As expected, our included studies were clinically heterogeneous, and we used a random‐effects model to calculate SMDs. We had intended to convert any outcome SMDs back to differences on a single, well‐understood scale, but given the lack of any intervention effects, this proved unnecessary.

We included RCT (including quasi‐RCT) studies in our meta‐analyses. No CBA or ITS studies were eligible for inclusion. As we noted substantial risk of bias for nearly all outcomes, we did not stratify meta‐analyses into low versus high or unclear risk of bias.

Results for studies included in the review but not suitable for meta‐analysis were presented in the narrative synthesis for the appropriate outcome. We used the summary of risk of bias of an outcome across studies to judge the robustness of this evidence ( Cash‐Gibson 2012 ). We used tables of results to form a narrative assessment of the evidence, clustering studies by intervention type and setting. For each study, we reported the same elements of information in the same order (Section 11.7.2; Higgins 2011a ).

We conducted statistical analyses by using the latest version of RevMan software ( Review Manager 2014 ).

Synthesis of qualitative data

A limited quantity of qualitative data were available for review; we followed advice from the Cochrane Consumers and Communication Review Group ‐ Ryan 2016 ‐ and the Economic and Social Research Council (ESRC) Methods Programme ‐ Popay 2006 ‐ in synthesising these data.

Subgroup analysis and investigation of heterogeneity

As discussed in the Background , subgroups of the population may differ in their capacity to benefit from the intervention, and intervention mode and setting may influence outcomes for different subgroups. We had intended to investigate the effects of variables such as existing social connectedness of participants, as well as delivery mode, setting, duration, and size of effects of interventions on outcomes. However, data were insufficient for subgroup analyses to be appropriate. Heterogeneity of data was taken into account when the certainty of evidence for each outcome was judged.

Sensitivity analysis

It was possible to use only SMDs for continuous outcomes due to the wide range of outcome measures used, and we found no dichotomous outcome measures for which it was necessary to make any decisions regarding types of ratios to be used. Therefore it was not appropriate to conduct sensitivity analyses for these variables. When we needed to impute data, we checked the effects of differing assumptions on our analyses and found that none were discernible.

Summary of findings and assessment of the certainty of the evidence

'Summary of findings' tables were based on the methods described in  Schünemann 2011 . We assessed the quality of evidence using the GRADE system ‐ Schünemann 2011 ‐ and GRADEpro software (www.guidelinedevelopment.org). Two review authors independently assessed the certainty of evidence for each outcome; when GRADE scores differed for an outcome, we discussed how we had applied the relevant criterion and come to a consensus score.

Consumer participation

The review authors have strong links with early childhood and disability advocacy agencies in Australia. We sent our contacts in these agencies drafts of the protocol and review and sought their comments, especially on recommendations regarding consumer‐important outcomes reported in the 'Summary of findings'. We used our connections with local consumer agencies to seek input from consumers overseas. Both the protocol and the review received input from a consumer as part of standard Cochrane Consumers and Communication Review Group editorial processes.

Description of studies

Results of the search.

We identified 95,732 records from electronic database searches and 5084 records through other sources (see flow chart of study selection in  Figure 1 ). After removing duplicates, we screened 55,961 records by title and abstract. We excluded 55,773 records at this stage. We obtained 182 records in full text, excluding 160 records. Reasons for exclusion of key excluded studies are detailed in the  Characteristics of excluded studies  table. A summary of reasons (chiefly methodological) for excluding other studies is provided in  Table 3 . Six studies are awaiting classification. These were identified through recent updates to the searches, or they are papers for which we have not been able to obtain full text copies (details are in Studies awaiting classification ). We approached authors of 9 subsequently excluded and 10 subsequently included studies for further information (see  Appendix 3 ). One author of an included study could not be contacted. Authors of 13 studies provided further details, and authors of 6 studies did not respond.

Study flow diagram.

Included studies

Twenty‐two studies including 2404 participants met selection criteria for inclusion in this review. Of these, 16 compared peer support interventions with a usual care control ( Aiello 2015 ;  Boogerd 2017 ;  Boylan 2013 ;  Flores 2009 ;  Ireys 1996 ;  Ireys 2001 ;  Kutash 2011 ;  Kutash 2013 ;  McCallion 2004 ;  Preyde 2003 ;  Ruffolo 2005 ;  Silver 1997 ;  Singer 1999 ;  Sullivan‐Bolyai 2004 ;  Sullivan‐Bolyai 2010 ;  Swallow 2014 ). Three other studies compared peer support with an alternative intervention, as well as a usual care control ( Roberts 2011 ;  Scharer 2009 ;  Wysocki 2008 ). In meta‐analyses of these studies, only peer support and usual care control findings were included. Three studies compared peer support with an alternative intervention only ( Ferrin 2014 ;  Rhodes 2008 ;  Singer 1994 ). These studies could not be included in meta‐analyses but are part of our narrative synthesis. Additionally,  Aiello 2015  did not include data in a format suitable for inclusion in a meta‐analysis.

Detailed information from all included studies is provided in the  Characteristics of included studies  tables. Key information is summarised below, and interventions evaluated by included studies are summarised in  Table 4 .

Most included studies (21 of 22) were randomised controlled trials (RCTs) ( Aiello 2015 ;  Boogerd 2017 ;  Boylan 2013 ;  Ferrin 2014 ;  Flores 2009 ;  Ireys 1996 ;  Ireys 2001 ;  Kutash 2011 ;  Kutash 2013 ;  McCallion 2004 ;  Rhodes 2008 ;  Roberts 2011 ;  Ruffolo 2005 ;  Scharer 2009 ;  Silver 1997 ;  Singer 1994 ;  Singer 1999 ;  Sullivan‐Bolyai 2004 ;  Sullivan‐Bolyai 2010 ;  Swallow 2014 ;  Wysocki 2008 ).

One study was a quasi‐RCT with allocation to treatment condition by alternation ( Preyde 2003 ). We did not identify any controlled before‐and‐after or interrupted time series studies that met inclusion criteria.

Sample size

Studies ranged in size from 15 participants in  Singer 1994  to 343 participants in  Silver 1997 . The median number of participants was 71.

We were able to include in at least one meta‐analysis 1927 participants from 14 studies ( Boogerd 2017 ;  Flores 2009 ;  Ireys 1996 ;  Ireys 2001 ;  Kutash 2011 ;  Kutash 2013 ;  McCallion 2004 ;  Preyde 2003 ;  Roberts 2011 ;  Ruffolo 2005 ;  Scharer 2009 ;  Silver 1997 ;  Singer 1999 ;  Swallow 2014 ); the largest meta‐analysis (8 studies) included 864 participants (psychological distress).

Studies were based in the United States (14) ( Flores 2009 ;  Ireys 1996 ;  Ireys 2001 ;  Kutash 2011 ;  Kutash 2013 ;  McCallion 2004 ;  Ruffolo 2005 ;  Scharer 2009 ;  Silver 1997 ;  Singer 1994 ;  Singer 1999 ;  Sullivan‐Bolyai 2004 ;  Sullivan‐Bolyai 2010 ;  Wysocki 2008 ); Australia (2) ( Rhodes 2008 ;  Roberts 2011 ); and Brazil ( Aiello 2015 ), Canada ( Preyde 2003 ), Ireland ( Boylan 2013 ), Spain ( Ferrin 2014 ), The Netherlands ( Boogerd 2017 ), and the UK ( Swallow 2014 ).

Peer support interventions were conducted in the following settings.

• Community (14) ( Ferrin 2014 ;  Flores 2009 ;  Ireys 1996 ;  Ireys 2001 ;  Kutash 2011 ;  Kutash 2013 ;  McCallion 2004 ;  Roberts 2011 ;  Ruffolo 2005 ;  Silver 1997 ;  Singer 1999 ;  Sullivan‐Bolyai 2004 ;  Sullivan‐Bolyai 2010 ;  Wysocki 2008 ).
• Online (4) ( Aiello 2015 ;  Boogerd 2017 ;  Scharer 2009 ;  Swallow 2014 ).
• Hospital (3) ( Boylan 2013 ;  Preyde 2003 ;  Singer 1994 ).
• Outpatient therapy (1) ( Rhodes 2008 ).

Participants

Participants were parents and carers of children with a wide range of chronic physical, developmental, and psychiatric conditions.

• Parents of children with diabetes (4 studies) ( Boogerd 2017 ;  Sullivan‐Bolyai 2004 ;  Sullivan‐Bolyai 2010 ;  Wysocki 2008 ).
• Parents of children with emotional disturbance (3 studies) ( Kutash 2011 ;  Kutash 2013 ;  Ruffolo 2005 ).
• Parents of children with chronic illness (2 studies) ( Ireys 2001 ;  Silver 1997 ).
• Parents of children with a disability (1 study) ( Singer 1999 ).
• Parents of children with acquired brain injury (1 study) ( Singer 1994 ).
• Parents of children with anorexia nervosa (1 study) ( Rhodes 2008 ).
• Parents of children with attention deficit hyperactivity disorder (1 study) ( Ferrin 2014 ).
• Parents of children with autism spectrum disorder (1 study) ( Roberts 2011 ).
• Parents of children with chronic kidney disease (1 study) ( Swallow 2014 ).
• Parents of children with juvenile rheumatoid arthritis (1 study) ( Ireys 1996 ).
• Parents of young people with self‐harm or suicidal behaviour (1 study) ( Boylan 2013 ).
• Parents of children with serious mental illness (1 study) ( Scharer 2009 ).
• Minority parents of children with asthma (1 study) ( Flores 2009 ).
• Mothers of very preterm infants (1 study) ( Preyde 2003 ).
• Mothers of children with severe and profound sensorineural hearing loss (1 study) ( Aiello 2015 ).
• Grandparents with primary care of children with intellectual disability, other developmental disability, or learning problems, or with attention deficit and hyperactivity disorders (1 study) ( McCallion 2004 ).

Interventions

Peer support interventions identified in this review fell into two broad categories.

• Support groups for parents and/or carers, with or without a facilitator, which were conducted online or face‐to‐face (11 studies) ( Aiello 2015 ;  Boogerd 2017 ;  Boylan 2013 ;  Ferrin 2014 ;  McCallion 2004 ;  Roberts 2011 ;  Ruffolo 2005 ;  Scharer 2009 ;  Singer 1994 ;  Swallow 2014 ;  Wysocki 2008 ).
• Mentor arrangements, whereby a 'novice' parent or carer was matched with a more experienced parent or carer, sometimes referred to as peer‐to‐peer support (11 studies) ( Flores 2009 ;  Ireys 1996 ;  Ireys 2001 ;  Kutash 2011 ;  Kutash 2013 ;  Preyde 2003 ;  Rhodes 2008 ;  Silver 1997 ;  Singer 1999 ;  Sullivan‐Bolyai 2004 ;  Sullivan‐Bolyai 2010 ).

Parent/carer support groups (11 studies)

The typical purpose of support groups was to encourage parents and carers to share information, concerns, and achievements and to form a mutually supportive network ( Roberts 2011 ). Support group interventions had a wide range of stated aims, such as to:

• provide social support and information ( Aiello 2015 ;  Boogerd 2017 ;  Boylan 2013 );
• reduce parental stress, depression, and anxiety ( Aiello 2015 ;  Boogerd 2017 ;  Boylan 2013 ;  McCallion 2004 ;  Roberts 2011 ;  Singer 1994 );
• improve communication, problem‐solving skills, and coping skills ( Boylan 2013 ;  Ruffolo 2005 ); or
• increase parent knowledge ( Aiello 2015   Boogerd 2017 ), self‐efficacy, sense of empowerment and caregiving mastery, and perception of competence in managing the child's condition ( McCallion 2004 ;  Roberts 2011 ;  Swallow 2014 ).

Not all trial authors cited a theoretical basis for their support group intervention. Those that were cited included social support as a way of reducing role strain and life disruptions (e.g.  McCallion 2004 ). References in these cases refer to studies citing the models, not to the original models.

Group structures ranged from formal peer support programmes, as in  Boylan 2013  and  Ruffolo 2005 , to self‐help groups with content determined collaboratively by participants and facilitator, as in  McCallion 2004 , to completely non‐directive groups, as in  Ferrin 2014 . The format for groups identified in this review was either face‐to‐face (as in  Boylan 2013 ,  Ferrin 2014 ,  McCallion 2004 ,  Roberts 2011 ,  Ruffolo 2005 ,  Singer 1994 , and  Wysocki 2008 ) or online (as in  Aiello 2015 ,  Boogerd 2017 ,  Scharer 2009 , and  Swallow 2014 ).

Whether online or face‐to‐face, support groups might include large and small group discussions of relevant information (e.g.  Boylan 2013 ;  McCallion 2004 ;  Singer 1994 ;  Wysocki 2008 ); problem‐solving activity‐based discussions ( Ruffolo 2005 ); and encouragement of emotional expression ( Singer 1994 ). Other components of support groups included homework, skill‐building exercises, free time for socialising ( Ruffolo 2005 ;  Wysocki 2008 ), testimonials from peers, and advice on managing stress ( Swallow 2014 ). To increase parents' access to groups, some interventions also provided in‐home or onsite respite care and transport assistance ( McCallion 2004 ).

Support groups were generally (although not always) led by a facilitator with input from participants ( Boylan 2013 ;  Ferrin 2014 ;  McCallion 2004 ), for example, choosing topics for discussion ( McCallion 2004 ;  Singer 1994 ;  Wysocki 2008 ). If facilitators were involved, these groups were usually non‐directive, with facilitators in some interventions explicitly prohibited from offering feedback, psychoeducation, or advice ( Boogerd 2017 ;  Ferrin 2014 ). When facilitators were more directive, they tended to intervene only to manage group processes, so as to ensure smooth running and full participation of members ( Scharer 2009 ). This aspect of facilitation seemed particularly important in online settings, where peer discussion took place in an online chat room with the facilitator present to monitor.

Some groups included both a professional facilitator and a parent leader ( Ruffolo 2005 ). Only one intervention appeared to have no facilitator or group leaders: an online intervention in which participants had open access to the psychosocial support site ( Swallow 2014 ).

Support group interventions may have been developed following parent focus groups ( Boogerd 2017 ;  Boylan 2013 ), or during a pilot phase ( Boogerd 2017 ). Grandparent recommendations were used to identify material to be covered in grandparent support group sessions ( McCallion 2004 ), and consumers were involved in the development of one online system ( Swallow 2014 ). In many cases, it was not clear whether there was consumer involvement in the design or conduct of the groups.

In most cases, the support group was the main intervention under investigation; in some cases, peer support was an alternate intervention control for more intensive interventions such as a structured psychoeducation programme ( Ferrin 2014 ), an individual home‐based intervention ( Roberts 2011 ), a stress management group ( Singer 1994 ), or a family therapy group ( Wysocki 2008 ). In some instances, peer support was a component of a broader online application ( Aiello 2015 ;  Boogerd 2017 ;  Swallow 2014 ).

Parent/carer mentors (11 studies)

The common purpose of parent mentor (or peer‐to‐peer) interventions was to enhance the mental health of participants ( Ireys 2001 ), while improving parent quality of life ( Flores 2009 ). These interventions included named programmes such as Parent‐to‐Parent ( Singer 1999 ;  Silver 1997 ), Family‐to‐Family Network ( Ireys 2001 ), Parent Connect ( Kutash 2011 ;  Kutash 2013 ), HOMEWARD ( Sullivan‐Bolyai 2004 ), Social Support to Empower Parents ( Sullivan‐Bolyai 2010 ), and unnamed mentoring arrangements ( Flores 2009 ;  Ireys 1996 ;  Preyde 2003 ). The stated aims of interventions were to provide informational, affirmational, and emotional support ( Ireys 1996 ;  Sullivan‐Bolyai 2004 ;  Sullivan‐Bolyai 2010 ) with the goals of:

• reducing parent anxiety, depression, and stress ( Ireys 1996 ;  Ireys 2001 );
• improving carer quality of life ( Flores 2009 );
• reducing caregiver strain ( Kutash 2011 ;  Kutash 2013 );
• improving parents' confidence in managing the child's condition ( Rhodes 2008 ;  Sullivan‐Bolyai 2004 ); and
• successfully adapting to the challenges of raising a child with a chronic condition ( Singer 1999 ;  Sullivan‐Bolyai 2004 ).

Theoretical bases cited for parent mentor interventions included consideration of the impact of social support on parent behaviour and attitudes ( Ireys 2001 ), social support as an extension of coping ( Singer 1999 ), as a determinant of parental mental health ( Silver 1997 ), and as an element of planned behaviour ( Kutash 2013 ).

Parent mentor interventions typically linked participants with a veteran parent who had experience raising a child with a comparable chronic condition ( Ireys 2001 ;  Preyde 2003 ;  Rhodes 2008 ). Peer support might be provided via home visits ( Ireys 2001 ), meetings in community venues ( Ireys 2001 ), or therapeutic settings ( Rhodes 2008 ). Interventions often included telephone contact in addition to face‐to‐face contact ( Flores 2009 ;  Ireys 1996 ;  Ireys 2001 ;  Preyde 2003 ;  Silver 1997 ;  Sullivan‐Bolyai 2010 ), or instead of face‐to‐face contact ( Kutash 2011 ;  Singer 1999 ).

Some parent mentor interventions also had a support group component, although this was generally informal and incidental to the mentoring relationship. For example, some parent mentors also convened group meetings with all their assigned families in community venues to encourage social networking and support ( Flores 2009 ). In a school‐based programme ( Kutash 2011 ;  Kutash 2013 ), teachers received extra training and parents received written information (this was provided in control groups as well). One intervention was an adjunct to a well‐established family‐based treatment in which participants had access to a parent mentor and to the mentor's therapist throughout their own family therapy ( Rhodes 2008 ). In at least one case, parent mentors had mandated topics to cover with participants ( Silver 1997 ).

Parent mentors may have received extensive paid or volunteer training in interpersonal skills (as in  Ireys 2001   Preyde 2003  and  Sullivan‐Bolyai 2010 ) and in providing affirmational support that recognised the participant's existing competencies ( Ireys 1996 ).

Some but not extensive consumer input was reported for parent mentor/peer‐to‐peer interventions. Parents had input into intervention design in one study ( Singer 1999 ), and participants determined the amount of contact they received from mentors in two other interventions ( Silver 1997 ;  Sullivan‐Bolyai 2004 ).

Both intervention types varied widely on salient details such as number and length of group and mentoring sessions, structure of sessions (if any), and training and qualifications of facilitators and mentors. In most studies, interventions tended to be poorly specified; it would not be possible to implement most interventions faithfully from the information published. This was the case whether the peer support intervention was the focus of the study or was used as an alternative treatment control. Generally, measures for ensuring programme fidelity were not reported, although several trial authors reported that fidelity was checked (e.g.  Flores 2009 ;  Kutash 2011 ;  Kutash 2013 ;  Roberts 2011 ).

Because there was such wide variation within intervention categories, we have followed our original protocol and have not conducted separate syntheses for each intervention type, although we considered doing so. With future studies and better‐specified interventions, conducting separate meta‐analyses and narrative syntheses for each intervention type would be an approach worth considering.

Many studies collected data on multiple child and family outcomes, as is shown in the  Characteristics of included studies  table. In most cases, the peer support intervention was compared with a treatment as usual control only. In other cases, there was a usual care control and another comparator; in a small number of cases, there was no usual care control and peer support was compared only with another intervention; data from these studies could not be included in meta‐analyses. These are noted in the  Characteristics of included studies  table.

Outcomes included in meta‐analyses and the specific scales used to measure those outcomes are listed below. Nearly all measures were self‐reported; however, this is to be expected given the field of research and the nature of the outcomes. Many of the scales used, particularly for psychological distress and for confidence and self‐efficacy, are well established with reasonable psychometric profiles. Although we considered the measures used when assessing risk of bias (especially performance bias), use of self‐report measures such as those listed here should be considered standard for this research.

• Global psychological distress: Psychiatric Symptom Index ( Ireys 1996 ;  Silver 1997 ); Profile of Mood States ( Scharer 2009 ).
• Stress: Parenting Stress Index ( Aiello 2015 ;  Boogerd 2017 ;  Ferrin 2014 ;  Roberts 2011 ); Parent Stress Scale ( Boylan 2013 ).
• Anxiety: Psychiatric Symptom Index (anxiety sub‐scale) ( Ireys 2001 ); State Anxiety Inventory ( Preyde 2003 ).
• Depression: Center for Epidemiological Studies Depression Scale ( McCallion 2004 ).
• Self‐efficacy: Parent Asthma Management Self‐Efficacy Scale ( Flores 2009 ); Parent Efficacy Scale ( Rhodes 2008 ); Parental Confidence Questionnaire ( Sullivan‐Bolyai 2004 ;  Sullivan‐Bolyai 2010 ).
• Locus of control: Parenting Locus of Control ( Ruffolo 2005 ).
• Feelings of mastery: Caregiving Mastery Scale ( McCallion 2004 ); Family Management Measure (condition management sub‐scale) ( Swallow 2014 ); confidence in managing the child's condition ( Roberts 2011 ).
• Positive attitude: Kansas Inventory of Parental Perceptions ( Singer 1999 ).
• Caregiver strain: Caregiver Strain Questionnaire ( Kutash 2011 ;  Kutash 2013 ).
• Perception of coping: Parent Coping Efficacy Scale ( Singer 1999 ).
• Pediatric Asthma Caregiver's QoL Scale ( Flores 2009 ); Beach QoL Scale ( Roberts 2011 ).
• Family Empowerment Scale, Family sub‐scale ( Kutash 2011 ;  McCallion 2004 ).
• Family Empowerment Scale, Services sub‐scale ( McCallion 2004 ).
• Impact on Family Scale ( Sullivan‐Bolyai 2004 ;  Sullivan‐Bolyai 2010 ).
• Video‐recorded family discussion coded using the Interaction Behavior Coded ( Wysocki 2008 ).
• PedsQL™ Family Impact Module ( Ferrin 2014 ).
• Ireys Social Support Inventory ( Ireys 1996 ;  Sullivan‐Bolyai 2010 ); Multidimensional Scale of Perceived Social Support ( Boylan 2013 ;  Preyde 2003 ); Arizona Social Support Scale (emotional support sub‐scale) ( Ruffolo 2005 ); MOS Social Support Scale ( Scharer 2009 ).
• Service efficacy: Vanderbilt Mental Health Service Efficacy Questionnaire ( Kutash 2011 ;  Kutash 2013 ).
• Empowerment: Family Empowerment Scale (Services sub‐scale) ( McCallion 2004 ;  Swallow 2014 ).

Outcomes for which no data were available

No studies specifically reported adverse events or outcomes. Given that all other outcomes were measured on continuous scales, it is always possible that participants might have scored worse on such scales, relative to control participants, following an intervention. We considered results carefully with this possibility in mind.

Most data came from published studies, with the exception of  Scharer 2009 , for which data were provided by trial authors. Several trial authors provided additional data or clarification; this is noted in the  Characteristics of included studies  table.

Consumer involvement

Consumer involvement was not widely reported by study authors. Some interventions were developed following parent focus groups or a pilot phase ( Boogerd 2017 ;  Boylan 2013 ), or on the basis of carer recommendations ( McCallion 2004 ;  Singer 1999 ;  Swallow 2014 ). Two studies reported that participants could determine their own preferred level of contact with mentors ( Silver 1997 ;  Sullivan‐Bolyai 2004 ), and participants were responsible for determining the materials discussed in several support group interventions ( Ferrin 2014 ;  McCallion 2004 ).

Excluded studies

We excluded 160 studies at the full‐text review stage. Of these, we excluded 151 for methodological reasons, as specified in Table 3 . Reasons for excluding the 16 potentially most relevant studies are listed in the Characteristics of excluded studies table.

Risk of bias in included studies

We present risk of bias information in Characteristics of included studies , Figure 2 (summary of all studies by risk of bias (ROB) items), and Figure 3 (individual studies by ROB items).

Risk of bias graph: review authors' judgements about each risk of bias item presented as percentages across all included studies.

Risk of bias summary: review authors' judgements about each risk of bias item for each included study.

We judged risk of bias to be moderate to high across studies as a whole. This was particularly so for selection bias (random sequence generation and allocation concealment), performance bias, and detection bias, with around 50% to 90% of studies rated as being at unclear or high risk of bias in these domains. Performance bias was particularly high, reflecting the difficulty of blinding participants and personnel to the provision of peer support delivered in comparison to usual care. A high proportion of studies provided insufficient information about their design and conduct, and so we judged them as being unclear in these domains.

Risk of bias was generally lower for other domains of the tool, with a majority (sometime a bare majority) of studies rated as being at low risk of attrition bias, reporting bias, and other biases.

Random sequence generation

Twelve studies described using a truly random sequence generation method and were rated as being at low risk of bias ( Boogerd 2017 ; Ferrin 2014 ; Flores 2009 ; Ireys 1996 ; Ireys 2001 ; Kutash 2013 ; Rhodes 2008 ; Roberts 2011 ; Ruffolo 2005 ; Singer 1999 ; Sullivan‐Bolyai 2010 ; Swallow 2014 ).

Nine studies stated that they used a random sequence but did not describe their method of sequence generation. They were rated as being at unclear risk of bias for this item ( Aiello 2015 ; Boylan 2013 ; Kutash 2011 ; McCallion 2004 ; Scharer 2009 ; Silver 1997 ; Singer 1994 ; Sullivan‐Bolyai 2004 ; Wysocki 2008 ).

One study reported using random assignment but actually used quasi‐random methods. This study was rated as being at high risk of bias ( Preyde 2003 ).

Allocation concealment

Allocation concealment was less well reported than was random sequence generation. Only three studies described adequate allocation concealment and were rated at low risk of bias for this item ( Ireys 2001 ; Rhodes 2008 ; Swallow 2014 ).

By contrast, risk of bias for allocation concealment was unclear in 16 studies due to insufficient information ( Aiello 2015 ; Boylan 2013 ; Ferrin 2014 ; Flores 2009 ; Ireys 1996 ; Kutash 2011 ; Kutash 2013 ; McCallion 2004 ; Ruffolo 2005 ; Scharer 2009 ; Silver 1997 ; Singer 1994 ; Singer 1999 ; Sullivan‐Bolyai 2004 ; Sullivan‐Bolyai 2010 ; Wysocki 2008 ).

In three studies, allocation did not appear to have been concealed; these studies were rated at high risk of bias ( Boogerd 2017 ; Preyde 2003 ; Roberts 2011 ).

Due to the nature of interventions in this field, blinding of participants and of staff delivering interventions can be difficult. When a peer support intervention was compared with usual care, it seems unlikely that participants could have been truly blind to their allocation to intervention, but this depends on the nature of the usual care provided and what participants were led to expect on recruitment to the study.

If in doubt, we have coded this domain as 'unclear risk' rather than 'high risk' because it is possible ‐ depending on how the research was described to prospective participants ‐ that participants were not aware whether they had been allocated to intervention or control. We rated as 'high risk' if it seemed clear, in our judgement, that participants could not have been blind to allocation due to the nature of the intervention. Research personnel could have been blinded to allocation during data collection, particularly if they did not also deliver the intervention, and in some cases, baseline measures at least were taken prior to allocation to intervention or control.

Outcome measures were a mixture of self‐report and structured interview, which represents a potential form of bias. However, the self‐report surveys generally used established, validated measures, and these may not represent substantially higher risk of bias than usual in this domain than for properly blinded participants.

We rated risk of bias as low if participants were blinded, even if personnel were not, especially if checks were in place to ensure fidelity of programme delivery and outcome measurement.

Performance bias

Only one study was rated as being at low risk of performance bias ( Ferrin 2014 ). Risk of performance bias was unclear in eight studies ( Boylan 2013 ; Flores 2009 ; Kutash 2011 ; Kutash 2013 ; McCallion 2004 ; Roberts 2011 ; Scharer 2009 ; Singer 1994 ).

The remaining 13 studies were at high risk of performance bias ( Aiello 2015 ; Boogerd 2017 ; Ireys 1996 ; Ireys 2001 ; Preyde 2003 ; Rhodes 2008 ; Ruffolo 2005 ; Silver 1997 ; Singer 1999 ; Sullivan‐Bolyai 2004 ; Sullivan‐Bolyai 2010 ; Swallow 2014 ; Wysocki 2008 ).

Detection bias

Five studies were at low risk of detection bias ( Flores 2009 ; Roberts 2011 ; Silver 1997 ; Swallow 2014 ; Wysocki 2008 ), and risk was unclear for 12 studies ( Boylan 2013 ; Ferrin 2014 ; Ireys 1996 ; Kutash 2011 ; Kutash 2013 ; McCallion 2004 ; Rhodes 2008 ; Ruffolo 2005 ; Scharer 2009 ; Singer 1994 ; Sullivan‐Bolyai 2004 ; Sullivan‐Bolyai 2010 ).

Five studies were assessed as being at high risk of detection bias ( Aiello 2015 ; Boogerd 2017 ; Ireys 2001 ; Preyde 2003 ; Singer 1999 ).

Incomplete outcome data

Attrition bias appeared to be at generally lower risk than bias in previous domains. Strategies used by trial authors to address potential attrition bias included full reporting of missing data; checking whether attrition differed between intervention and control; and using intention‐to‐treat analyses and checking against per‐protocol analyses. When there appeared to be high risk of attrition bias, this was due to issues such as discarding final outcome measures due to attrition and using earlier measures (considered here rather than in selective reporting below), reporting unequal attrition rates without reporting potential reasons, or reporting attrition rates that differed by participant characteristics.

Fourteen studies were assessed as being at low risk of bias ( Aiello 2015 ; Boogerd 2017 ; Ferrin 2014 ; Flores 2009 ; Ireys 1996 ; Ireys 2001 ; Kutash 2013 ; McCallion 2004 ; Preyde 2003 ; Silver 1997 ; Singer 1999 ; Sullivan‐Bolyai 2004 ; Swallow 2014 ; Wysocki 2008 ).

Risk of bias was unclear in four studies ( Boylan 2013 ; Roberts 2011 ; Ruffolo 2005 ; Singer 1994 ), and risk was high in four studies ( Kutash 2011 ; Rhodes 2008 ; Scharer 2009 ; Sullivan‐Bolyai 2010 ).

Selective reporting

Seventeen studies were assessed as being at low risk of reporting bias ( Aiello 2015 ; Boogerd 2017 ; Ferrin 2014 ; Flores 2009 ; Kutash 2011 ; Kutash 2013 ; McCallion 2004 ; Preyde 2003 ; Roberts 2011 ; Ruffolo 2005 ; Scharer 2009 ; Silver 1997 ; Singer 1994 ; Sullivan‐Bolyai 2004 ; Sullivan‐Bolyai 2010 ; Swallow 2014 ; Wysocki 2008 ).

Risk of reporting bias was rated as unclear in two studies ( Boylan 2013 ; Singer 1999 ), and risk was high in three studies ( Ireys 1996 ; Ireys 2001 ; Rhodes 2008 ).

Other potential sources of bias

Six studies were assessed as being at high risk of bias from other potential sources of bias ( Ireys 1996 ; McCallion 2004 ; Rhodes 2008 ; Roberts 2011 ; Ruffolo 2005 ; Singer 1994 ).

• Differences between intervention and control participants in functional status of the child, severity of child diagnosis, and rates of relevant child comorbidity ( Ireys 1996 ; Roberts 2011 ; Ruffolo 2005 ; Singer 1994 ).
• Differences between intervention and control participant demographics that could plausibly affect outcomes (family composition and rates of obsessive‐compulsive disorder and depression) ( Rhodes 2008 ).
• Potential baseline differences in major outcomes, not corrected for in analysis ( Roberts 2011 ).
• Agencies delivering interventions and responsible for recruitment of participants, when it was not clear whether participants could self‐select the intervention ( McCallion 2004 ).
• Unknown dose of treatment as usual when this was something that might act as a confounder, such as intensive case management ( Ruffolo 2005 ).

Bias from other potential sources was unclear in three studies ( Boylan 2013 ; Kutash 2011 ; Scharer 2009 ).

Effects of interventions

See: Table 1 ; Table 2

Summary of findings 1

1 Of 8 studies, 1 was quasi‐RCT with attendant risk of confounding. High proportion of high/unknown RoB in random sequence generation, allocation concealment, and blinding

2 Minimal overlap of CIs; tests of heterogeneity suggest departure from null hypothesis. Effects were in different directions (positive and negative)

3 Majority of studies had high or unclear ROB in allocation concealment and blinding of participants and personnel

4 Majority of ROB criteria are high or unknown risk, including nearly all sequence generation, allocation concealment, and blinding criteria

5 Total sample was underpowered to detect small effect size according to GRADE guideline of 200 participants each in intervention and control

6 Of 4 studies, 1 was quasi‐RCT. Majority of ROB criteria are high or unknown risk, including nearly all sequence generation, allocation concealment, and blinding criteria

7 High proportion of ROB criteria are unknown risk

Summary of findings 2

1 High proportion of high/unknown risk of bias across the two RCTs

2 Very small sample sizes, especially Singer 1994.

&&In preparing this section of the review, we have relied upon guidance from the Cochrane Consumers and Communication Group ( Ryan 2016 ) in addition to the Cochrane Handbook ( Higgins 2011a ).

See:  Table 1  for seven outcomes in comparison 1 (peer support interventions versus usual care).

Comparison 1. Peer support interventions versus usual care

1.1 psychological distress.

Ten studies were identified which assessed psychological distress following peer support interventions compared with usual care. Eight studies assessing psychological distress in 864 participants were able to be included in a meta‐analysis ( Boogerd 2017   Ireys 1996   Ireys 2001   Preyde 2003   Silver 1997   McCallion 2004   Roberts 2011   Scharer 2009 ). The pooled interventions arms showed no evidence of effect on psychological distress (SMD ‐0.10 (95% CI ‐0.32 to 0.11), see  Analysis 1.1 ).

Comparison 1: Peer support vs usual care, Outcome 1: Psychological distress

Two RCTs could not be included in the meta‐analysis due to missing data. In  Aiello 2015  (22 participants), no significant difference in participant distress scores between intervention and control participants was observed at either baseline or follow‐up. In  Boylan 2013  (147 participants), both the intervention and the usual care control participants reported significantly improved well‐being (reduced distress) at follow‐up, but with significantly greater improvement for intervention participants. More detail on these results is provided in  Table 5 .

The certainty of the evidence relating to this outcome (see  Table 1 , for this and subsequent outcomes in this comparison) was very low, meaning we can have very little confidence in the effect estimates. The eight studies contributing to the pooled estimate of effect included interventions in a range of settings, delivery of interventions varied widely, there was a wide range of follow‐up times, and there is some degree of heterogeneity in estimates (I 2 51%). Additionally, most studies had high or unclear risk of bias for allocation concealment and blinding (participants and personnel, and outcome assessors).

Based on this evidence, we are uncertain about the effect of peer support interventions on parents' psychological distress. The true effect is likely to differ substantially from the estimate of effect reported here.

1.2 Confidence and self‐efficacy

We identified eight studies which compared confidence and self‐efficacy outcomes for peer support interventions compared with usual care in 542 participants ( Flores 2009   McCallion 2004   Roberts 2011   Ruffolo 2005   Singer 1999   Sullivan‐Bolyai 2004   Sullivan‐Bolyai 2010   Swallow 2014 ). The pooled intervention arms showed no evidence of effect on parents' confidence and self‐efficacy (SMD 0.04 (95% CI ‐0.14 to 0.21), see  Analysis 1.2 ). Note that one scale measuring this outcome (used in the two Sullivan‐Bolyai studies) was scored negatively, so a decrease represents an improvement on that scale.

Comparison 1: Peer support vs usual care, Outcome 2: Confidence and self‐efficacy

The certainty of the evidence relating to this outcome (see  Table 1 ) was low, meaning we can have only limited confidence in the effect estimates. The majority of the studies had a high or unclear risk of bias for allocation concealment and blinding of participants and personnel.

Based on this evidence, peer support may have little or no effect on parent confidence and self‐efficacy. The true effect may differ substantially from that reported here.

1.3 Perception of coping

We identified three studies assessing perception of coping in 293 participants, and these were able to be included in a meta‐analysis ( Kutash 2011   Kutash 2013   Singer 1999 ). The pooled intervention arms showed no evidence of effect on parents' perception of coping (SMD ‐0.08 (95% CI ‐0.38 to 0.21), see  Analysis 1.3 ). Note that two of the three scales used to assess this outcome are scored in such a way that a lower score represents improved perception (better) of coping.

Comparison 1: Peer support vs usual care, Outcome 3: Perception of coping

The certainty of the evidence relating to this outcome (see Summary of findings table 1) was very low, meaning we can have very little confidence in the effect estimate. Delivery of interventions varied widely, there was a wide range of follow‐up times, and the majority of risk of bias items are at high or unknown risk including all allocation concealment, and blinding criteria. The total sample was underpowered according to GRADE guidelines.

Based on this evidence, we are uncertain about the effect of peer support interventions on parents' perception of coping. The true effect is likely to differ substantially from the estimate of effect reported here.

1.4 Quality of life

We identified two studies which assessed quality of life in 143 participants, following peer support intervention or usual care ( Flores 2009   Roberts 2011 ). Both were eligible for inclusion in a meta‐analysis. The pooled effect estimate showed no evidence of effect of the intervention on parents' quality of life (SMD 0.03 (95% CI ‐0.32 to 0.38),  Analysis 1.4 ).

Comparison 1: Peer support vs usual care, Outcome 4: Quality of life

The certainty of the evidence relating to this outcome (see  Table 1 ) was very low, meaning we can have very little confidence in the effect estimate. Delivery of interventions varied widely, there was a wide range of follow‐up times, and the total sample was underpowered to detect small effect size according to GRADE guidelines ( Schünemann 2013 ). Additionally, several key risk of bias criteria were rated as at high or unknown risk, including allocation concealment in both studies.

Based on this evidence, we are uncertain about the effect of peer support interventions on quality of life in parents and carers. The true effect is likely to differ substantially from the estimate of effect reported here. 

1.5 Family functioning

We identified five studies which compared family functioning following peer support intervention or usual care. Four studies assessing family functioning in 272 participants were able to be included in a meta‐analysis ( Kutash 2011   McCallion 2004   Sullivan‐Bolyai 2004   Sullivan‐Bolyai 2010 ). The pooled effect estimate showed no evidence of effect of the intervention on family functioning (SMD 0.15 (95% CI‐0.09 to 0.38), see  Analysis 1.5 ).

Comparison 1: Peer support vs usual care, Outcome 5: Family functioning

One study could not be included in the meta‐analysis as there was no suitable data reported and the authors could not be contacted ( Wysocki 2008 , 104 participants). This study was very difficult to interpret as analysis of variance tables focused on the authors' preferred intervention (Behavioural Family Systems Therapy) while we were interested in their Educational Support (peer support) condition, an active control using peer support; however both interventions appeared to perform better than a usual care control on some measures of family communication and problem‐solving skills, for mothers but not for fathers, and at the later (18 months) but not earlier (6 to 12 month) time point.

The certainty of the evidence was very low. Only a small proportion of risk of bias criteria were rated as low risk, and almost all studies were at unclear risk due to sequence generation and allocation concealment. There were also differences in intervention delivery and follow‐up times and the total sample was underpowered by GRADE guidelines.

Based on this evidence, we are uncertain about the effect of peer support interventions on family functioning and the true effect is likely to differ substantially from the estimate of effect reported here.

1.6 Perceived social support

We identified six studies assessing perceived social support. Four studies assessing perceived social support in 191 participants following peer support intervention or usual care were able to be included in a meta‐analysis ( Ireys 1996   Preyde 2003   Ruffolo 2005   Scharer 2009 ). The pooled effect estimate showed no evidence of an effect of the intervention on parents' perceived social support (SMD 0.31 (95% CI ‐0.15 to 0.77), see  Analysis 1.6 ).

Comparison 1: Peer support vs usual care, Outcome 6: Perceived social support

Two studies ( Boylan 2013   Sullivan‐Bolyai 2010 ) could not be included in the meta‐analysis. The authors reported no significant change in perceived social support over time for either intervention or usual care group in either study.

The certainty of the evidence was very low. Of the four studies, one was a quasi‐RCT and the majority of risk of bias criteria were rated as high or unknown risk, including all allocation concealment and blinding criteria. Intervention delivery and timing of follow‐up varied widely. Tests of heterogeneity suggest some heterogeneity of individual results (I 2 60%) and the total sample was underpowered by GRADE guidelines.

Based on this evidence, we are uncertain about the effect of peer support interventions on parents and carers' perceived social support. The true effect is likely to differ substantially from the estimate of effect reported here.

1.7 Confidence and skill in navigating medical services

W identified four studies assessing confidence and skill at navigating medical services in 304 participants, following peer support intervention or usual care ( Kutash 2011   Kutash 2013   McCallion 2004   Swallow 2014 ). All were able to be included in a meta‐analysis. The pooled effect estimate showed no evidence of effect of the intervention on parents' confidence and skill at navigating the medical service system (SMD 0.05 (95% CI ‐0.17 to 0.28), see  Analysis 1.7 ).

Comparison 1: Peer support vs usual care, Outcome 7: Confidence and skill at navigating medical services

The quality of the evidence was very low. Of the four studies, a high proportion of risk of bias criteria were rated as at unknown risk, including the majority of studies for allocation concealment and blinding. The total sample was underpowered by GRADE guidelines.

Based on this evidence, we are uncertain about the effect of peer support parents' confidence and skill at navigating medical services. The true effect may differ substantially from that reported here.

1.8 Adverse events

No authors reported discrete adverse events. A relative worsening of outcomes following intervention (for example an increase in psychological distress) would also have counted as an adverse event in this review; however, given that there was no evidence of effect in either direction for any of the assessed outcomes, peer support interventions do not appear to worsen any outcomes for participants as far as we currently are aware. However, the very low certainty of evidence overall indicates that we are currently uncertain about possible adverse events and should continue to monitor for these, rather than indicating that none are possible with the use of peer support interventions.

Comparison 2. Peer support interventions versus alternative intervention

A small number of studies compared peer support with an alternative intervention only ‐ that is, there was no usual care control (several studies in comparison 1 had all three arms, but we reported only the peer support and usual care arms in this review). In these studies, the authors' assumption was presumably that peer support would be less effective than the comparator intervention, as peer support was being used as a control.

2.1 Psychological distress

Two studies assessed psychological distress in 95 participants ( Ferrin 2014  (comparator was psycho‐education),  Singer 1994  (comparator was stress management group)). The pooled estimates of effect did not differ between peer support and alternative interventions (SMD 0.2 (95% CI ‐0.38 to 0.79), see  Analysis 2.1 ). However, the certainty of evidence was rated as very low, as the pooled estimate was based on a very small sample size, and there was a high proportion of risk of bias criteria rated as being at high or unknown risk of bias, particularly in  Singer 1994 .

Comparison 2: Peer support vs alternative intervention, Outcome 1: Psychological distress

Based on this evidence, we are uncertain about the effect of peer support interventions on parents' psychological distress, compared with alternative interventions. The true effect is likely to differ substantially from the estimate of effect reported here.

2.2 Confidence and self‐efficacy

One study ( Rhodes 2008 , 20 participants) assessed parent confidence and indicated that peer support plus family‐based treatment had no significant effect on parent confidence, relative to family‐based treatment alone. As this is a single study, we are very uncertain about the effect and expect that the true effect may differ substantially from that reported here.

2.3 Family functioning

Ferrin 2014  assessed impact on family life (PedsQL family function module) in 81 participants. The authors found no significant difference in quality of life between peer support group participants and a psycho‐educational group. As this is a single study, we are very uncertain about the effect and expect that the true effect may differ substantially from that reported here. 

Satisfaction with the intervention (Comparison 1, peer support interventions versus usual care)

Only three studies reported on parent satisfaction with the intervention, but data is not comparative and should therefore be viewed only as indicative.  Boogerd 2017  found moderate acceptability of and demand for the intervention in parents, and high acceptability and demand in health care professionals (however, this was not a direct measure of satisfaction, but is inferred from reported rates of uptake and continued use).  Kutash 2011  reported that parents were very satisfied with the intervention (98% (40 of 41) of participants responding to that question). Similarly  Preyde 2003  reported that of 24 participants (out of 32) who responded to a question about helpfulness, 21 (87.5%) indicated that the intervention was helpful or very helpful.

Incidental learning/improved knowledge

No included studies in either comparison addressed this outcome.

Qualitative findings: process factors

Some authors reported on process factors that influenced the implementation of interventions and participants' experience of those interventions:

• Contextual factors influencing the development of peer support: facilitators and barriers to uptake of peer support interventions,
• User and provider experiences of peer support interventions.

We have assessed these factors through qualitative data identified in our search for studies evaluating the effectiveness of intervention. Our intention was to provide insight into how or why interventions work (if they in fact do so), we make no claim to be providing a completely comprehensive or systematic account of qualitative findings. The qualitative component of this review was intended to provide suggestions as to why particular interventions may or may not be effective for particular participants or particular outcomes. We have used guidance from  Popay 2006  in writing this section of the review, which is best considered as a preliminary implementation synthesis given the lack of significant pooled effects and scarcity of qualitative evidence from included studies.

Five studies included a qualitative component, either providing additional context in a single publication, or as an additional publication arising from an included study ( Rearick 2011  (additional data from  Sullivan‐Bolyai 2010 ); Ruffolo 2005   Scharer 2009   Singer 1999   Sullivan‐Bolyai 2004 ). The qualitative data collection and analysis methods used included:

• Open‐ended satisfaction interview ( Sullivan‐Bolyai 2004 ), analysis method not reported
• Interview as part of a concurrent nested mixed‐methods study. Content analysis of interview transcripts conducted independently of quantitative analysis ( Rearick 2011 )
• Random selection of telephone support transcripts, thematic analysis, sampling ended when no new themes or differences in content emerged ( Scharer 2009 ).
• Semi‐structured interview, constant‐comparative procedures to identify emerging themes ( Singer 1999 )
• Qualitative methods not described ( Ruffolo 2005 )

Factors shaping access to and acceptability of peer support

Authors reported a variety of factors shaping‐‐whether positively or negatively‐‐access to and availability of peer support. As there is very little cross‐over in the factors cited, they are listed below by author, as well as being tabulated below.

Rearick 2011  (method extremely well described)

• High level of comfort with mentors and ease of discussion
• Readily available support from other sources decreased need for parent mentor support
• Availability of mentor, ability to contact through a range of methods
• Parent mentor initiating contact
• Parent mentors whose child had the same diagnosis as participant's child

Ruffolo 2005

• Structured format
• Collaboration between parent and professional leaders
• Onsite childcare, transportation support

Scharer 2009

• Group (online) available in the evenings
• Personality of nurse (chat room facilitator) determined acceptability of format

Singer 1999

• Perceived similarity of parent mentor
• Practical and logistical obstacles to contact
• Consistency of parent mentor follow‐up/initiation of contact

Sullivan‐Bolyai 2004

• Perceived availability of mentor
• Perceived interest of mentor
• Calling mentor less intimidating than calling medical team

Factors shaping effectiveness of peer support

Given the lack of significant pooled effects, this should perhaps more properly be phrased as 'factors participants consider important for peer support to work for them'. These were identified by study participants as contributing to or detracting from the support they received.

Rearick 2011 . Contributed: perceived availability of mentor, ability of mentor to provide practical tips about condition management, 'common ground' between mentor and parent (enables mentor to provide validation of emotion, build parent's confidence, assist with adaptation to child diagnosis and the 'new normal'.

Ruffolo 2005 . Nothing reported relevant to facilitators of or barriers to effectiveness.

Scharer 2009 . Contributed: professional (nurse) facilitator, providing empathy and emotional support, information, clarification, encouragement, and affirmation.

Singer 1999 . Contributed: social comparisons between parent and mentor, exchange of practical information. Detracted: differences in circumstances, especially relating to child condition and behaviour.

Sullivan‐Bolyai 2004 . Contributed: parent belief that they could call mentor for advice and support; mentor validated parent experience; mentor encouraged parent to call medical team when necessary.

We assessed the quality of the qualitative data, where possible, against the criteria outlined in  Noyes 2011a . These assessments are summarised in  Table 6   Credibility/internal validity was generally at high or unknown risk of bias, with only one study ( Singer 1999 ) clearly reporting steps taken to reduce response bias. On the other hand, we rated transferability/external validity as being at low risk of bias overall, with good contextual and demographic data provided by most authors. Dependability/reliability was addressed by most authors, with some form of triangulation, inter‐rater agreement check, peer debriefing or audit trail (or a combination of these) used by most authors. Confirmability/objectivity was moderate. Three authors provided context and background for the research and research team or attempted to do so, but in the remaining four this was unclear.

Summary of main results

Twenty‐two studies of 2,404 participants met criteria for inclusion in this review. Studies varied in design (twenty‐one RCTs and one quasi‐RCT), setting (community, hospital, online, and outpatient), participants (mothers only, parents, and grandparents), and child diagnosis (a wide range of disabilities, chronic conditions, and mental illnesses).

Interventions fell into two broad categories: parent/carer support groups and parent mentoring arrangements. Both intervention types varied widely in their reported characteristics such as number and length of sessions, structure of sessions, and the training and qualifications of personnel. Interventions of both types also varied widely in the degree of detail in which these characteristics were described, but the majority were fairly poorly described. Measures for ensuring fidelity of implementation were generally not described.

Risk of bias was moderate to high across the studies as a whole, and was used as a basis for downgrading certainty of the evidence. Most risk of bias concerns related to selection, performance, and detection bias. With regard to performance bias, our rating of moderate to high bias on this domain results primarily from the difficulty of blinding participants and personnel to participation intervention versus control. Of lesser concern was the high proportion of self‐report measures, as this can be considered typical of the field and measures with acceptable psychometric profiles tended to be used. However, there was also some inconsistency in measures used and effect estimates were sometimes in different (opposite) directions. A high proportion of studies provided insufficient information across a range of bias domains and were rated as being at unclear risk of bias. Risk of bias was generally lower for attrition and reporting biases.

Eight outcomes were assessed in this review. Meta‐analyses were conducted for all outcomes other than adverse events, for which no data were reported, but not all studies measuring a given outcome could be included in the relevant meta‐analysis. Effects of peer support interventions were assessed on outcomes compared to usual care control or to an alternative intervention.

Relative to usual care control:

• Psychological distress (8 studies in meta‐analysis, 2 could not be included). We are uncertain about the effect of peer support on distress.
• Confidence and self‐efficacy (6 studies in meta‐analysis, 2 could not be included). We are uncertain about the effect of peer support on confidence and self‐efficacy.
• Perception of coping (3 studies in meta‐analysis). We are uncertain about the effect of peer support on perception of coping.
• Quality of life (2 studies included in meta‐analysis). We are uncertain about the effect of peer support on quality of life.
• Family functioning (4 studies in meta‐analysis, 1 could not be included). We are uncertain about the effect of peer support on family functioning.
• Perceived social support (4 studies in meta‐analysis, 2 could not be included). We are uncertain about the effect of peer support on perceived social support.
• Confidence and skill at navigating medical services (4 studies in meta‐analysis). We are uncertain about the effect of peer support on confidence and skill at navigating medical services.
• Adverse events: could not be assessed as no studies reported on this outcome.

Relative to alternative intervention (psychoeducation or stress management groups):

• Psychological distress (2 studies in meta‐analysis). We are uncertain about the effect of peer support on distress.
• Confidence and self efficacy (1 study). We are uncertain about the effect of peer support on confidence and self‐efficacy.
• Family functioning (1 study). We are uncertain about the effect of peer support on quality of life.

In addition to pooled estimates of effect lacking significance, individual studies varied widely in whether they found significant or non‐significant effects, and whether those effects supported (or tended to support) intervention or control. The variance of included studies (see forest plots) means that there was very little unequivocal evidence supporting the intervention. In fact, only three results favoured peer support, two of which came from Preyde 2003 (psychological distress and perceived social support). This was the only included quasi‐RCT, a design at a much higher risk of bias ‐ and hence less able to increase the certainty of our conclusions ‐ than the RCT studies. In addition, the small sample size of some (although not all) studies meant that they lacked power and were therefore imprecise; that is, would have been unable to detect a statistically (more importantly, a clinically) significant effect even if one existed. Many individual studies reported non‐significant findings where the direction of effect favoured intervention; however some reported non‐significant findings where the direction of effect favoured control. The narratively synthesised data was similarly equivocal in terms of the effects of interventions across comparisons and outcomes.

Some qualitative data were available, mainly relating to what participants valued about peer support interventions.

Factors shaping access to support included interpersonal considerations and group dynamics (such as the perceived similarity and interest of the mentor and collaboration between parent and professional leaders), the perceived availability and approachability of the mentor/facilitator, and pragmatic issues such as the availability of onsite childcare and transportation support.

Potential barriers to accessing peer support included: difficulty of initiating sensitive conversations, the perceived availability of mentor, insufficient resources from facilitator, and differences in other participants' circumstances and experiences.

Factors that participants considered important for peer support to work for them included: the perceived availability and similarity of the mentor, the ability of the mentor to provide practical tips about condition management, 'common ground' between mentor and parent, and socially comparable parents and mentors. Parents valued the exchange of practical information, feeling able to call mentor for advice and support, and having the mentor validate their experience.

The results of this review must be interpreted in the light of the overall very low certainty of evidence, as discussed in more detail below. On the other hand, they should also be interpreted in light of the fact that peer support may perform as well as alternative, generally more intensive, forms of intervention such as psycho‐education and stress management (although the evidence was uncertain and based on a very small number of studies). These alternative interventions may often necessarily involve a health professional for their delivery, unlike peer support interventions (even if a facilitator is involved, such a facilitator need not be a health professional, although they should have expertise in supporting groups). This has implications for the ease and relative cost of implementation of peer support groups. Peer support may potentially be beneficial, but the extent and quality of currently available evidence is insufficient to demonstrate benefit.

Overall completeness and applicability of evidence

All studies identified were conducted in high‐income countries. The majority were conducted in the US (14 studies), and the remainder in Australia (2 studies), and Brazil, Canada, Ireland, South Korea, Spain, The Netherlands, and the UK (1 each). The majority of studies took place in community settings (14 studies), with the remainder spread across online, hospital, and outpatient settings (4, 3, and 1 study respectively). Most studies (18 of 22) have been conducted since 2000, with nine of those conducted between 2010‐2017. Apart from the lack of data from middle‐ and low‐income countries, the studies identified cover a range of relevant participants, interventions, and outcomes, for parents and carers of children with a very broad range of chronic conditions.

For the most part, the gender identity, relationship status, CALD status, LGBTIQ status, and educational level of participants was not reported. 720 participants were noted as being the mother of the child with the condition; all other participants were recorded as being the parent or carer or grandparent of the child. 220 participants were noted as being either African‐American or Latino (Flores 2009). It is therefore difficult to comment on the completeness and applicability of the evidence in relation to such factors.

In most studies, the theoretical model underpinning the intervention was not reported, although many authors provided a general rationale for the benefits of social support. The range of scales for each outcome was quite broad. The outcomes of psychological distress and confidence/self‐efficacy were thosewith the greatest number of measurement scales, and arguably, the most used and best established scales. On the other hand, these outcomes are the most general and least condition‐specific compared to, for example, perception of coping (caregiver strain) and confidence at navigating medical systems. It remains an open question whether an outcome with well‐established but very general measures, such as distress, is more or less appropriate than a condition‐specific but less established outcome measure. The more global the outcome, the more difficult it may be for a relatively low‐intensity intervention to affect it. On the other hand, such outcomes may be more important to consumers and practitioners. For this reason, we chose a mix of outcomes for this review. However, researchers and practitioners should consider whether the scales for measuring their outcomes of interest are relevant to them when considering the applicability of this review.

It will be noted that we pooled several measures of distress for outcomes 1.1 and 2.1. The studies for these comparisons used a mix of anxiety scales, depression scales, indicators of mood change, and general psychiatric symptoms. We were not interested in any specific parent diagnosis because the link between peer support for a child's condition and a formal diagnosis of (for example) depression seems fairly tenuous. It is unlikely that a parent would seek a diagnosis for themselves in this context, and our intervention of interest is not an intervention for any particular diagnosis. Similar to the reasoning behind using the Kessler K6 scale ( Kessler 2010 ), we decided to view elevated symptoms of common mental health concerns as indicating elevated distress without being concerned about whether the participant met formal diagnostic criteria for a condition. Psychiatric distress (due to family stressors) seems like a more appropriate target for peer support interventions, rather than an entrenched and possibly pre‐existing condition.

We contacted several authors for clarification and further details. While many responded, and some provided further data, six studies could not be included in meta‐analyses because no suitable data were available. Findings from all these studies were addressed narratively. No studies reported adverse events.

There was considerable variation in how well particular interventions were described, but in most cases the detail about content and delivery would be insufficient to replicate the intervention. A certain amount of variability is unavoidable in any case, given that both peer support groups and parent‐to‐parent mentoring interventions generally rely on unstructured free discussion. The range of peer support interventions available, the variability of interventions included in this review, and the incomplete details reported all potentially limit the applicability of this review. Practitioners and researchers should think carefully about the content of their intervention when assessing the applicability of this review to their work.

Generally, authors did not provide information about the training and on‐going supervision of those identified as peer support leaders. This is an area in which potentially open to harmful outcomes might arise, if leaders are not appropriately supported, but we cannot comment one way or another. Similarly, it would be useful to track participant withdrawal from peer support programs and investigate reasons for withdrawal, as this could shed further light on the acceptability of peer support interventions, as well as any potentially negative effects encountered or arising from such interventions.

Quality of the evidence

We assessed the degree of certainty of the evidence for each outcome using the GRADE system and presented findings in summary of findings tables for each comparison ( Table 1 ; Table 2 ). Two authors independently assessed the evidence for each outcome; where GRADE scores differed, we discussed how we had each applied the relevant criterion and came to a consensus score. Where individual studies could not be included in meta‐analyses, we commented briefly on them in the narrative results.

The degree of certainty relating to all outcomes was very low or low. We downgraded on all outcomes for high or unknown risk of bias in random sequence generation, allocation concealment, and blinding. Two outcomes (psychological distress and perceived social support) included a quasi‐RCT.

Evidence for all outcomes was affected by the wide variation in intervention delivery and follow‐up times. The total samples for quality of life, family functioning, perceived social support, and confidence and skill at navigating medical services were underpowered to detect small effect sizes, according to GRADE guidelines. This problem also affected the psychological distress outcome in the peer support versus alternative intervention comparison.

We assessed the quality of the evidence for the limited qualitative data which was available relating to factors affecting access to and acceptability of support as moderate to low overall ( Table 6 ).

We have very little confidence in the effect estimates (which all suggest no effect of peer support interventions) for all outcomes in this review. The true effects may differ substantially from those reported here.

Potential biases in the review process

We minimised bias in this review by adhering to our published protocol ( Sartore 2013 ). Changes to this protocol are detailed below; they include expanding inclusion criteria to account for studies where peer support was an active control, and combining depression and anxiety outcomes into a general psychological distress outcome. These changes were made in consultation with Cochrane Australia. We also did not conduct our planned subgroup analyses, stratification by design, and sensitivity analyses, as these were no longer appropriate given the lack of main effects. In any case subgroup analyses could not be conducted because of the small number of studies contributing data to each outcome, within each comparison.

These changes aside, we adhered to a comprehensive search strategy, and two reviewers independently assessed eligibility criteria, extracted data, assessed risk of bias, and used GRADE criteria to evaluate our degree of confidence in the evidence. A third reviewer was available to resolve differences.

As discussed in previous sections, the range of scales for each outcome was quite broad, and we had to use our best judgement in grouping them to derive standardized mean difference estimates. While psychometric and other information was available for most scales and we attempted the most sensible groupings given the scales we had, it is possible that other reviewers would have made different decisions as to which scales should be allocated to which outcomes.

We attempted to contact authors for additional outcome data, to resolve uncertainties, and to request any unpublished studies. Despite these activities, and our extensive searches for relevant literature, it is possible that we may have missed studies relevant for inclusion in the review.

Agreements and disagreements with other studies or reviews

We identified five completed Cochrane reviews relevant to this area. All concerned peer support for adult participants who were directly experiencing a condition or supporting another adult, rather than children living with a condition.

Dale 2008 assessed the effectiveness of peer support telephone calls to improve physical, psychological, and behavioural health outcomes in adults. While there was some evidence of effect for some outcomes (such as improving screening rates, increasing healthy behaviours, and reducing symptoms of depression) the authors concluded, as we did, that few of the studies were of high quality and that methodological limitations decrease confidence in and generalizability of their findings.

Lavender 2013 investigated telephone support for women during pregnancy and six weeks postpartum. Peer support was provided only in a small minority of trials (four trials out of twenty nine meeting inclusion criteria). The review did not find clear evidence of effectiveness for telephone support, and could not draw any conclusions regarding the desirability of peer support.

In a recently updated review ( Chamberlain 2017 ) of psychosocial interventions for smoking cessation in pregnant women, the authors found that high‐quality evidence suggests that effectiveness is unclear for interventions provided by peers (compared to clear evidence of effects for counselling and incentive interventions, and borderline evidence for health education interventions). However, this review identified only a single study of peer social support.

A recent review of psychosocial interventions for informal caregivers of people living with cancer ( Treanor 2019 ) found some support for psychosocial interventions compared to usual care for improving caregiver quality of life, including 18 interventions with a component of support. However, these components formed part of a hierarchical framework (comprising information, support, coping skills training, psychotherapy, and spiritual or existential therapy) and could not be distinguished from other intervention components of the hierarchy in the analysis. Peer‐led support interventions were excluded from the review.

A very recent review of remotely delivered information, training, and support for informal caregivers of people with dementia ( González‐Fraile 2021 ) found that interventions including support or training or both, with or without information, may slightly reduce caregiver burden and improve caregiver depressive symptoms compared with provision of information alone, but not compared with usual treatment, waiting list, or attentional control. Both peer support and professional support interventions were eligible for inclusion in the review. Such interventions may not add significantly to usual care in settings where social and health resources are well developed and available; the authors could not comment on their efficacy in settings when usual care services cannot be accessed or are less developed.

We identified two recent non‐Cochrane reviews that are relevant to this review. Niela‐Vilén 2014 conducted a systematic review (four databases, independent screening and quality assessment but no GRADE or equivalent reporting) of internet‐based peer support for parents. Note that this review covered any parents, and not only parents of children with complex needs. Thirty‐eight publications met inclusion criteria. The authors concluded that internet‐based peer support provided informational, emotional, and affirmational support to parent; however similarly to our review they found only inconclusive evidence that this translated into improved mental well‐being. Shilling 2013 identified 17 studies (qualitative, quantitative, and mixed‐methods) of parent‐to‐parent (mentoring) support interventions. This integrative review searched a wide range of databases, journals, and grey literature and used independent screening and assessment against formal quality criteria. Again, consistent with our review the authors found that parents perceived benefit from peer support programs, but that evidence of positive effects on psychological health was inconsistent and was not able to be aggregated across studies.

Implications for practice

Parents and carers of children with complex needs perceive peer support programs as valuable, but there is currently no evidence of effect and the existing evidence is of low or very low certainty. At present, we are uncertain of the potential benefits and harms of peer support interventions in this population of parents and carers of children with complex needs. Although we are unsure of the effects of these interventions from the evidence evaluated in trials to date, qualitative data from these same trials suggest that people often valued these interventions, particularly when peer support is provided by peers perceived as available, approachable, and with similar experiences to themselves. Participants valued exchanges of practical information about condition management and having their experiences validated.

Implications for research

Ongoing randomised controlled trials could help to clarify whether peer support interventions improve outcomes for parents and carers of children with complex needs.

Of most use would be RCTs with larger samples than is generally seen here, which use and describe rigorous randomisation and allocation concealment strategies. For the kinds of outcomes assessed in this review, self‐report measures are likely to remain the most appropriate and easily‐administered; however care should be taken to select well‐validated measures with broad applicability. Researchers might also consider whether researcher‐rating scales are feasible.

In order to allow for replication and to facilitate comparisons across different studies, researchers should specify both intervention and control in as much detail as possible. This is particularly important where the control is usual care, given that participants may be participating in other programs or otherwise receiving condition‐related support with their child as part of standard care.

While qualitative data would not have changed our estimates of effect, given the nature of the interventions it is possible that mixed‐method research incorporating rigorous qualitative data would shed valuable light on participants' perceptions of peer support.

Given the low certainty of evidence to date, and the low degree of certainty in the evidence, our estimates showing no effect of intervention may change in the light of future research, especially future research of higher quality. Ideally, sufficient high‐quality research will be conducted in coming years to determine the effect of peer support programs generally, and to permit subgroup analyses for intervention type (group vs mentoring) and other important variables such as program setting, duration, and key features of participants that may importantly influence effectiveness.

Protocol first published: Issue 6, 2013

Acknowledgements

We thank Dr Megan Prictor, Dr Rebecca Ryan and Anne Parkhill for their extensive assistance in the preparation of this review, and Mr John Kis‐Rigo for his help in drafting our MEDLINE search strategy. Dr Prictor, Dr Ryan, Ms Parkhill and Mr Kis‐Rigo are from the Cochrane Consumers and Communication Review Group, based at La Trobe University's Centre for Health Communication and Participation. We thank Dr Michelle Macvean from the Parenting Research Centre for her comments on the full draft of this review.

We also thank the staff at Cochrane Australia for advice and assistance, especially Miranda Cumpston, Kelly Allen, and Dr Jo McKenzie.

Appendix 1. Quantitative data extraction template

GO TO ‘RISK OF BIAS’ BELOW

Assessment of Risk of Bias for RCTs, quasi‐RCTs and CBAs (used to complete the ‘Risk of Bias’ tables in RevMan 5.)

Adapted from Cochrane Handbook Table 8.5.a: The Cochrane Collaboration’s tool for assessing risk of bias

GO TO ‘INTERVENTION’ BELOW

GO TO ‘NOTES’ BELOW

GO TO ‘RESULTS’ BELOW

These data will be used in the “ Comparisons and Data” section in RevMan ( not the table “Characteristics of Included Studies” ) and as the basis for the “ Results ” section of review text.

All data are numbers (of patients/units), not percentages.

Dichotomous outcomes

*Note: add additional columns if there is more than one intervention group, e.g. Intervention Group A, Intervention Group B…

Continuous outcomes

*delete as appropriate

Appendix 2. Qualitative data extraction template

Appendix 3. record of author contacts, appendix 4. central search strategy.

1. child* or infan* or toddler* or newborn or neonat* or baby or babies or preschool* or pre‐school* or boy or boys or girl or girls or schoolchild* or school‐age or adolescen* or pediatric* or paediatric* or youth* or juvenile* or teen* or "minors"

2. [mh pediatrics]

3. {or #1‐#2}

4. [mh parents]

5. (parent or parents or parental or parenting or mother* or maternal or father* or paternal or carer* or caregiver* or care‐giver* or guardian* or stepparent* or foster‐care or foster‐home* or childrearing or child‐rearing):ti,ab,kw

6. [mh "parent child relations"]

7. {or #4‐#6}

8. #3 and #7

9. chronic*:ti,ab,kw

10. ((persistent or long*‐term or ongoing or degenerative) near/3 (disease* or disab* or ill* or condition or impairment)):ti,ab,kw

11. long*‐term‐care:ti,ab,kw

12. [mh "cardiovascular diseases"]

13. ((coronary or artery) next (disease* or disorder*)):ti,ab,kw

14. (angina‐pectoris or hypertension or high‐blood‐pressure):ti,ab,kw

15. ((heart or *cardia* or cardio*) next (disease* or disorder* or failure)):ti,ab,kw

16. ((myocardial or brain or cerebral) next (ischemia or infarction)):ti,ab,kw

17. (cerebrovascular or stroke or epilep* or seizure*):ti,ab,kw

18. [mh "lung diseases obstructive"]

19. (obstructive‐lung‐disease* or obstructive‐pulmonary‐disease* or obstructive‐airway*‐disease* or copd or asthma* or bronchitis):ti,ab,kw

20. [mh emphysema]

21. [mh "pulmonary emphysema"]

22. emphysema:ti,ab,kw

23. (cystic‐fibrosis or respiratory‐distress):ti,ab,kw

24. [mh "nervous system diseases"]

25. ((neurologic* or brain) next (disease* or damage* or injur*)):ti,ab,kw

26. (neurodegenerative or Huntington* or Parkinson* or amyotrophic‐lateral‐sclerosis or multiple‐sclerosis or motor‐neuron*‐disease):ti,ab,kw

27. (down* near/2 syndrome):ti,ab,kw

28. (palsy or paralys* or quadriplegi* or tetraplegi* or paraplegi* or locked‐in‐syndrome):ti,ab,kw

29. ((communication or learning or consciousness or language or speech or voice or vision or visual or hearing) next disorder*):ti,ab,kw

30. (hearing‐loss or hearing‐aid* or deaf* or blind* or stutter*):ti,ab,kw

31. [mh "gastrointestinal diseases"]

32. ((intestinal or bowel or colon*) next (disease* or disorder*)):ti,ab,kw

33. (((inflammatory or irritable) next (colon or bowel)) or colitis or crohn* or gastroenter*):ti,ab,kw

34. [mh "nutrition disorders"]

35. (underweight or malnutrition or malnourished or overweight or obes*):ti,ab,kw

36. ((renal or kidney) next (failure or insufficienc* or disease*)):ti,ab,kw

37. (diabetes or diabetic*):ti,ab,kw

38. [mh arthritis]

39. [mh "rheumatic diseases"]

40. (*arthritis or rheumati* or fibromyalgia):ti,ab,kw

41. (((back or neck) next (pain or ache)) or backache):ti,ab,kw

42. [mh "thyroid diseases"]

43. thyroid‐disease*:ti,ab,kw

44. [mh hypersensitivity]

45. (hypersensitivit* or allerg* or intolerance or anaphyla*):ti,ab,kw

46. [mh neoplasms]

47. (cancer* or oncolog* or neoplasm* or carcinom* or tumo*r* or malignan* or leuk*emia):ti,ab,kw

48. [mh "hiv infections"]

49. (hiv‐infect* or hiv‐disease or human‐immunodeficiency‐virus‐infection):ti,ab,kw

50. [mh "mental disorders"]

51. [mh "behavioral symptoms"]

52. ((mental* or psychiatr* or psychological* or behavioral*) next (ill* or disorder* or disease* or distress or disab* or dysfunction* or problem* or health* or patient* or treatment*)):ti,ab,kw

53. ((personality or mood or dysthymic or cognit* or anxiety or stress or eating or adjustment or reactive or somatoform or conversion or behavior* or percept* or thought or psycho* or impulse‐control or development* or attention‐deficit or hyperactivity or conduct or motor‐skills or movement or tic or substance‐related) next disorder*):ti,ab,kw

54. (psychosis or psychoses or psychotic* or paranoi* or schizo* or neurosis or neuroses or neurotic* or delusion* or depression or depressive or bipolar or mania or manic or obsessi* or compulsi* or panic or phobic or phobia or anorexia or bulimia or neurastheni* or dissociative or autis* or Asperger* or Tourette or dyslex* or affective or borderline or narcissis* or suicid* or self‐injur* or self‐harm or adhd):ti,ab,kw

55. (((substance or drug or alcohol) next abuse) or "substance use" or "illegal drug use" or addict* or alcoholism or (problem* near/1 drinking)):ti,ab,kw

56. [mh "congenital hereditary and neonatal diseases and abnormalities"]

57. (congenital* or abnormalit*):ti,ab,kw

58. [mh "chromosome aberrations"]

59. ((genetic or hereditary or chromosome) next (disease* or disorder*)):ti,ab,kw

60. [mh "disease susceptibility"]

61. (susceptib* or predispos*):kw

62. [mh "infant low birth weight"]

63. [mh "infant premature"]

64. (preterm or birth‐weight or (premature near/1 (infant* or birth))):ti,ab,kw

65. ((development* or growth) near/1 (delay* or disorder*)):ti,ab,kw

66. ((newborn or neonatal or infant or child* or adolescent or juvenile) next (disease* or disorder*)):ti,ab,kw

67. [mh "disabled persons"]

68. (disabled or disabilit* or handicap* or impaired or impairment* or dysfunction*):ti,ab,kw

69. ((behavio* or emotion*) near/1 (problem* or disorder*)):ti,ab,kw

70. (sensory‐dysfunction* or sensory‐system‐disorder*):ti,ab,kw

71. [mh "special education"]

72. (special near/1 education):ti,ab,kw

73. ((complex or special) near/3 need*):ti,ab,kw

74. {or #9‐#73}

75. #8 and #74

76. ((lay or user*) near/2 (led or run)):ti,ab,kw

77. (lay near/2 (expert* or person* or worker* or advisor* or consultant* or leader* or educator* or tutor*)):ti,ab,kw

78. (layperson* or expert‐patient* or non‐professional* or nonprofessional* or non‐medical or nonmedical):ti,ab,kw

79. (peer or peers):ti,ab,kw

80. (((self‐help or support*) next (group* or network*)) or ((parent* or carer* or caregiv* or care‐giv*) near/2 (group* or network*)) or (mutual next (aid or support)) or ((social or community) near/2 network*)):ti,ab,kw

81. (parent‐to‐parent):ti,ab,kw

82. social‐support:kw

83. (mentor* or befriend* or buddy or buddies):ti,ab,kw

84. volunteer*:kw

85. ((trained or aide*) near/1 volunteer*):ti,ab,kw

86. ((voluntary or volunteer) next (work* or care* or service* or involvement or health* or help* or counsel* or staff or personnel or provider* or group* or organi*ation* or agenc* or sector or program*)):ti,ab,kw

87. ((online or on‐line or internet or web or electronic or virtual) next communit*):ti,ab,kw

88. {or #76‐#87}

89. #75 and #88

Appendix 5. Journals @ Ovid search strategy

1. (child* or infan* or toddler* or newborn or neonat* or baby or babies or preschool* or pre‐school* or boy? or girl? or schoolchild* or school‐age or adolescen* or pediatric* or paediatric* or youth* or juvenile* or teen* or minors).ti,ab.

2. (parent? or parental or parenting or mother* or maternal or father* or paternal).ti,ab.

3. (carer* or caregiver* or care giver* or guardian* or stepparent* or foster care or foster home* or childrearing or child rearing).ti,ab.

4. 1 and (2 or 3)

5. chronic*.ti,ab.

6. ((persistent or long* term or ongoing or degenerative) adj3 (disease* or ill* or condition* or insufficienc* or disorder*)).ti,ab.

7. long* term care.ti,ab.

8. (cardi* disease* or heart disease* or heart failure or myocardial ischemia or coronary disease* or coronary artery disease* or myocardial infarction or hypertension or high blood pressure).ti,ab.

9. sickle cell.ti,ab.

10. (obstructive lung disease* or obstructive pulmonary disease* or copd or asthma or bronchitis).ti,ab.

11. emphysema.ti,ab.

12. (cystic fibrosis or respiratory distress).ti,ab.

13. (brain adj (disease* or damage* or injur*)).ti,ab.

14. (cerebrovascular or brain ischemia or cerebral infarction or carotid artery disease* or stroke or epilep* or seizure*).ti,ab.

15. (neurodegenerative or Huntington* or Parkinson* or amyotrophic lateral sclerosis or multiple sclerosis or motor neuron disease).ti,ab.

16. (paralys* or quadriplegi* or tetraplegi* or paraplegi* or locked‐in syndrome).ti,ab.

17. ((communication or learning or consciousness or perceptual or language or speech or voice or vision or hearing or psychomotor) adj disorder*).ti,ab.

18. (hearing loss or hearing aid* or deaf* or blind* or stutter*).ti,ab.

19. down* syndrome.ti,ab.

20. cerebral palsy.ti,ab.

21. (gatroenter* or intestinal or bowel or colonic).ti,ab.

22. ((renal or kidney) adj (failure* or insufficienc*)).ti,ab.

23. (diabetes or diabetic*).ti,ab.

24. (underweight or malnutrition or malnourished or overweight or obes*).ti,ab.

25. (arthritis or osteoarthritis or rheumati* or fibromyalgia).ti,ab.

26. ((back or neck) adj pain).ti,ab.

27. thyroid.ti,ab.

28. (hypersensitivit* or allerg* or intolerance or anaphyla*).ti,ab.

29. (cancer* or oncolog* or neoplasm* or carcinom* or tumo?r* or malignan* or leuk?emia).ti,ab.

30. (hiv infect* or hiv disease*).ti,ab.

31. ((mental* or psychiatr* or psychological*) adj (ill* or disorder* or disease* or distress* or disab* or dysfunction* or problem* or health* or patient* or treatment)).ti,ab.

32. ((personality or mood or dysthymic or cognit* or anxiety or stress or eating or adjustment or reactive or somatoform or conversion or behavior or percept* or psycho* or impulse control or development* or attention deficit or hyperactivity or conduct or motor skills or movement or tic or substance related) adj disorder*).ti,ab.

33. (psychos#s or psychotic* or paranoi* or schizo* or neuros#s or neurotic* or delusion* or depression or depressive or bipolar or mania or manic or obsessi* or compulsi* or panic or phobic or phobia or anorexia or bulimia or neurastheni* or dissociative or autis* or Asperger* or Tourette or dyslex* or affective or borderline or narcissis* or suicid* or self injur* or self harm or adhd).ti,ab.

34. (((substance or drug or alcohol) adj abuse) or "substance use" or "illegal drug use" or addict* or alcoholism or (problem* adj1 drinking)).ti,ab.

35. (congenital* or abnormalit*).ti,ab.

36. ((genetic or hereditary or chromosome) adj (disease* or disorder*)).ti,ab.

37. (preterm or low birth weight).ti,ab.

38. growth disorder*.ti,ab.

39. (development* adj1 delay*).ti,ab.

40. ((newborn or neonatal or infant or child* or adolescent or juvenile) adj (disease* or disorder*)).ti,ab.

41. (disabled or disabilit* or handicap* or impaired or impairment* or dysfunction*).ti,ab.

42. ((behavio* or emotion*) adj1 (problem* or disorder*)).ti,ab.

43. ((complex or special) adj3 need*).ti,ab.

44. or/5‐43

45. 4 and 44

46. ((lay or user*) adj2 (led or run)).ti,ab.

47. (lay adj2 (expert* or person* or worker* or advisor* or consultant* or leader* or educator* or tutor*)).ti,ab.

48. (layperson* or expert patient* or non professional* or nonprofessional* or non medical or nonmedical).ti,ab.

49. peer?.ti,ab.

50. (((self help or support*) adj (group* or network*)) or ((parent* or carer* or caregiv* or care giv*) adj2 (group* or network*)) or (mutual adj (aid or support)) or ((social or community) adj2 network*)).ti,ab.

51. parent to parent.ti,ab.

52. (mentor* or befriend* or buddy or buddies).ti,ab.

53. ((trained or aide*) adj1 volunteer*).ti,ab.

54. ((voluntary or volunteer) adj (work* or care* or service* or involvement or health* or help* or counsel* or staff or personnel or provider* or group* or organi#ation* or agenc* or sector)).ti,ab.

55. ((online or on‐line or internet or web or electronic or virtual) adj communit*).ti,ab.

56. or/46‐55

57. 45 and 56

58. random*.ti,ab.

59. (experiment* or intervention*).ti,ab.

60. trial*.ti,ab.

61. placebo*.ti,ab.

62. ((singl* or doubl* or trebl* or tripl*) and (blind* or mask*)).ti,ab.

63. (pre test or pretest or post test or posttest).ti,ab.

64. (preintervention or postintervention).ti,ab.

65. (cross over or crossover or factorial* or latin square).ti,ab.

66. (assign* or allocat* or volunteer*).ti,ab.

67. (control* or compar* or prospectiv*).ti,ab.

68. (impact* or effect? or chang* or evaluat*).ti,ab.

69. or/58‐68

70. 57 and 69

Appendix 6. BiblioMap search strategy

1 Freetext: "child*" or "infan*" or "toddler*" or "newborn" or "neonat*" or "baby" or "babies" or "preschool*" or "pre‐school*" or "boy" or "boys" or "girl" or "girls" or "schoolchild*" or "school‐age" or "adolescen*" or "pediatric*" or "paediatric*" or "youth*" or "juvenile*" or "teen*" or "minors"

2 Freetext: "parent" or "parents" or "parental" or "parenting" or "mother*" or "maternal" or "father*" or "paternal" or "carer*" or "caregiver*" or "care giver*" or "guardian*" or "stepparent*" or "foster care" or "foster home*" or "childrearing" or "child rearing"

3 Person(s) providing the intervention: community OR community worker OR counsellor OR health promotion practitioner OR lay therapist OR parent OR peer

4 What type of study does this report describe?: intervention OR outcome evaluation OR process evaluation OR RCT OR trial

5 1 AND 2 AND 3 AND 4

Appendix 7. MEDLINE search strategy

1. exp child/

2. exp infant/

3. adolescent/

5. pediatrics/

6. (child* or infant* or newborn* or baby or babies or neonat* or perinatal or adolescen* or youth* or juvenile or teen* or pediatric*).tw,hw.

7. or/1‐6

8. exp parents/

9. exp parent child relations/

10. parenting/

11. child rearing/

12. foster home care/

13. (parent? or parental or parenting or mother* or maternal or father* or paternal).tw.

14. caregivers/

15. (carer* or caregiver* or care giver* or guardian* or foster care or foster home*).tw.

16. or/8‐15

17. 7 and 16

18. chronic*.mp.

19. ((persistent or long* term or ongoing or degenerative) adj3 (disease* or ill* or condition* or insufficienc* or disorder*)).tw.

20. long term care/

21. long* term care.tw.

22. exp cardiovascular diseases/

23. (heart disease* or heart failure or myocardial ischemia or coronary disease* or coronary artery disease* or myocardial infarction or hypertension or high blood pressure).tw.

24. sickle cell.mp.

25. exp lung diseases obstructive/

26. (obstructive lung disease* or obstructive pulmonary disease* or copd or asthma or bronchitis).tw.

27. exp emphysema/

28. exp pulmonary emphysema/

29. emphysema.tw.

30. (cystic fibrosis or respiratory distress).mp.

31. exp nervous system diseases/

32. (brain adj (disease* or damage* or injur*)).tw.

33. (cerebrovascular or brain ischemia or cerebral infarction or carotid artery disease* or stroke or epilep* or seizure*).tw.

34. (neurodegenerative or Huntington* or Parkinson* or amyotrophic lateral sclerosis or multiple sclerosis or motor neuron disease).tw.

35. (paralys* or quadriplegi* or tetraplegi* or paraplegi* or locked‐in syndrome).tw.

36. ((communication or learning or consciousness or perceptual or speech or voice or vision or hearing or psychomotor) adj disorder*).tw.

37. (hearing loss or hearing aid* or deaf* or blind* or stutter*).tw.

38. down* syndrome.tw.

39. cerebral palsy.tw.

40. exp gastrointestinal diseases/

41. (gastroenter* or intestinal or bowel or colonic).tw.

42. renal insufficiency/

43. ((renal or kidney) adj (failure* or insufficienc*)).tw.

44. diabetes mellitus/

45. (diabetes or diabetic*).tw.

46. exp nutrition disorders/

47. (underweight or malnutrition or malnourished or overweight or obes*).tw.

48. exp arthritis/

49. exp rheumatic diseases/

50. (arthritis or osteoarthritis or rheumati* or fibromyalgia).tw.

51. ((back or neck) adj pain).tw.

52. exp thyroid diseases/

53. thyroid.tw.

54. exp hypersensitivity/

55. (hypersensitivit* or allerg* or intolerance or anaphyla*).mp.

56. exp neoplasms/

57. (cancer* or oncolog* or neoplasm* or carcinom* or tumo?r* or malignan* or leuk?emia).tw.

58. exp hiv infections/

59. (hiv infect* or hiv disease*).tw.

60. exp mental disorders/

61. exp behavioral symptoms/

62. ((mental* or psychiatr* or psychological*) adj (ill* or disorder* or disease* or distress* or disab* or problem* or health* or patient* or treatment)).tw.

63. ((personality or mood or dysthymic or cognit* or anxiety or stress or eating or adjustment or reactive or somatoform or conversion or behavior or perception or psycho* or impulse control or development* or attention deficit or hyperactivity or conduct or motor skills or movement or tic or substance related) adj disorder*).tw.

64. (psychos#s or psychotic* or paranoi* or schizo* or neuros#s or neurotic* or delusion* or depression or depressive or bipolar or mania or manic or obsessi* or compulsi* or panic or phobic or phobia or anorexia or bulimia or neurastheni* or dissociative or autis* or Asperger* or Tourette or dyslex* or affective or borderline or narcissis* or suicid* or self injur* or self harm or adhd).tw.

65. (((substance or drug or alcohol) adj abuse) or "substance use" or "illegal drug use" or addict* or alcoholism or (problem* adj1 drinking)).tw.

66. exp "Congenital, Hereditary, and Neonatal Diseases and Abnormalities"/

67. (congenital* or abnormalit*).mp.

68. exp chromosome aberrations/

69. ((genetic or hereditary or chromosome) adj (disease* or disorder*)).mp.

70. exp disease susceptibility/

71. exp infant low birth weight/

72. infant premature/

73. (preterm or low birth weight).tw.

74. growth disorder*.mp.

75. exp disabled persons/

76. (disabled or disabilit* or handicapped or impaired or impairment* or dysfunction*).tw.

77. developmental delay*.tw.

78. ((behavio* or emotion*) adj1 (problem* or disorder*)).mp.

79. exp education special/

80. ((complex or special) adj3 need*).tw.

81. or/18‐80

82. 17 and 81

83. ((lay or user*) adj2 (led or run)).tw.

84. (lay adj2 (expert* or person* or worker* or advisor* or consultant* or leader* or educator* or tutor*)).tw.

85. (layperson* or expert patient* or non professional* or nonprofessional* or non medical or nonmedical).tw.

86. peer group/

87. peer?.tw.

88. self help groups/

89. (((self help or support*) adj (group* or network*)) or ((parent* or carer* or caregiv* or care giv*) adj2 (group* or network*)) or (mutual adj (aid or support)) or ((social or community) adj2 network*)).tw.

90. parent to parent.tw.

91. community networks/

92. mentors/

93. (mentor* or befriend* or buddy or buddies).tw.

94. voluntary workers/

95. ((trained or aide*) adj1 volunteer*).tw.

96. ((voluntary or volunteer) adj (work* or care* or service* or involvement or health* or help* or counsel* or staff or personnel or provider* or group* or organi#ation* or agenc* or sector)).tw.

97. ((online or on‐line or internet or web or electronic or virtual) adj communit*).tw.

98. or/83‐97

99. 82 and 98

100. randomized controlled trial.pt. 101. controlled clinical trial.pt. 102. clinical trial.pt. 103. evaluation studies.pt. 104. comparative study.pt. 105. random*.tw. 106. placebo*.tw. 107. trial.tw. 108. research design/ 109. follow up studies/ 110. prospective studies/ 111. cross over studies/ 112. (experiment* or intervention*).tw. 113. (pre test or pretest or post test or posttest).tw. 114. (preintervention or postintervention).tw. 115. time series.tw. 116. (cross over or crossover or factorial* or latin square).tw. 117. (assign* or allocat* or volunteer*).tw. 118. (control* or compar* or prospectiv*).tw. 119. (impact* or effect? or chang* or evaluat*).tw. 120. or/100‐119 121. exp animals/ not humans.sh. 122. 120 not 121 123. 99 and 122

Appendix 8. Embase search strategy

2. exp newborn/

3. exp adolescent/

4. exp pediatrics/

5. (child* or infan* or toddler* or newborn or neonat* or baby or babies or preschool* or pre‐school* or boy? or girl? or schoolchild* or school‐age or adolescen* or pediatric* or paediatric* or youth* or juvenile* or teen* or minors).mp.

6. or/1‐5

7. exp parental behavior/

8. (parent? or parental or parenting or mother* or maternal or father* or paternal).mp.

9. (carer* or caregiver* or care giver* or guardian* or stepparent* or foster care or foster home* or childrearing or child rearing).mp.

10. or/7‐9

11. 6 and 10

12. chronic*.mp.

13. ((persistent or long* term or ongoing or degenerative) adj3 (disease* or disorder* or disab* or ill* or condition*)).ti,ab,kw.

14. long term care/

15. long* term care.ti,ab,kw.

16. exp degenerative disease/

17. (neurodegenerative or Huntington* or Parkinson* or amyotrophic lateral sclerosis or motor neuron* disease).ti,ab,kw.

18. exp neurologic disease/

19. (brain adj (damag* or injur*)).ti,ab,kw.

20. multiple sclerosis.ti,ab,kw.

21. exp paralysis/

22. (palsy or paralys* or quadriplegi* or tetraplegi* or paraplegi* or locked‐in syndrome).ti,ab,kw.

23. exp arthritis/

24. exp rheumatic disease/

25. (arthritis or osteoarthritis or rheumati*).ti,ab,kw.

26. exp obstructive airway disease/

27. (obstructive lung disease* or obstructive pulmonary disease* or copd or asthma* or bronchitis).ti,ab,kw.

28. exp emphysema/

29. emphysema.ti,ab,kw.

30. exp diabetes mellitus/

31. (diabetes or diabetic).ti,ab,kw.

32. exp hypertension/

33. (hypertension or high blood pressure).ti,ab,kw.

34. exp cerebrovascular disease/

35. (cerebrovascular disease* or cerebrovascular disorder* or brain ischemia or cerebral infarction or carotid artery disease* or stroke).ti,ab,kw.

36. exp epilepsy/

37. epilep*.ti,ab,kw.

38. exp ischemic heart disease/

39. (myocardial ischemia or angina pectoris or coronary disease* or coronary artery disease* or myocardial infarction).ti,ab,kw.

40. exp heart failure/

41. ((heart or cardiac) adj (failure or disease* or disorder*)).ti,ab,kw.

42. kidney disease/

43. ((renal or kidney) adj (failure* or insufficien* or disease*)).ti,ab,kw.

44. exp colon disease/

45. (colon* disease* or colon* disorder* or colitis or crohn*).ti,ab,kw.

46. ((inflammatory or irritable) adj (colon or bowel)).ti,ab,kw.

47. exp obesity/

48. (obesity or obese).ti,ab,kw.

49. exp human immunodeficiency virus infection/

50. (hiv infect* or hiv disease*).ti,ab,kw.

51. exp osteoporosis/

52. osteoporosis.ti,ab,kw.

53. fibromyalgia/

54. fibromyalgia*.ti,ab,kw.

55. endometriosis.mp.

56. exp thyroid disease/

57. (thyroid adj (disease* or disorder*)).ti,ab,kw.

58. exp neoplasm/

59. (cancer* or oncolog* or neoplasm* or carcinom* or tumo?r* or malignan*).ti,ab,kw.

60. exp mental disease/

61. ((mental* or psychiatr* or psychological*) adj (ill* or disorder* or disease* or distress* or disab* or dysfunction* or problem* or health* or patient* or treatment)).ti,ab,kw.

62. ((personality or mood or dysthymic or cognit* or anxiety or stress or eating or adjustment or reactive or somatoform or conversion or behavior or communication or language or learning or percept* or thought or psycho* or impulse control or development* or attention deficit or hyperactivity or conduct or motor skills or movement or tic or substance related) adj disorder*).ti,ab,kw.

63. (psychos#s or psychotic* or paranoi* or schizo* or neuros#s or neurotic* or delusion* or depression or depressive or bipolar or mania or manic or obsessi* or compulsi* or panic or phobic or phobia or anorexia or bulimia or neurastheni* or dissociative or autis* or Asperger* or Tourette or dyslex* or affective or borderline or narcissis* or suicid* or self injur* or self harm or adhd).ti,ab,kw.

64. (((substance or drug or alcohol) adj abuse) or "substance use" or "illegal drug use" or addict* or alcoholism or (problem* adj1 drinking)).ti,ab,kw.

65. exp "genetic and familial disorders"/

66. exp infant disease/

68. ((genetic or hereditary or chromosome) adj (disease* or disorder*)).mp.

69. exp disease predisposition/

70. (predispos* or susceptib*).ti,ab,kw.

71. (preterm or low birth weight or premature infant*).ti,ab,kw.

72. exp disability/

73. disabled person/

74. (disabled or disabilit* or handicap* or impaired or impairment* or dysfunction*).mp.

75. exp childhood disease/

76. exp adolescent disease/

77. exp developmental disorder/

78. exp growth disorder/

79. ((development* or growth) adj1 (delay* or disorder*)).ti,ab,kw.

80. ((newborn or neonatal or infant or child* or adolescent or juvenile) adj (disease* or disorder*)).ti,ab,kw.

81. ((behavio* or emotion*) adj1 (problem* or disorder*)).ti,ab,kw.

82. exp sensory dysfunction/

83. (deaf* or blind* or ((vision or visual or hearing) adj disorder*) or hearing loss or hearing aid*).ti,ab,kw.

84. exp speech disorder/

85. (((speech or voice) adj disorder*) or stutter*).ti,ab,kw.

86. exp special education/

87. ((complex or special) adj3 need*).ti,ab,kw.

88. or/12‐87

89. 11 and 88

90. ((lay or user*) adj2 (led or run)).ti,ab,kw.

91. (lay adj2 (expert* or person* or worker* or advisor* or consultant* or leader* or educator* or tutor*)).ti,ab,kw.

92. (layperson* or expert patient* or non professional* or nonprofessional* or non medical or nonmedical).ti,ab,kw.

93. peer group/

94. peer counseling/

95. peer?.ti,ab,kw.

96. (((self help or support*) adj (group* or network*)) or ((parent* or carer* or caregiv* or care giv*) adj2 (group* or network* or support)) or (mutual adj (aid or support)) or ((social or community) adj network*)).mp.

97. parent to parent.ti,ab,kw.

98. (mentor* or befriend* or buddy or buddies).ti,ab,kw.

99. voluntary worker/

100. voluntary program/

101. volunteer/

102. ((trained or aide*) adj1 volunteer*).ti,ab,kw.

103. ((voluntary or volunteer) adj (work* or care* or service* or involvement or health* or help* or counsel* or staff or personnel or provider* or group* or organi#ation* or agenc* or sector)).ti,ab,kw.

104. ((online or on‐line or internet or web or electronic or virtual) adj communit*).ti,ab,kw.

105. or/90‐104

106. 89 and 105

107. randomized controlled trial/

108. controlled clinical trial/

109. single blind procedure/ or double blind procedure/

110. crossover procedure/

111. random*.tw.

112. trial.tw.

113. placebo*.tw.

114. ((singl* or doubl*) adj (blind* or mask*)).tw.

115. (experiment* or intervention*).tw.

116. (pre test or pretest or post test or posttest).tw.

117. (preintervention or postintervention).tw.

118. (cross over or crossover or factorial* or latin square).tw.

119. (assign* or allocat* or volunteer*).tw.

120. (control* or compar* or prospectiv*).tw.

121. (impact* or effect? or chang* or evaluat*).tw.

122. time series.tw.

123. or/107‐122

124. 106 and 123

Appendix 9. PsycINFO search strategy

1. ("100" or "120" or "140" or "160" or "180" or "200").ag.

2. (child* or infan* or toddler* or newborn or neonat* or baby or babies or preschool* or pre‐school* or boy? or girl? or schoolchild* or school‐age or adolescen* or pediatric* or paediatric* or youth* or juvenile* or teen* or minors).ti,ab,hw,id.

3. or/1‐2

4. exp parents/

5. exp parenting/

6. (parent? or parental or parenting or mother* or maternal or father* or paternal).ti,ab,hw,id.

7. (carer* or caregiver* or care giver* or guardian* or stepparent* or foster care or foster home* or childrearing or child rearing).ti,ab,hw,id.

8. or/4‐7

10. chronic*.ti,ab,hw,id.

11. ((persistent or long* term or ongoing or degenerative) adj3 (disease* or disorder* or disab* or ill* or condition*)).ti,ab,hw,id.

12. long term care/

13. long* term care.ti,ab,id.

14. exp nervous system disorders/

15. (neurodegenerative or Huntington* or Parkinson* or amyotrophic lateral sclerosis or motor neuron* disease).ti,ab,hw,id.

16. (paralys* or palsy or quadriplegi* or tetraplegi* or paraplegi* or locked‐in syndrome).ti,ab,hw,id.

17. multiple sclerosis.ti,ab,hw,id.

18. (arthritis or osteoarthritis or rheumati*).ti,ab,hw,id.

19. (obstructive lung disease* or obstructive pulmonary disease* or copd or asthma* or bronchitis or bronchial).ti,ab,hw,id.

20. emphysema.ti,ab,hw,id.

21. (diabetes or diabetic).ti,ab,hw,id.

22. ((cardiovascular or cerebrovascular or coronary or artery) adj (disease* or disorder*)).ti,ab,hw,id.

23. ((myocardial or brain or cerebral) adj (ischemia or infarction)).ti,ab,hw,id.

24. (stroke or epilep* or seizure*).ti,ab,hw,id.

25. ((heart or cardiac) adj (disease* or disorder* or failure)).ti,ab,hw,id.

26. (hypertension or high blood pressure).ti,ab,hw,id.

27. (dementia or alzheimer*).ti,ab,hw,id.

28. ((renal or kidney) adj (failure* or insufficienc* or disease*)).ti,ab,hw,id.

29. (colon* disease* or colon* disorder* or colitis or irritable bowel syndrome).ti,ab,hw,id.

30. (obesity or obese).ti,ab,hw,id.

31. exp hiv/

32. (hiv infect* or hiv disease*).ti,ab,id.

33. osteoporosis.ti,ab,hw,id.

34. fibromyalgia*.ti,ab,hw,id.

35. exp neoplasms/

36. (cancer* or oncolog* or neoplasm* or carcinom* or tumo?r* or malignan*).ti,ab,hw,id.

37. exp mental disorders/

38. exp behavior disorders/

39. ((mental* or psychiatr* or psychological*) adj (ill* or disorder* or disease* or distress* or disab* or dysfunction* or problem* or health* or patient* or treatment)).ti,ab,hw,id.

40. ((personality or mood or dysthymic or cognit* or anxiety or stress or eating or adjustment or reactive or somatoform or conversion or behavior or communication or language or learning or percept* or thought or psycho* or impulse control or development* or attention deficit or hyperactivity or conduct or motor skills or movement or tic or substance related) adj disorder*).ti,ab,hw,id.

41. (psychos#s or psychotic* or paranoi* or schizo* or neuros#s or neurotic* or delusion* or depression or depressive or bipolar or mania or manic or obsessi* or compulsi* or panic or phobic or phobia or anorexia or bulimia or neurastheni* or dissociative or autis* or Asperger* or Tourette or dyslex* or affective or borderline or narcissis* or suicid* or self injur* or self harm or adhd).ti,ab,hw,id.

42. (((substance or drug or alcohol) adj abuse) or "substance use" or "illegal drug use" or addict* or alcoholism or (problem* adj1 drinking)).ti,ab,hw,id.

43. exp disabilities/

44. (disabled or disabilit* or handicap* or impaired or impairment* or dysfunction*).ti,ab,hw,id.

45. exp genetic disorders/

46. exp congenital disorders/

47. (congenital* or abnormalit*).ti,ab,hw,id.

48. ((genetic or hereditary or chromosome) adj (disease* or disorder*)).ti,ab,hw,id.

49. "susceptibility (disorders)"/

50. predisposition/

51. exp neonatal disorders/

52. premature birth/

53. birth weight/

54. (preterm or low birth weight or premature infant*).ti,ab,hw,id.

55. growth disorder*.ti,ab,hw,id.

56. exp intellectual development disorder/

57. down* syndrome.ti,ab,hw,id.

58. exp delayed development/

59. (development* adj1 delay*).ti,ab,hw,id.

60. ((newborn or neonatal or infant or child* or adolescent or juvenile) adj (disease* or disorder*)).ti,ab,hw,id.

61. ((behavio* or emotion*) adj1 (problem* or disorder*)).mp.

62. exp communication disorders/

63. exp sensory system disorders/

64. (deaf* or blind* or hearing disorder* or vis* disorder* or hearing loss or hearing aid*).ti,ab,hw,id.

65. special education/

66. ((complex or special) adj3 need*).ti,ab,hw,id.

67. or/10‐66

68. 9 and 67

69. ((lay or user*) adj2 (led or run)).ti,ab,hw,id.

70. (lay adj2 (expert* or person* or worker* or advisor* or consultant* or leader* or educator* or tutor*)).ti,ab,hw,id.

71. (layperson* or expert patient* or non professional* or nonprofessional* or non medical or nonmedical).ti,ab,id.

72. peer?.ti,ab,hw,id.

73. (((self help or support*) adj (group* or network*)) or ((parent* or carer* or caregiv* or care giv*) adj2 (group* or network*)) or (mutual adj (aid or support)) or ((social or community) adj2 network*)).ti,ab,hw,id.

74. parent to parent.ti,ab,id.

75. social support/

76. mentor/

77. (mentor* or befriend* or buddy or buddies).ti,ab,id.

78. volunteers/

79. ((trained or aide*) adj1 volunteer*).tw.

80. ((voluntary or volunteer) adj (work* or care* or service* or involvement or health* or help* or counsel* or staff or personnel or provider* or group* or organi#ation* or agenc* or sector)).ti,ab,hw,id.

81. ((online or on‐line or internet or web or electronic or virtual) adj communit*).ti,ab,hw,id.

82. or/69‐81

83. 68 and 82

84. random*.ti,ab,hw,id.

85. (experiment* or intervention*).ti,ab,hw,id.

86. trial*.ti,ab,hw,id.

87. placebo*.ti,ab,hw,id.

88. ((singl* or doubl* or trebl* or tripl*) and (blind* or mask*)).ti,ab,hw,id.

89. treatment effectiveness evaluation/

90. mental health program evaluation/

91. (pre test or pretest or post test or posttest).ti,ab,hw,id.

92. (preintervention or postintervention).ti,ab,hw,id.

93. (cross over or crossover or factorial* or latin square).ti,ab,hw,id.

94. (assign* or allocat* or volunteer*).ti,ab,hw,id.

95. (control* or compar* or prospectiv*).ti,ab,hw,id.

96. (impact* or effect? or chang* or evaluat*).ti,ab,hw,id.

97. time series.ti,ab,hw,id.

98. exp experimental design/

99. ("0430" or "0450" or "0451" or "1800" or "2000").md.

100. or/84‐99

101. 83 and 100

Data and analyses

Comparison 1, comparison 2, characteristics of studies, characteristics of included studies [ordered by study id], characteristics of excluded studies [ordered by study id], characteristics of studies awaiting classification [ordered by study id], differences between protocol and review.

INCLUSION: We originally specified that peer support intervention versus no‐treatment control studies would be included, but interventions where peer support was an incidental component of a more intensive intervention would be excluded. Our search identified a third option, where peer support was used as an active control for a more intensive intervention (for example, a non‐directive support group versus a psycho‐education or therapy group). We included such studies in the review as a whole, although they could not be included in meta‐analyses unless the study also used a no‐treatment control group.

OUTCOMES: Following discussion with Cochrane Australia, it was decided to subsume protocol outcomes 1 and 2 (anxiety and depression) in a single broader outcome, psychological distress. Several studies used a general psychiatric symptom scale (the PSI), the sub‐scales for depression and/or anxiety from that general scale, or some combination of the three. From the point of view both of consumers and of agencies deciding what support to offer consumers, it is more important to know if overall psychological distress is reduced than to know the precise symptomatology. This is particularly so because none of the scales or sub‐scales were used to make formal diagnoses, nor would such diagnoses be appropriate in this context. Additionally, general distress outcomes fit better with the broad outcome categories listed above.This replaces 'level of anxiety and depression' in the protocol. Similarly, the outcomes 'confidence and skill at navigating medical, community, and service support networks' and 'knowledge of local resources' were combined, and the single outcome 'confidence and skill at navigating medical services' was reported.

Also on the advice of Cochrane Australia, we changed our method of selecting from multiple scales measuring a single outcome. We preferred full, general, scales to specific scales and sub‐scales; where there was no general scale and several specific scales and/or sub‐scales we selected one at random.

SUBGROUP ANALYSES: A number of subgroup analyses were planned to determine if particular subgroups of parents receive more or less benefit than others, or if particular settings and modes of delivery are more effective than others. As no overall effect of peer support programs was apparent, these subgroup analyses were not conducted. They should be included in any update of this review, should new studies be located and overall effectiveness demonstrated for any outcome. Any new RCT of peer support programs would benefit from considering these questions.

• How socially connected are parents before commencing the intervention?
• How is the peer support delivered: in pairs, in a group, peer‐led, facilitator‐led?
• Should peer support be delivered face‐to‐face, or assisted by technology?
• Is there an optimum group size (apart from the support pairs considered above)?
• Is there an optimum duration, either of individual sessions or of the intervention?
• Is there an optimum timing for peer support interventions?
• Is it better for peer groups or pairs to be homogeneous (that is, age‐ or condition‐specific)?

STRATIFICATION BY DESIGN: we had intended to stratify studies for meta‐analysis according to whether they were RCT or quasi‐RCT. As none of our meta‐analyses showed any effect of intervention, this was not considered necessary.

SENSITIVITY ANALYSES: we had intended to investigate the effect of variables such as existing social connectedness of participants, and delivery mode, setting, duration, and size of interventions on outcomes. We also intended to check the effects of choice of SMD across all scales versus individual mean differences and other assumptions about outcome measures on pooled estimates. In the event, there was insufficient data for such analyses to be appropriate. It was only possible to use SMDs for continuous outcomes due to the wide range of outcome measures used.

Contributions of authors

GS conceived the review question; VL provided advice on formulating the review question

GS and AP ran searches, screened retrieved studies, determined inclusions/exclusions, extracted data from included studies

VL checked studies where there was screening disagreement

GS and VL resolved outstanding screening disagreements

GS and AP completed risk of bias assessments

GS, AP, and VL checked extracted data and final inclusion decisions

GS conducted analyses and prepared the first draft of full review

GS and AP conducted and cross‐checked GRADE assessments

AP assisted with first draft of full review

VL commented on first draft of full review.

GS and AP conducted top‐up searches, screening, and extraction where updates were needed

AP and VL checked and commented on the full review, abstract, and plain language summary

GS and AP incorporated feedback and prepared the final draft.

Sources of support

Internal sources, external sources.

• No sources of support provided

Declarations of interest

The first author was previously the manager of a federally‐funded peer support program for parents and carers of children with complex needs in Australia. All three authors worked at The Parenting Research Centre, which administers the program on behalf of the Australian government, for a substantial portion of the time taken to complete this review. An evaluation of the effectiveness and acceptability of this program was conducted; no publications or data from this evaluation to date met inclusion criteria for this review.

References to studies included in this review

Aiello 2015 {published data only (unpublished sought but not used)}.

• Aiello CP, Ferrari DV. Teleaudiology: efficacy assessment of an online social network as a support tool for parents of children candidates for cochlear implant . CoDAS 2015; 27 ( 5 ):411-8. [ PubMed ] [ Google Scholar ]

Boogerd 2017 {published data only}

• Boogerd E, Maas-Van Schaaijk NM, Sas TC, Clement-de Boers A, Smallenbroek M, Nuboer R, Noordam C, Verhaak CM. Sugarsquare, a web-based patient portal for parents of a child with Type 1 diabetes: A multicenter randomized controlled feasibility trial . Journal of Medical Internet Research 2017; 19 ( 8 ):e287. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Boogerd EA, Noordam C, Verhaak CM. The Sugarsquare study: protocol of a multicenter randomized controlled trial concerning a web-based patient portal for parents of a child with type 1 diabetes . BMC Pediatrics 2014; 14 :24. [ PMC free article ] [ PubMed ] [ Google Scholar ]

Boylan 2013 {published data only (unpublished sought but not used)}

• Boylan C, Morgan S, Carthy A, Crowley S, Lyons J, Fitzpatrick C, Rickard E, Guerin S. A randomised controlled trial of a programme for parents and full-time carers of young people with self-harm and suicidal behaviour . European Child and Adolescent Psychiatry 2013; 22 ( (Suppl 2) ):S87-S313. [ Google Scholar ]

Ferrin 2014 {published data only}

• Ferrin M, Moreno-Granados JM, Salcedo-Marin MD, Ruiz-Veguilla M, Perez-Ayala V, Taylor E. Evaluation of a psychoeducation programme for parents of children and adolescents with ADHD: immediate and long-term effects using a blind randomized controlled trial . European Child and Adolescent Psychiatry 2013; 23 ( 8 ):637-47. [DOI: DOI 10.1007/s00787-013-0494-7] [ PubMed ] [ Google Scholar ]

Flores 2009 {published data only}

• Flores G, Bridon C, Torres S, Perez R, Walter T, Brotanek J, Hua L, Tomany-Korman S. Improving asthma outcomes in minority children: A randomized, controlled trial of parent mentors . Pediatrics 2009; 124 :1522-0230. [ PubMed ] [ Google Scholar ]

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New modification of Russian VVER-440 fuel loaded at Paks NPP in Hungary

DECEMBER 14, 2020 — After the recent refueling at power unit 3 of the Hungarian Paks NPP, its VVER-440 reactor has been loaded with a batch of fresh fuel including 18 fuel bundles of the new modification. The new fuel will be introduced at all four operating power units of the Paks NPP, and the amount of new-modification bundles in each refueling will be increased gradually.

Development of the new VVER-440 fuel modification was completed in 2020 under the contract between TVEL JSC and MVM Paks NPP Ltd. Its introduction would optimize the hydro-uranium ratio in the reactor core, enabling to increase the efficiency of fuel usage and advance the economic performance of the power plant operation. All VVER-440 fuel modifications are manufactured at the Elemash Machine-Building Plant, a facility of TVEL Fuel Company in Elektrostal, Moscow Region.

“Introduction of a new fuel is an option to improve technical and economic performance of a nuclear power plant without substantial investment. We are actively engaged in development of new models and modifications of VVER-440 fuel for power plants in Europe. The projects of the new fuels for Loviisa NPP in Finland, Dukovany NPP in the Czech Republic, Mochovce and Bohunice NPPs in Slovakia, are currently at various stages of implementation. Despite the same reactor model, these projects are quite different technically and conceptually, since we take into account the individual needs and requirements of our customers,” commented Natalia Nikipelova, President of TVEL JSC.

For reference:

The project of development and validation of the new fuel has been accomplished with participation of a number of Russian nuclear industry enterprises, such as OKB Gidropress (a part of Rosatom machine-building division Atomenergomash), Bochvar Institute (material science research facility of TVEL Fuel Company), Elemash Machine-building plant and Kurchatov Institute national research center. At the site of OKB Gidropress research and experiment facility, the new fuel passed a range of hydraulic, longevity and vibration tests.

Paks NPP is the only functioning nuclear power plant in Hungary with total installed capacity 2000 MWe. It operates four similar units powered by VVER-440 reactors and commissioned one by one in 1982-1987. Currently, Paks NPP is the only VVER-440 plant in the world operating in extended 15-monthes fuel cycle. The power plant produces about 15 bln kWh annually, about a half of electric power generation in Hungary. In 2018, the project of increasing the duration of Paks NPP fuel cycle won the European competition Quality Innovation Award in the nomination “Innovations of large enterprises”. Russian engineers from TVEL JSC, Kurchatov Institute, OKB Gidropress, Bochvar Institute and Elemash Machine-building plant provided assistance to the Hungarian colleagues in accomplishment of the project.

  TVEL Fuel Company of Rosatom incorporates enterprises for the fabrication of nuclear fuel, conversion and enrichment of uranium, production of gas centrifuges, as well as research and design organizations. It is the only supplier of nuclear fuel for Russian nuclear power plants. TVEL Fuel Company of Rosatom provides nuclear fuel for 73 power reactors in 13 countries worldwide, research reactors in eight countries, as well as transport reactors of the Russian nuclear fleet. Every sixth power reactor in the world operates on fuel manufactured by TVEL.  www.tvel.ru