literature review of self management

Before Managing Others, Manage Yourself Strategically: A Systematic Literature Review

• August 2021
• v(viii):650-560

• University of Sri Jayewardenepura

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Peer-reviewed

Research Article

Helping patients help themselves: A systematic review of self-management support strategies in primary health care practice

Roles Conceptualization, Data curation, Formal analysis, Methodology, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Current address: Graduate School of Health, University of Technology Sydney, Ultimo, NSW, Australia

Affiliation Graduate School of Health, University of Technology Sydney, Sydney, Australia

Roles Conceptualization, Methodology, Supervision, Validation, Writing – review & editing

Roles Conceptualization, Supervision, Writing – review & editing

Roles Conceptualization, Methodology, Supervision, Writing – review & editing

Affiliation Emeritus Professor, University of Sydney, Sydney, Australia

• Sarah Dineen-Griffin, 
• Victoria Garcia-Cardenas, 
• Kylie Williams, 
• Shalom I. Benrimoj

• Published: August 1, 2019
• https://doi.org/10.1371/journal.pone.0220116
• Reader Comments

Primary health professionals are well positioned to support the delivery of patient self-management in an evidence-based, structured capacity. A need exists to better understand the active components required for effective self-management support, how these might be delivered within primary care, and the training and system changes that would subsequently be needed.

(1) To examine self-management support interventions in primary care on health outcomes for a wide range of diseases compared to usual standard of care; and (2) To identify the effective strategies that facilitate positive clinical and humanistic outcomes in this setting.

A systematic review of randomized controlled trials evaluating self-management support interventions was conducted following the Cochrane handbook & PRISMA guidelines. Published literature was systematically searched from inception to June 2019 in PubMed, Scopus and Web of Science. Eligible studies assessed the effectiveness of individualized interventions with follow-up, delivered face-to-face to adult patients with any condition in primary care, compared with usual standard of care. Matrices were developed that mapped the evidence and components for each intervention. The methodological quality of included studies were appraised.

6,510 records were retrieved. 58 studies were included in the final qualitative synthesis. Findings reveal a structured patient-provider exchange is required in primary care (including a one-on-one patient-provider consultation, ongoing follow up and provision of self-help materials). Interventions should be tailored to patient needs and may include combinations of strategies to improve a patient’s disease or treatment knowledge; independent monitoring of symptoms, encouraging self-treatment through a personalized action plan in response worsening symptoms or exacerbations, psychological coping and stress management strategies, and enhancing responsibility in medication adherence and lifestyle choices. Follow-up may include tailored feedback, monitoring of progress with respect to patient set healthcare goals, or honing problem-solving and decision-making skills. Theoretical models provided a strong base for effective SMS interventions. Positive outcomes for effective SMS included improvements in clinical indicators, health-related quality of life, self-efficacy (confidence to self-manage), disease knowledge or control. An SMS model has been developed which sets the foundation for the design and evaluation of practical strategies for the construct of self-management support interventions in primary healthcare practice.

Conclusions

These findings provide primary care professionals with evidence-based strategies and structure to deliver SMS in practice. For this collaborative partnership approach to be more widely applied, future research should build on these findings for optimal SMS service design and upskilling healthcare providers to effectively support patients in this collaborative process.

Citation: Dineen-Griffin S, Garcia-Cardenas V, Williams K, Benrimoj SI (2019) Helping patients help themselves: A systematic review of self-management support strategies in primary health care practice. PLoS ONE 14(8): e0220116. https://doi.org/10.1371/journal.pone.0220116

Editor: Christophe Leroyer, Universite de Bretagne Occidentale, FRANCE

Received: November 13, 2018; Accepted: July 9, 2019; Published: August 1, 2019

Copyright: © 2019 Dineen-Griffin et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the paper and its Supporting Information files.

Funding: The authors received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

Introduction

Internationally, healthcare systems are challenged with the rising rates of chronic and complex illness and the clinical and economic burden associated represents a major challenge to the optimal provision of healthcare [ 1 ]. Health systems need to accommodate changes to meet the increasing need for health services. Evidence suggests that leveraging the potential of people to care for themselves and involving patients in decisions affecting their health is beneficial, particularly on the increasing rates of primary care consultations and health system pressures [ 2 ]. A key issue that needs to be addressed is how primary health care professionals (HCPs) can support self-management in an evidence-based, structured way and how self-management processes can be integrated into clinical practice, as models of care evolve to deliver a person-centred approach. Patient participation is suggested to narrow the gap between the dichotomous roles of patient and HCP [ 3 ]. Patient participation involves being engaged in the planning of care and exchanging knowledge, setting own goals and carrying out self-management activities [ 3 ]. This partnership has been suggested as valuable in the support of the management and control of symptoms, particularly for patients with chronic health conditions [ 4 ]. Self-management strategies are increasingly recognized as an essential component of chronic disease management and secondary prevention [ 5 ], individually tailored to patient preferences, prior knowledge and circumstances, supporting patient participation in their care [ 6 ].

Self-management support (SMS) is viewed in two ways: (1) as a portfolio of techniques and tools that help patients choose healthy behaviours, and (2) as a fundamental transformation of the patient-professional relationship into a collaborative partnership [ 7 ]. SMS encompasses more than a didactic, instructional program and goes beyond simple dissemination of information or disease state management. The pivotal objective of SMS is to change behaviour within a collaborative arrangement to produce sustainable effects. This can be achieved by increasing patients’ skills and confidence in managing their disease state through regular assessment of progress and problems, goal setting, and problem-solving support [ 8 ]. Simply put, patients and HCPs work to develop tangible and realistic healthcare goals, while HCPs can assist with the development of the skill set necessary to achieve these goals and monitor for improvements in patient health [ 9 ]. Lorig and Holman [ 10 ] identify a generic set of skills proven successful for effective self-management, including (1) problem-solving; (2) decision-making; (3) resource utilization; (4) forming a patient-health care provider partnership; and (5) taking action. Acquisition of these skills leads to increased self-efficacy. Self-efficacy refers to beliefs in one’s capabilities to execute a behaviour or course of action necessary to reach a desired goal [ 10 , 11 ].

There is a growing body of evidence that shows supporting people to self-manage their health and care can lead to improvements in clinical and humanistic outcomes [ 12 – 18 ], reducing the economic impact of chronic disease and a means of contributing to the sustainability of the global healthcare system. Supporting people to self-manage has resulted in reduced use of general practitioners, reduced admissions to hospital, significant gains in health status and increased symptom control [ 19 , 20 ]. Interventions have targeted patients with arthritis [ 21 ], asthma [ 22 ], chronic heart failure (CHF) [ 23 ], chronic obstructive pulmonary disease (COPD) [ 24 ], type 2 diabetes mellitus (T2DM) [ 25 , 26 ], hypertension (HT) [ 27 ] and patients on oral anticoagulation [ 28 ]. Self-management support interventions vary in the literature with increasing evaluations of peer-led, lay-led, or non-health professional-led, web-based and group-based interventions. For example, the generic Chronic Disease Self-Management Program, a non-health professional group-delivered intervention remains the most widely adopted self-management support program internationally [ 29 ].

Primary HCPs are typically an individuals’ first point of contact with the health system [ 30 ], and are continuing contacts for people with chronic disease. This opens up substantial opportunities to effect sustainable changes through supporting self-management and delivery of more personalized healthcare services. There is an increasing number and uptake of primary care services which require HCPs to be patient-oriented however none of the education provided appears to include any theoretical framework or evidence-based structure for providers to effectively support self-management and facilitate patient behaviour change. Importantly, HCPs need to acquire the competencies not only to identify the techniques and tools for specific patients but to ensure that patients acquire the skills to self-manage. Kennedy et al. recommends a whole systems approach, which integrates SMS at the level of the patient, HCP, and service organizations, which has proven effective in improving outcomes for patients [ 31 ]. Effective implementation is profoundly important to ensure viability and sustainability, and potential scale-up. In some countries, governments have developed health policy and funding alignment for self-management support with the aim of improving health outcomes and alleviating pressures on the wider health system [ 32 ].

While the role of primary HCPs in delivering SMS is highlighted in the literature, there remains a gap in research regarding the specific strategies and active components of interventions used by providers resulting in better health outcomes for patients. A need exists to better understand how these might be delivered within primary care, what outcomes can be achieved, and the training and system changes needed as a result. This gap increases the challenge of providing consistent SMS in primary care, and enabling the appropriate evaluation of SMS trials. Therefore, the objective of this systematic review is to summarize the evidence of effectiveness for SMS interventions delivered face-to-face in primary care practice, and identify evidence-based strategies with active components facilitating positive clinical and humanistic patient outcomes.

A systematic review of randomized controlled trials evaluating SMS interventions was conducted following the Cochrane Handbook for Systematic Reviews of Interventions. We have reported the review according to PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) guidelines [ 33 , 34 ]. Details of the protocol for this systematic review can be found in the PROSPERO international prospective register of systematic reviews database (registration CRD42017062639).

Search strategy

The research question (using PICO) and search strategy were developed and reviewed by three authors (SDG, VGC, SB) to identify studies for this review. In a preliminary scoping search of databases, we as a group of authors identified ten key papers which were suitable to be included in the review. In the multiple search strategies all authors were involved. We tested and refined our strategies as a group, which ensured reproducibility of key papers within search results and a robust search strategy. The detailed search strategy for different electronic databases can be found in S1 Table . A comprehensive search was undertaken in three databases using PubMed, Scopus and Web of Science and search strategies were refined for each individual database. Multiple databases were searched to adequately identify all literature relevant to the research question. Published literature was systematically searched from inception to June 2019. Neither publication date nor publication type filters were used. Citation searching was also conducted to find articles cited by other publications. Searches of grey literature and reference lists of previous systematic reviews complemented our literature search to ensure all relevant studies were captured. The complete results from all databases were imported and managed in a unique EndNote X9 library upon search completion and saved without duplication.

Data extraction, management and synthesis

The review team were responsible for assessing the trials’ eligibility using the methods outlined. The lead reviewer (SDG) screened by title and abstract to select relevant publications. A second and third reviewer (VGC, SB) were consulted throughout this process if an article could not be rejected with certainty. Any disagreement among the reviewers throughout this process were resolved by discussion and consensus. All authors (SDG, VGC, KW, SB) agreed on the final texts for inclusion. Full texts were assessed for eligibility according to inclusion and exclusion criteria. Eligible studies were randomized controlled trials (RCTs) and cluster-randomized controlled trials (c-RCTs) assessing SMS interventions with follow-up, delivered by primary HCPs, face-to-face to adult patients with any condition, compared to usual standard of care. The types of interventions included in the review were multicomponent interventions aimed at supporting patient self-management. Jonkman et al’s definition of SMS interventions was applied for the purposes of selection of interventions for inclusion in this review [ 35 ]. This definition includes the wide range of components considered for ‘self-management interventions’. Self-management interventions are defined as [ 35 ]:

“ Interventions that aim to equip patients with skills to actively participate and take responsibility in the management of their chronic condition . This includes knowledge acquisition , and a combination of at least two of the following : (1) stimulation of independent sign and/or symptom monitoring; (2) medication management; (3) enhancing problem-solving and decision-making skills for treatment or disease management; (4) or changing physical activity , dietary and/or smoking behaviour ”.

Excluded studies were: (1) non-randomized controlled study designs; (2) interventions not meeting Jonkman’s definition of self-management support; (3) interventions not delivered face-to-face (i.e. web-based interventions); (4) group-delivered interventions; (5) study populations under 18 years of age; (6) interventions delivered in settings other than primary care; (7) interventions delivered by non-HCPs (i.e. lay, peer-led); (8) studies without usual standard of care as comparator; (9) studies written in a language other than English or Spanish; or (10) non-primary research articles (i.e. literature reviews, study protocols).

Authors kept a record of the number of trials included or excluded from the review at each stage of the assessment process. Multiple papers of the same study were linked together. Study design, setting, methods, participant characteristics, type of intervention, content, duration and intensity of components, follow up, and study findings were extracted using a tailored data extraction form developed for data retrieval using the Cochrane Handbook for Systematic Reviews of Interventions [ 36 ] and the Cochrane Effective Practice and Organisation of Care Group (EPOC) data collection form [ 37 ] and checklist [ 38 ].

Matrices were developed mapping both evidence and active components for each self-management intervention. Outcome indicators were independently extracted, tabulated and grouped using the following categories of outcome measures, including (1) disease specific indicators; (2) self-efficacy; (3) health-related quality of life; (4) functional status and disability; (5) psychological functioning; (6) disease knowledge; (7) behaviours and self-management activities. Components were categorized according to Jonkman’s definition of SMS interventions [ 35 ], including strategies for: (1) condition or treatment knowledge acquisition; (2) active stimulation of symptom monitoring; (3) self-treatment through the use of an action plan; (4) enhancing resource utilization; (5) enhancing problem-solving and/ or decision-making skills; (6) enhancing stress management or emotional coping with condition; (7) enhancing physical activity; (8) enhancing dietary intake; (9) enhancing smoking cessation; and (10) medication management or adherence. Given the heterogeneity of the studies regarding participants, varying healthcare setting, strategies and outcome measures, no formal quantitative synthesis or meta-analysis could be conducted.

Assessment of risk of bias

The methodological quality of studies were appraised using the ‘Suggested risk of bias criteria for EPOC reviews’ tool in accordance with the Cochrane Handbook [ 39 ]. Domains of bias included in the final assessment, were: (1) random sequence generation; (2) allocation concealment; (3) similarities on baseline outcome measurements; (4) similarities on baseline characteristics; (5) completeness of outcome data; (6) blinding (participants, personnel); (7) protection against contamination; (8) selective outcome reporting; and (9) other risks of bias. Studies were assessed by domain as 'low risk' or 'high risk' of bias. Domains were ‘unclear risk’ if too few details were available to make an acceptable judgement of ‘high’ or ‘low’ risk. A second and third reviewer (VGC, SB) were consulted throughout this process if decisions could not be made with certainty. Any disagreement among the reviewers throughout this process were resolved by discussion and consensus. Three categories of study quality were identified by study authors according to each study’s methodological characteristics. In high-quality studies, the majority of criteria were fulfilled and done well (low risk of bias in at least six criterion), while in low-quality studies, the majority of criteria were not done or done poorly (high risk of bias in at least five criterion); other situations were considered medium quality [ 40 ]. No papers were excluded as a result of quality assessment.

Study selection

6,510 citations were retrieved. After the removal of duplicates, 4,831 records were screened by title and abstract. After review of full texts, fifty-eight RCTs/c-RCTs (reported in 80 citations) fulfilled the review criteria and were included in this systematic review (see flow diagram in Fig 1 ). A completed PRISMA checklist can be found in S2 Table . Descriptive characteristics of individual studies are provided in S3 Table .

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https://doi.org/10.1371/journal.pone.0220116.g001

Description of studies

The included studies originated from 18 countries, predominantly the United Kingdom (UK) and the United States (US). The conditions most frequently targeted included T2DM (37.9%; n = 22), COPD (20.7%; n = 12) and depression (13.8%; n = 8) ( Table 1 ). Settings primarily reported were general practice (48.3%; n = 28), primary care clinics (25.9%; n = 15) and community pharmacies (10.3%; n = 6). Interventions were delivered largely by general practitioners or nurses, commonly specialising in areas such as respiratory, diabetes and mental health. SMS interventions in fourteen studies were delivered in primary care teams involving more than one health care professional from different disciplines (24.1%; n = 14).

https://doi.org/10.1371/journal.pone.0220116.t001

Study outcomes

Ninety-three different outcome measures were adopted by studies. Clinical outcome measures associated with a particular condition were typically reported (e.g. clinical outcomes such as changes in blood pressure or HbA1c levels). Humanistic outcomes sought to measure physical, social and psychological functioning and changes in health-related quality of life (HRQOL). Others captured changes in self-efficacy. Results were classified by outcome and method of assessment (summarised in S4 Table relative to key findings).

Impact of interventions on outcomes

The overall impact of interventions on clinical and humanistic outcomes are illustrated in Table 2 .

https://doi.org/10.1371/journal.pone.0220116.t002

Disease specific outcomes.

Forty four RCTs examined the impact of interventions on disease specific outcomes [ 42 – 57 , 60 , 70 , 71 , 76 , 78 , 79 , 82 , 85 – 87 , 102 , 106 , 107 , 109 , 110 , 112 , 114 , 115 , 118 ]. Disease specific outcomes were most commonly reported in studies evaluating interventions targeting patients with T2DM (e.g. changes in HbA1c, weight, blood pressure and lipids), COPD (e.g. changes in Peak Expiratory Flow (PEF)), courses of antibiotics, oral corticosteroids and frequency of exacerbations), asthma (e.g. PEF, symptoms, inhalation technique, number of exacerbations and nocturnal awakenings), binge eating disorders (e.g. frequency of episodes and purging) and osteoarthritis (OA) (e.g. pain intensity, level of fatigue and use of pain medication). Seventeen studies targeting diabetes reported mean changes in HbA1c, with seven reporting significant improvements in the intervention compared to usual care [ 42 , 46 , 47 , 50 , 52 , 53 , 56 , 109 , 112 ]. Goudswaard et al. [ 42 ] reported a decrease in HbA1c at six weeks by 0.7% more (95% CI 0.1, 1.4) in those receiving the intervention when compared with control. The intervention evaluated by Adachi et al. [ 50 ] for patients with T2DM resulted in a 0.7% decrease in HbA1c at six months in the intervention group (n = 100) compared with a 0.2% decrease in the control group (n = 93) (difference −0.5%, 95% CI: -0.2%, −0.8%; p = 0.004).

Three RCTs reported on the level of asthma control and symptoms [ 80 – 82 ]. Mehuys et al. measured the level of asthma control using the Asthma Control Test (ACT), a clinically validated measure [ 81 ]. While mean ACT scores did not change from baseline for both study groups, a subgroup analysis of patients having insufficiently controlled asthma at baseline showed the intervention group had significantly increased ACT scores after six months (mean ACT change from baseline in the intervention group was +2.3 and +0.3 in the control group (mean difference 2.0, 95% CI: 0.1, 3.9; p = 0.038). The need for rescue medication was reduced in both groups from baseline, however a significantly higher reduction in the intervention group (-0.56 and -0.57 inhalations per day at three and six-month follow-up, respectively) was reported against control (-0.03 and -0.43 inhalations per day at three and six-month follow-up, respectively; p = 0.012) [ 81 ]. Six studies reported on COPD-specific outcomes [ 64 , 65 , 68 – 71 , 111 ]. McGeoch et al. [ 64 ] reported no significant change in St. George’s Respiratory Questionnaire (SGRQ) as the primary outcome measure. The intervention also showed no effect on self-reported outcomes including the frequency of use of antibiotic courses and oral corticosteroids over 12 months [ 64 ].

Interventions targeting eating disorders were evaluated in four RCTs [ 41 , 92 , 93 , 97 , 103 , 117 ]. Banasiak et al. [ 97 ] explored primary outcome measures of eating pathology derived from the Eating Disorder Examination Questionnaire (EDE-Q). Intention-to-treat (ITT) analyses revealed significant improvements in psychological symptoms at the end of the intervention compared with control, reduction in mean frequency of binge-eating episodes by 60% in intervention and 6% in control, and remission from all binge-eating and compensatory behaviours in 28% of the intervention and 11% of control. Treatment gains were maintained at three and six-month follow-up [ 97 ].

An intervention targeting patients with OA measured primary outcomes of pain intensity, physical functioning, self-efficacy, psychological distress, use of pain coping strategies, catastrophizing and HRQOL [ 84 ]. ITT analyses were performed on primary outcomes at baseline, post-treatment, 6 and 12 month follow-up which yielded significant group differences, indicating improvement in pain intensity (F(3,233) = 2.75, p = 0.044), physical functioning (F(3,233) = 3.11, p = 0.027), psychological distress (F(3,233) = 2.83, p = 0.039), use of pain coping strategies (F(3,233) = 4.97, p = 0.002), and self-efficacy (F(3,232) = 10.59, p< 0.001) in intervention, compared with control. All outcomes, except for self-efficacy, were maintained at 12-month follow-up while effects on self-efficacy degraded over time [ 84 ].

Health-related quality of life.

Twenty-four RCTs examined the impact of interventions on HRQOL [ 31 , 54 , 56 , 57 , 60 , 61 , 64 – 66 , 69 , 71 , 73 , 74 , 76 , 81 – 84 , 90 – 92 , 94 , 96 , 98 , 101 , 102 , 108 , 113 , 117 ]. The method of assessment varied and included general HRQOL questionnaires such as the SF-12 survey questionnaire and EuroQoL EQ-5D questionnaire. Disease specific QOL measures were also identified including the Arthritis Impact Measurement Scales Short Form questionnaire (AIMS2-SF) [ 119 ], Irritable Bowel Syndrome Quality of Life Questionnaire (IBSQOL) [ 120 ], Audit of Diabetes Dependent Quality of Life (ADDQOL) [ 121 ] and the standardised Asthma Quality of Life Questionnaire (AQLQ) [ 122 ]. Eight studies reported significant improvements in HRQOL [ 56 , 66 , 71 , 82 , 90 – 92 , 96 , 113 , 117 ]. Efraimsson et al. [ 66 ] evaluated the effects of COPD self-management delivered at a nurse-led primary health care clinic. HRQOL, measured using the SGRQ, was improved by an average value of 8.2 units (from 30.6) in the intervention group, whereas no change was noted in control. Differences between groups were clinically relevant and statistically significant (p = 0.00030) [ 66 ]. Heitkemper et al. [ 91 ] examined the effect of an IBS SMS intervention on HRQOL using the Irritable Bowel Syndrome Quality of Life questionnaire (IBSQOL), a 30-item questionnaire. Compared to usual care, participants receiving the intervention demonstrated statistically significant improvements in QOL, increasing by 10.6 units, 12.8 units and 12.2 units at nine weeks, six and twelve-months, respectively. Changes persisted at 12-month follow-up (p<0.001) [ 91 ].

Physical, psychological or social functioning.

Physical, mental or social functioning were measured in 25 RCTs [ 31 , 43 , 44 , 47 , 54 , 56 – 58 , 60 – 64 , 68 , 72 – 76 , 79 , 84 – 97 , 100 , 102 , 108 , 111 – 115 , 117 ]. Psychological symptoms and social functioning using the CORE-OM scale [ 123 ] were measured in three studies [ 74 , 75 , 100 ]. Psychological functioning was measured using the Beck Depression Inventory (BDI) and Beck Depression Inventory-II (BDI-II) scale [ 124 ] in eight studies [ 72 , 75 , 84 , 92 – 94 , 97 , 100 , 108 , 117 ]. Williams et al. [ 75 ] reported lower mean BDI-II scores in the intervention group at four months (2.6 to 7.9; mean difference 5.3 points, p<0.001). At twelve-month follow-up, there were also significantly higher proportions of participants achieving a 50% reduction in BDI-II in the intervention arm compared to control [ 75 ]. The Problem Areas in Diabetes Scale (PAID), a brief self-report scale [ 125 ], was used to evaluate diabetes-related distress. Sturt et al. [ 44 ] reported a reduction by 4.5 points in mean PAID scores at follow-up (95% CI: −8.1, −1.0), indicating lowered diabetes-related distress after a nurse-delivered intervention compared with control (p = 0.012), however this difference was considered a small effect [ 44 ]. Physical functioning was assessed with the SF-36PF scale [ 126 ] by Friedberg et al. [ 94 , 108 ] evaluating a chronic fatigue self-management intervention. No significant changes in scores by time, treatment group, or diagnostic group were revealed (p>0.05) [ 94 , 108 ].

Patient self-efficacy.

Self-efficacy was assessed using a number of validated instruments including the General Self Efficacy Scale (GSES-12) [ 127 ], Diabetes Management Self Efficacy Scale (DMSE) [ 128 ] and the Arthritis Self Efficacy Scale (an eight item scale measuring patients’ perceived ability to perform specific behaviours aimed at controlling arthritis pain and disability) [ 129 ], the COPD self-efficacy scale (CSES) [ 130 ], among others. Self-management and patient enablement were measured by the Patient Enablement Instrument (PEI) [ 87 ]. Changes in perceived self-efficacy were reported in 14 studies [ 31 , 44 , 54 , 57 , 68 , 69 , 73 , 76 – 78 , 84 , 87 , 98 , 99 , 102 , 104 , 110 , 111 , 116 ]. Sturt et al. showed self-efficacy scores were 11.2 points higher on the DMSE (95% CI: 4.4, 18.0) in the intervention group compared with the control group following a structured intervention delivered by practice nurses in the UK (p = 0.0014) [ 44 ]. Broderick et al. [ 84 ] reported significant improvement in self-efficacy (F(3,232) = 10.59, p = 0.001) following a nurse-practitioner delivered intervention for OA patients, however this was not maintained at 12-month follow up (p = 0.158). Seven RCTs reported non-significant improvements in self-efficacy [ 54 , 57 , 59 , 68 , 69 , 77 , 78 , 98 , 102 , 105 , 110 , 111 , 116 ]. Bischoff et al. found no statistically significant changes in CSES scores at 24 months [ 69 ]. Smit et al. [ 77 , 116 ] assessed self-efficacy in controlling depressive symptoms and preventing future episodes, using the Depression Self-Efficacy Scale (DSES) [ 131 ]. No statistically significant differences between groups were revealed at 12-month follow-up [ 77 , 116 ]. Eikelenboom et al. reported no significant difference in PAM-13 scores (measure of patient activation [ 132 ]) between control and intervention arms at six-month follow-up [ 59 , 105 ].

Self-management behaviours.

Behaviours commonly measured were diet, physical activity, medication adherence and smoking. Five studies reported on level of physical activity [ 41 , 59 , 83 , 88 , 103 , 105 ]. A range of measures included the International Physical Activity Questionnaire short form (IPAQ-SF) [ 133 ], Rapid Assessment of Physical Activity questionnaire (RAPA) [ 134 ] and The Physician-based Assessment and Counselling for Physical Activity (PACE) questionnaire [ 135 ]. No significant between group differences were reported for physical activity in 4 RCTs [ 41 , 59 , 65 , 83 , 103 , 105 ]. There was evidence in one study to suggest self-reported exercise participation was higher 1-week post-intervention (p<0.001) however differences were no longer significant at seven-week follow-up [ 88 ]. Self-care activities within 7 days were measured in 4 RCTs [ 41 , 52 , 54 , 60 , 102 , 103 ] using the Summary of Diabetes Self-Care Activities (SDSCA) questionnaire, a brief self-report instrument for measuring levels of self-management in diabetes (‘general diet’, ‘specific diet’, ‘physical exercise’, ‘foot care’ and ‘smoking’) [ 136 ]. Mehuys et al. reported significant improvements in self-management activities in the domains of ‘specific diet’ (+0.5 day/week, p = 0.008), ‘physical exercise’ (+0.4 day/week, p = 0.006), and ‘foot care’ (+1.0 day/week, p<0.001) for intervention patients. There were significant between-study group differences in the domains ‘physical exercise’ (p = 0.045) and ‘foot care’ (p<0.001), however the between-group difference for ‘specific diet’ were non-significant [ 52 ].

Disease knowledge.

Nine studies reported disease knowledge as an outcome [ 52 , 66 – 68 , 71 , 81 , 82 , 88 , 93 , 111 ]. Two RCTs [ 67 , 68 , 111 ], measured COPD disease knowledge using the Bristol COPD Knowledge Questionnaire (BCKQ) [ 137 ]. Hill et al. reported the results of the BCKQ for each domain in both groups. Compared with baseline measures, the total Bristol COPD knowledge Questionnaire score increased from 27.6 ± 8.7 to 36.5 ± 7.7 points (p<0.001) in the intervention group, and unchanged in the control group (29.6 ± 7.9 to 30.2 ± 7.2; p = 0.51) [ 67 ].

Intervention components and theoretical underpinnings

Each of the studies described interventions including multiple core components (see S5 Table for full component breakdown). Providing knowledge about the condition or treatment (100%; n = 58), enhancing patients role in making lifestyle changes (71.9%; n = 41), development of a self-management or action plan (45.6%; n = 26), keeping logs of self-monitoring (43.9%; n = 25), strategies for psychological coping with conditions (43.9%; n = 25), enhancing problem-solving and/or decision-making skills (42.1%; n = 24) and medication adherence or management (36.8%; n = 21) were most prominently detected ( Table 3 ). Interventions targeting heart disease, irritable bowel disease (IBD) and asthma reported the highest number of self-management components. Self-treatment through the use of an action plan, enhancing medication adherence and smoking cessation components were frequently seen in studies evaluating interventions targeting COPD. Similarly, SMS components targeting T2DM commonly included strategies to stimulate symptom monitoring, making positive lifestyle improvements with physical activity or dietary improvements. In contrast, interventions for depression included components focusing on patients’ role in managing stress, problem-solving and strategies for coping with conditions.

https://doi.org/10.1371/journal.pone.0220116.t003

Overall, sixteen studies explicitly reported a theoretical framework underpinning the intervention (28.1%; n = 16) including Cognitive Behavioural Theory (17.5%; n = 10) [ 58 , 74 , 75 , 84 , 90 – 94 , 100 ], Social Cognitive Theory (3.5%; n = 2) [ 79 , 104 ], Prochaska and DiClementes’ Transtheoretical model of the Stages of Change (3.5%; n = 2) [ 51 , 55 , 66 , 82 ], Social Learning Theory (1.8%, n = 1) [ 44 ], Normalization Process Theory [ 31 ] and Implementation Intention Theory (1.8%; n = 1) [ 104 ]. Intervention fidelity was reported in 21 studies (27.6%; n = 16).

Training of primary care provider to deliver SMS.

70.7% (n = 41) of studies included upskilling of HCPs to deliver the intervention. Training aimed at enhancing aspects of patient self-efficacy including mastery achievements, positive learning, adjustment to stress, verbal encouragement and outcome expectations. Intervention approaches were underpinned by the use of core communication skills to build trust and rapport in the patient-provider relationship, and as such providers were trained in areas including active listening, non-verbal communication, reflection, empathy and affirmation. Studies reported the provision of HCP resources to support self-management, e.g. written material or manuals, feedback on care reports, video demonstrations or case studies, and tools to assess patient support needs and priorities (PRISMS).

Interventions reporting positive findings for clinical and humanistic measures

Thirteen RCTs targeting a range of conditions including asthma, T2DM, COPD, recurrent binge eating, chronic fatigue, major depression, low self-esteem, IBS and depression reported positive findings for all clinical and humanistic outcome measures ( Table 4 ) [ 42 , 66 , 67 , 72 , 75 , 80 , 91 , 92 , 95 , 100 , 117 ].

https://doi.org/10.1371/journal.pone.0220116.t004

A mean of five self-management components (SD 1.7) were included in effective interventions. Elements most frequently reported to enhance the patient’s role in self-management included information provision (100.0%; n = 13), enhancing problem-solving or decision-making skills (76.9%; n = 10), active stimulation of symptom monitoring (46.2%; n = 6), medication management or adherence (46,2%; n = 6), strategies for stress or psychological management of condition (46.2%; n = 6) or enhancing dietary intake (46.2%; n = 6). The total duration of interventions ranged from 4 to 52 weeks. Initial consultations were on average 62 minutes (SD 13.8). Follow-up was delivered face-to-face in 11 interventions (84.6%; n = 11), and two studies reported telephone follow up (15.4%; n = 2). Studies reported mean of five follow-up sessions (SD 3.6) on average, ranging from 1 to 12 sessions. Mean duration of follow up sessions were 57 minutes (SD 18.5). Individuals were provided self-help support materials or resources in majority of interventions (92.3%; n = 12). Accompanying patient materials provided in addition to face-to-face sessions included manuals, information or educational booklets to work through at home, personalized treatment or action plans, devices and diaries for self-monitoring, goal setting forms or individualized dietary plans. Six RCTs incorporated a theoretical underpinning in their intervention: cognitive behavioral theory (30.8%; n = 4) and Prochaska and DiClementes’ transtheoretical model of the stages of change (15.4%; n = 2). Five integrated cognitive behavioral therapy (CBT) into their intervention (38.5%; n = 5).

Barbanel et al. [ 80 ] and Goudswaard et al. [ 42 ] targeted asthma and T2DM respectively and produced positive improvements in clinical outcomes. The SMS intervention evaluated by Barbanel et al. [ 80 ] examined the impact of a self-management program delivered by community pharmacists on asthma control. Intervention participants received self-management support from the pharmacist with weekly telephone follow-up for 3 months. This included a review of inhaler technique, skills including monitoring of peak flow, and a personalized action plan for worsening symptoms or exacerbations. Symptom scores improved in the intervention group and marginally worsened in the control group to 20.3 (4.2) and 28.1 (3.5), respectively (p<0.001; adjusted difference = 7.0 (95% CI: 4.4, 9.5). Goudswaard et al. [ 42 ] evaluated long-term effects of nurse-delivered self-management education in type 2 diabetics. The intervention focused on medication adherence, enhancing physical exercise, dietary intake and self-monitoring blood glucose at home. Six sessions were provided at intervals of 3–6 weeks, resulting in contact time of approximately 2.5 hours with HCPs over 6 months. HbA1c levels improved from 8.2% to 7.2% in the intervention group and 8.8% to 8.4% in usual care at 6 weeks, however this result was not sustained at 18 months [ 42 ].

Efraimsson et al. [ 66 ] examined effects of nurse-led COPD intervention. Patients received education on self-care ability to cope with disease and treatment. Patients were scheduled for two visits with nurses lasting 60 minutes during a 5-month period. A statistically significant increase was noted in the intervention group on QOL, the proportion of patients who ceased smoking, and patients’ knowledge about COPD at 3–5 month follow up, compared with usual care. Heitkemper et al. [ 91 ] examined an intervention delivered to women with IBS. Women in the intervention received eight weekly 1-hour individual sessions. The intervention included education, dietary counselling, symptom monitoring, relaxation training and cognitive-behavioral strategies including anger management, cognitive restructuring, assertiveness and social skills training [ 91 ]. Hill et al. [ 67 ] examined an intervention in people with COPD. Intervention participants attended two one-to-one 60-minute sessions, focusing on enhancing self-efficacy. Sessions were accompanied by a written manual adapted from the "Living Well with COPD" program. COPD knowledge increased from 27.6 (+/- 8.7) to 36.5 (+/- 7.7) in the intervention group, which was greater than any difference seen in the control group. Waite et al. [ 100 ] examined an individualized intervention for patients with low self-esteem. This included goal setting, learning skills to re-evaluate anxious and self-critical thoughts and beliefs through cognitive techniques. All participants were given a three-part self-help workbook in addition to individual treatment sessions. The intervention showed significantly better functioning than control on measures of overall functioning and depression and had fewer psychiatric diagnoses at the end of treatment. All treatment gains were maintained at follow-up assessment. Williams et al. [ 75 ] evaluated a guided self-help intervention for depression in primary care. The first appointment focused on an introduction to the use of the self-help materials. Three additional face-to-face support sessions of approximately 40 minutes were provided on a weekly or fortnightly basis. Mean Beck Depression Inventory (BDI-II) scores were lower in the intervention group at 4 months by 5.3 points, compared with control (2.6 to 7.9, p = 0.001). There were also significantly higher proportions of intervention participants achieving a 50% reduction in BDI-II scores at 4 and 12 months.

McLean et al. [ 82 ] involved a pharmacist-delivered intervention for asthma self-management. The intervention involved education surrounding the basic concepts of disease, medications, trigger identification and avoidance, and an asthma action plan. Patients were taught to use a peak flow meter, spacer devices, calendars/diaries were provided and asked to record peak expiratory flow rates (PEFRs) regularly for the course of the study period. Patients received appointments of approximately one hour in length with a pharmacist in a private counselling area every two to three weeks for at least three appointments, and then follow-up appointments at least quarterly for 12 months [ 82 ]. Symptom scores decreased by 50% (p<0.05) and peak flow readings increased by 11% (p = 0.0002) for intervention patients, compared to those receiving usual care. Chalder et al. [ 95 ] evaluated the efficacy of a self‐help booklet and advice delivered by a nurse in reducing chronic fatigue in adult patients. The intervention reiterated self-monitoring and maintaining symptom diaries. Basic cognitive techniques such as identifying and challenging unhelpful thoughts were also introduced. The self‐help group showed significantly greater improvements in fatigue (p = 0.01) and psychological distress (p<0.01) than controls. Striegel-Moore et al. [ 92 , 117 ] evaluated cognitive behavioural guided self-help for the treatment of recurrent binge eating. Intervention participants received 8 sessions over 12 weeks. The primary focus of this intervention was on developing a regular pattern of moderate eating using self-monitoring and problem-solving. The main outcome, abstinence from binge eating differed significantly between the groups: the initial improvement in abstinence from baseline was greater for the intervention group than usual care (p<0.001). Watkins et al. [ 72 ] evaluated guided self-help concreteness training as an intervention for major depression. During the initial session of the self-help intervention, psycho-education and training exercises were provided. During the follow-up telephone sessions, feedback, guidance and encouragement was provided to ensure accurate use of exercises, and progress monitored. The intervention resulted in significantly fewer depressive symptoms post-treatment, relative to treatment as usual (ITT, p = 0.006, effect size d for change in Hamilton Rating Scale for Depression (HAMD) = 0.76; PP, p<0.0001, d = 1.06).

Quality risk of bias assessment of individual studies

The overall methodological quality was considered high (lower risk of bias) in 41.4% of studies (n = 24 RCTs), and of medium quality in 58.6% of studies (n = 34 RCTs). The domains considered lowest risk of bias were selective reporting (96.6%; n = 56), baseline outcome measures (84.5%; n = 49), random sequence generation (79.3%; n = 46) and baseline characteristics (79.3%; n = 46). The domains with higher risk of bias were ‘blinding of outcome assessment’ (25.9% of studies; n = 15). Reporting bias was judged low for more than 95% of studies. Half of studies (51.7%; n = 30) presented low risk for the domain ‘other bias’. Reasons for other risk of bias included not meeting recruitment targets for assumed power. Fig 2 shows aggregate appraisal of risk of bias of included studies and visual representation of each domain.

https://doi.org/10.1371/journal.pone.0220116.g002

This systematic review has synthesized evidence from 58 randomized controlled trials examining the effectiveness of primary HCP delivered self-management support interventions for adult patients, with any condition, compared to usual standard of care. We describe effective SMS interventions and have highlighted their active elements, identified trends in combinations of intervention strategies, range of outcomes measured and the magnitude of effect size. This review demonstrates that SMS interventions delivered face-to-face by primary HCPs, which are multicomponent and tailored to explicitly enhance patient self-management skill set can lead to improvements in clinical and humanistic outcomes. The various tools and strategies that provide a structure to interventions delivered face-to-face include adapting interventions according to patients’ readiness to change, action planning and goal setting by collaboratively breaking down individual health goals into small achievable actions. The effectiveness of multicomponent SMS interventions is not surprising. But it raises the question of how to focus efforts on the best combination of active components within interventions. The variation in context, outcome measures, training methodology used across the 58 studies, in addition to the high degree of autonomy given to providers, deem the evaluation of SMS interventions more difficult.

Ninety-three different outcome measures were adopted to demonstrate evaluated impact of the various interventions and presumably were selected to reflect expected outcomes or processes of self-management. These include different measures of health-related quality of life, overall functioning, self-efficacy, health behaviours, disease knowledge, symptoms and disease control. Disease specific clinical indicators were mostly included as primary outcomes, and QoL indicators generally served as secondary or ancillary outcomes to primary outcome criteria. Generic HRQOL measures varied across different types of diseases, interventions and groups (i.e. EQ5D, SF-12), and specific HRQOL disease measures were also utilized. (i.e. IBSQOL questionnaire was used to measure changes in HRQOL for IBS patients). Further examination of studies producing positive improvements in HRQOL revealed use of disease specific measures (i.e. Ferrone et al. [ 71 ] reported positive changes in HRQOL using the Clinical COPD Questionnaire (CCQ)—a 10-item, health-related quality of life questionnaire). Interestingly, studies using more generic HRQOL measures (i.e. EQ5D, SF scales) mostly reported insignificant differences in their interventions. S4 Table provides a summary of the various instruments used in studies.

Our findings reveal a structured patient-provider exchange is required in primary care (including a one-on-one patient-provider consultation, ongoing follow up and provision of self-help materials). A systematic and tailored patient-primary care provider exchange is needed to provide individuals with the portfolio of techniques and tools to effectively self-manage. Various combinations of strategies were used to achieve this and adapted to the individuals’ condition, health literacy, skills and confidence in managing their own health. Strategies containing several interacting components and varying dimensions of complexity produce favourable effects when tailored to the individual. No one intervention solution is suitable for all patient groups and the selection of combinations of strategies should support patients’ needs relevant to both primary care and HCP. The strategy of enhancing the patient’s decision-making skills or ability to problem-solve was reported in the highest percentage of studies (53.8%) with positive results, after knowledge acquisition. Active stimulation of symptom monitoring (46.2%) and having specific, clear and accepted treatment or healthcare goals was also commonly identified. This involved setting measurable, clear and accepted treatment or healthcare goals on a per patient basis with a specific action or self-management plan detailing these. Tailored, written information and care plans that are mutually agreed upon have previously been identified as helpful [ 138 ]. Strategies to improve responsibility in medication adherence and lifestyle choices were also reported within effective interventions.

Interestingly, strategies for stress or psychological coping of conditions (46.2%) were commonly identified in effective interventions. Changing the patient’s cognitive approach to their illness was commonly incorporated into the intervention to deal with the physical and emotional symptoms resulting from a chronic illness. Effective interventions integrated cognitive behavioral therapy (CBT) into the intervention in 40% of studies. Multiple cognitive strategies were raised, such as identifying and challenging unhelpful thoughts [ 95 ], relaxation training and cognitive-behavioral strategies including anger management, cognitive restructuring, assertiveness and social skills training [ 91 ]. A 2014 systematic review of qualitative literature identified patients often express difficulties in dealing with the physical and emotional symptoms of their chronic conditions [ 138 ]. As such, undesirable physical and emotional symptoms and impaired physical functioning can directly prevent patients from carrying out normal daily activities, including tasks required to appropriately and successfully self-manage [ 139 – 141 ]. Self-management of chronic conditions should therefore be examined not only from the clinical perspective, but also the patient perspective with a focus on humanistic outcomes. Importantly, the theory of SMS drawn for effective studies included Cognitive Behavioral Theory and Prochaska and DiClementes’ transtheoretical model of the stages of change. Follow-up by HCPs included tailored feedback, monitoring of progress with respect to patient set healthcare goals, or honing problem-solving and decision-making skills. Self-help tools and assistance with locating resources were commonly provided during the patient-provider exchange.

The scope of the terms ‘self-management’, ‘self-management support’ and ‘self-management support interventions’ in literature and the large heterogeneity in terminology has repeatedly been highlighted in previous systematic reviews and meta-analyses [ 27 , 142 – 144 ]. This is a key limitation, as very broad or very narrow definitions of what constitutes “self-management support” have been applied. Lorig and Holman [ 10 ] previously underlined the need to explore interventions beyond the label of self-management to define if interventions actually address the necessary support strategies required to change behaviour. Subtle variations in self-management definitions can result in substantial differences in selected studies. Using Jonkman’s operational definition [ 35 ] to define our interventions has shown highly important in distinguishing self-management interventions from other types of interventions (ie. patient education or disease management) without being too restrictive. The definition clearly defines the elements or strategies that constitute a self-management support intervention, with the pivotal objective of changing behaviour. This has guided the selection of studies on which our review conclusions have been based.

A notable gap identified in the literature was a lack of focus on multimorbidity. This is understood to pose challenges for self-management, as many individuals have more than one health condition [ 138 ]. The effects of multimorbidity on a person are not always linear. Interestingly enough, some studies have found that patients with multimorbidity consider themselves better at self-management because they had already developed skills such as self-monitoring and self-advocacy [ 145 ].

In acknowledging that SMS is a multidimensional topic, we aimed to create a broader picture of the landscape of SMS in primary care. This was achieved by evaluating the patterns of intervention components comprehensively across all conditions, by not limiting our research to a clinical condition, or specific intervention strategies. Although including different clinical conditions in the review may be considered as a drawback due the potential heterogeneity induced, in our research, there was a clear distinction of strategies across the conditions studied. Findings from this review add further detail to this body of knowledge, while providing HCPs with a number of evidence-based strategies that can be utilized in practice. These findings pave the way to explore further SMS strategies targeting patient’s behaviour change, effective patterns of strategies, and develop a more evidence-based model for optimum SMS service design. Primary care providers (e.g. general practitioners, nurses, pharmacists) can play a foundational role in supporting patient self-management, especially for people with multiple chronic conditions. Fig 3 sets the foundation for an evidence-based SMS primary care model for face-to-face interventions, allowing for a more efficient and effective process to evaluate and implement SMS interventions in primary care.

Modelled on the definition of self-management interventions by Jonkman et al. 2016 [ 35 ].

https://doi.org/10.1371/journal.pone.0220116.g003

For this collaborative partnership approach to be more widely applied, there should be a strong focus on upskilling primary care providers to deliver SMS strategies in health care, which are both integrated and coordinated to improve the patient-provider encounter in practice [ 5 ]. The total duration of the intervention and the correlation of intervention duration with the number of strategies delivered are important aspects when considering the sustainability within primary care. Policy and funding alignment will also be a major determinant for future sustainability. Therefore, we must determine where the best compromise in SMS interventions lie for cost-effective and resource-limited approaches. Future high-quality evaluations of consistent interventions will be of value to practitioners, policy-makers and researchers in terms of collecting clinical, humanistic and economic outcome measures to generate a robust evidence base of primary care providers impact in the area. This will also allow determination of ineffective combinations of strategies.

Future research efforts should continue to expand on this landscape to (1) examine the patterns of strategies within effective multicomponent interventions for various conditions; (2) examine the weighting of each strategy (ie. determine intervention components which are more or less effective) within effective multicomponent interventions; (3) determine if certain types of patient populations could be targeted most effectively by certain combinations of strategies; (4) develop a core SMS outcome set in primary care; (5) examine the patient’s ability to self-manage over time as well as aiming to achieve the goal of long-term sustainability for improved self-management; and (6) determine training requirements for the upskilling of health care providers for sustained patient behaviour change.

Furthermore, sustainability of improved SMS first requires an understanding of the implementation of SMS enhancing interventions [ 146 ]. Sustainability can be challenging if not embedded into everyday clinical practice [ 31 ], and achieving the potential of primary care as a platform to effectively deliver SMS and achieve the stated outcomes means overcoming known barriers, such as limited time, skills and confidence among health professionals [ 31 , 147 ]. We know changes in health care professional practice requires exhaustive planning and testing to increase the probability that they are successfully and sustainably implemented. The adoption of Intervention Mapping has been widely used in health care settings to plan changes in the behaviour and practice of health care professionals, and should be applied to ensure SMS interventions are both effective and successfully implemented in practice [ 148 ].

There are limitations to this review. A number of studies did not report sufficient detail to their interventions which hampered the assessment of possible effective combinations of strategies being evaluated. The methodological quality domains of the included trials were in a lot of cases unclear, with a lack of poor description of the study methodology and intervention fidelity in evaluations. This was mitigated by contacting authors for further relevant information, searching for study protocols or further examining supplementary data online. With the growing recognition of the importance of assessing treatment fidelity in multicomponent interventions [ 149 – 151 ] (ie. compliance to treatment protocols by HCPs, or compliance to treatment by patients), it is important to note most trials (72%) did not include this in their design and few provided data on treatment fidelity to the intervention. Only 38% of effective interventions reported an assessment of intervention fidelity. The methodological quality domains of the included trials were in a lot of cases unclear. Four high-quality studies provided positive evidence that SMS interventions delivered in primary care dominate usual standard of care, by improving patients’ clinical outcomes, HRQOL or psychological functioning [ 72 , 91 , 92 , 100 ]. Similar trends have been found in existing literature in several contexts that self-management is essential to optimizing clinical and humanistic outcomes for patients with chronic conditions [ 13 , 15 , 18 , 152 – 155 ].

Although multiple databases were extensively searched using clear, specific and appropriate terms, the search may not have yielded all published relevant studies given the ambiguity of what constitutes “self-management support” and the variation in terminology for “self-management” identified in the literature. Unsurprisingly, with the rising burden of chronic disease, the nomenclature of “self-management” has become more prevalent in both published and grey literature. We recognize the use of different search terms and definitions to guide the development of the search strategy may lead to variation in the identification of studies, and affect a review's conclusions. This is identified as a limitation of our review. Search terms were sourced from previous systematic reviews, primary studies and grey literature. Our search included general terms for “self-management” and was not limited to specific illnesses or outcomes.

Systematic reviews are at risk for bias from a number of sources [ 156 ]. We sought to reduce potential sources of bias within the inclusion and synthesis of studies. One of our main goals was developing inclusion criteria to minimize ambiguity and reduce bias in study selection decisions. We have defined our inclusion and exclusion criteria by PICO clearly and have documented and reported all decisions made in the study selection process for transparency. Since we restricted our review to face-to-face interventions, there may be other SMS interventions that may be effective that are not covered by this review. We decided to categorize the comparator as usual standard of care and understand the definition of usual standard of care may vary by country or healthcare system.

In conclusion, this review highlights core components of successful interventions showing positive clinical and/or humanistic outcomes. Whilst it was difficult to directly correlate individual strategies to outcomes and effectiveness, there was a clear distinction of strategies across the conditions studied. This review provides encouraging groundwork for the design and evaluation of practical strategies for evidence-based practice and the construction of self-management support processes in primary healthcare practice. This review may assist in determining the breadth and focus of the support primary care professionals provide. Application of a theoretical perspective provides a strong base for the development of SMS interventions. The developed model sets the foundation for the design and evaluation of practical strategies for the construct of self-management support in primary healthcare practice. These results may be used to justify additional research investigating self-management interventions delivered in the primary care setting. In response, primary care providers can begin to deeply reflect on current practice and become involved in a dialogue to improve self-management support. Critically, these results should stimulate informed discussion for the future delivery of self-management support in primary care and the requirements for upskilling healthcare providers to effectively support patients in this collaborative process.

Supporting information

S1 data. database..

https://doi.org/10.1371/journal.pone.0220116.s001

S1 Table. Search strategy.

https://doi.org/10.1371/journal.pone.0220116.s002

S2 Table. PRISMA checklist.

https://doi.org/10.1371/journal.pone.0220116.s003

S3 Table. Descriptive characteristics of included studies.

https://doi.org/10.1371/journal.pone.0220116.s004

S4 Table. Summary of findings and extracted outcomes.

https://doi.org/10.1371/journal.pone.0220116.s005

S5 Table. Mapping of intervention components.

https://doi.org/10.1371/journal.pone.0220116.s006

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• Volume 14, Issue 8
• Self-management interventions among community-dwelling older adults with type 2 diabetes mellitus: a scoping review protocol
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• http://orcid.org/0000-0002-6015-8702 Shashank Mehrotra 1 ,
• Sutanuka Bhattacharjya 2 ,
• http://orcid.org/0000-0002-3210-2293 Ranjitha S Shetty 3
• 1 Department of Occupational Therapy , Manipal College of Health Professions,Manipal Academy of Higher Education , Manipal , Karnataka , India-576104
• 2 Department of Occupational Therapy , Byrdine F. Lewis College of Nursing & Health Professions, Georgia State University , Atlanta , Georgia , USA
• 3 Department of Community Medicine , Kasturba Medical College, Manipal, Manipal Academy of Higher Education , Manipal , Karnataka , India -576104
• Correspondence to Dr Ranjitha S Shetty; ranjitha.shetty{at}manipal.edu

Background Globally, the number of older adults is increasing rapidly; simultaneously, there is an epidemiological shift toward chronic diseases. One such chronic disease is type 2 diabetes mellitus (DM) which is caused either by the inability to produce insulin or due to the ineffective use of insulin. In recent years, self-management programmes for chronic conditions have gained importance, especially among occupational therapists. Though there is an increasing focus on ‘self-management interventions’ among older adults, there is still a lack of such interventions for older adults with type 2 DM in low- or middle-income countries (LMICs).

Objectives Summarise the existing literature on self-management intervention programmes for community-dwelling older adults with type 2 DM; identify the principles, practices and criteria that define a self-management intervention programme for community-dwelling older adults with type 2 DM in LMICs.

Methods This present study will be a scoping review, combining quantitative and qualitative literature with a parallel results convergent synthesis design. The synthesis applies to analysing existing principles and practices that influence the selection and application of ‘diabetes self-management intervention’ among older adults in community settings with type 2 DM in LMICs.

Ethics and dissemination As a secondary analysis, this scoping review does not require ethics approval. The final review results will be submitted for publication in a peer-reviewed journal in the rehabilitation, diabetes, occupational therapy or health promotion-related fields. Other dissemination strategies may be an oral presentation at international conferences or through various social media networks.

• diabetes & endocrinology
• rehabilitation medicine
• health education
• primary health care

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See:  http://creativecommons.org/licenses/by-nc/4.0/ .

https://doi.org/10.1136/bmjopen-2024-084743

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Strengths and limitations of this study

This scoping review will follow the Joanna Briggs Institute’s methods and undertake a comprehensive database and additional resources search, such as searching for reference checking of the included studies.

The study will include, analyse and present quantitative and qualitative research results related to self-management intervention programmes.

Being a scoping review, assessing the quality of the published studies included in the review may not be feasible.

Introduction

Globally, the number of older adults is increasing rapidly; simultaneously, there is an epidemiological shift toward chronic diseases. These diseases usually have extended periods and result from hereditary, physiological, ecological and behavioural factors. 1 One such chronic disease is type 2 diabetes mellitus (DM) which is caused either by the inability to produce insulin or due to the ineffective use of insulin. 2

The global prevalence of DM is projected to increase to 10.2% by 2030 and 10.9% by 2045 with nearly 50.1% of people living with diabetes being undiagnosed. 3 The prevalence of DM in India’s urban and rural areas has increased significantly over the years with 15.0% to 19.0% in urban areas and from 2.4% to 3.3% in rural areas during 2015–2019. 4–6 In 2019, India had the second-highest prevalence of diabetes globally with 77 million diabetic adults and the number of affected individuals is rapidly increasing. 3 The prevalence of DM in India is estimated to be 16.1% with 27.5% of them being aware, 21.5% receiving treatment and 7% having their glucose levels in control. 6

The prevalence of type 2 DM is increasing among older adults with more than half of them being prediabetics which leads to various functional impairments and comorbidities. 7 8 It has increased significantly in nearly all countries and may be considered an epidemic. 9 Globally, it was estimated that 19.3% of older adults aged 65 years and above live with DM. Further, as projected, the number of older adults with diabetes will reach 195.2 million by 2030 and 276.2 million by 2045. 3 Older individuals with DM are more likely to have functional decline 10 and decreased quality of life. 11 Low disease awareness, financial and social inequality and dependence in old age and less utilisation of public healthcare services amplify the disease burden in this age group. 12 Despite various initiatives by the Indian government, the overall situation demands a combined effort from patients and healthcare workers to manage this disease effectively 13

In recent years, self-management programmes for chronic conditions have gained importance, especially among occupational therapists. 14 As type 2 DM is a challenging chronic disease to manage, a self-management approach has been identified as one of the core strategies in its management. 15 This approach views the individual as a fundamental component in maintaining health by combining partnerships between patients and professionals to attain effective care. 16 Self-management is the activities that individuals initiate and perform on their behalf in maintaining life, health and well-being and ‘developing the skills needed to devise, implement, evaluate and revise an individualised plan for a lifestyle change’. 17 It also refers to ‘the active involvement of individuals in various issues associated with their chronic diseases such as management of the symptoms, complications, treatment and modifying one’s lifestyle to live with chronic illness. 18

The self-management intervention approach includes five essential skills: problem-solving, decision-making, resource utilisation, effective communication with healthcare professionals and action planning. 19 The tasks involved in this approach comprise medication compliance, managing one’s nutrition and personal care, promoting mental and social health, communicating with healthcare providers and performing activities. 20

Changing habits and routines is a complex phenomenon specific to the context and develops with time. 21 Therefore, healthcare providers must focus on individuals’ experiences and empower them to integrate self-management practices into their routines 22 with an occupational focus. 23

Study rationale

Occupational therapy professionals focus on an individual’s occupation and are significant members of healthcare groups working with individuals with multiple chronic conditions. 24 Occupational therapists can assess client factors such as their knowledge, willingness for intervention and ability to engage in health-promoting activities. By doing so, occupational therapists can facilitate their participation in daily activities and occupations. Also, the profession advocates that quality of life can be improved through participation in meaningful occupations or tasks an individual requires or wants to do. 20

However, occupational therapists have been rarely recognised as prevention players in the past or present. There is a need for occupational therapists to promote health and wellness through occupation. 25 Pyatak 26 suggested that occupational therapy intervention for diabetes self-management can enhance the quality of life by facilitating individuals to adapt self-management skills into daily activities. Considering the profession’s comprehensive approach, occupational therapists should actively promote older adults’ health while promoting quality of life throughout their lifespan. 27 Active client participation throughout life is paramount considering the long duration of illness and functional impairment among individuals with chronic diseases such as diabetes. 28 Still, there is a lack of self-management interventions for older adults with type 2 DM in low-income or middle-income countries (LMICs). 29 Additionally, self-management intervention’s long-term effects on occupational performance and quality of life among older adults have been investigated sparsely. 30 With this context, the study questions are-

What is the existing literature on diabetes self-management programmes for community-dwelling older adults with type 2 DM in LMICs?

What are the existing principles, practices and criteria of self-management intervention programmes for community-dwelling older adults with type 2 DM in LMICs?

The present scoping review is planned to have two objectives, with the first focused on exploring and summarising the global literature on diabetes self-management interventions and the second focused on identifying various principles, practices and criteria related to self-management in LMICs.

Methods and analysis

Protocol design.

This study follows a scoping review design, combining quantitative and qualitative literature with a parallel results convergent synthesis design. The synthesis applies to analysing existing principles, practices and criteria that influence the selection and application of ‘diabetes self-management intervention’ among older adults in community settings with type 2 DM in LMICs. This review protocol was prepared following the Joanna Briggs Institute (JBI) scoping review methodology 31 devised using Arksey and O’Malley framework 32 and Levac et al framework 33 which was further modified by Peters et al. 31

Box 1 presents the enhanced scoping review framework proposed by Peters et al . 31 Further amendments, if any, in the protocol will be documented with justification in the final review.

Enhanced scoping review framework (Peters et al , 2015)

Defining and aligning the study objectives

Developing and aligning the inclusion criteria with the objectives and questions of the study

Describing the planned approach to evidence search and selection

Searching for the evidence

Selecting the evidence

Extracting the evidence

Charting the evidence

Summarising the evidence about the different objectives and questions

Consulting of the information scientists or experts (this process should be considered throughout)

Inclusion and exclusion criteria

The eligibility criteria for the scoping review will be based on the ‘PCC’ or the ‘Population-Concept-Context’ approach. It will include the type of resource components as presented in figure 1 .

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Eligibility criteria. DM, Diabetes Mellitus.

The study would include articles that refer to the population of older adults diagnosed with type 2 DM residing in the community, their caregivers and any professionals involved in providing diabetes-related care to these older adults.

For the present study, papers from inception until April 2024 that have included older adults, both men and women, aged 60 years and above and diagnosed with type 2 DM will be considered. Additionally, papers that focus on caregivers who are spouses or any family members residing with older adults with type 2 DM and aiding them will be included. Also, the focus will be on the papers related to various professionals such as community physicians/nurses and rehabilitation professionals including occupational therapists, physical therapists, community-based workers, social workers and speech and language therapists who usually work in rehabilitation settings and may have a direct or indirect role in providing care to older adults diagnosed with type 2 DM in the community.

Published studies that have included older adults or any other age groups diagnosed with type 1 diabetes or any other chronic conditions such as cancer, cardiovascular disease or chronic obstructive pulmonary disease will be excluded.

The central concept for this scoping review is the diabetes self-management programmes for older adults diagnosed with type 2 DM. For this review, we will focus on diabetes self-management intervention programmes. We will extract evidence related to (1) theoretical principles, practices and criteria that were followed for the development of such self-management intervention programmes and (2) current practices related to the design, development and use of self-management programmes among older adults diagnosed with type 2 DM will be charted.

McLean et al 2016 34 defined self-management as the care taken by individuals toward their health and well-being consisting of the actions they take to (1) lead a healthy lifestyle, (2) meet their social, emotional and psychological needs, (3) care for their long-term condition and (4) prevent further illness. For this review, diabetes self-management is considered as any intervention provided to community-dwelling older adults focusing on education about type 2 DM and awareness toward its self-management, exercises or activities to maintain physical health, mental health and well-being, maintaining participation in various daily life activities, fatigue management and energy conservation, maintaining social and leisure participation, medication management, effective communication strategies, maintaining physical and biochemical parameters, maintaining healthy nutrition and lifestyle. The present study would include all these approaches as part of a self-management intervention that may be delivered across various modes such as in-person or virtual mode, individual or group-based, digital or non-digital mode, home-based or centre-based, peer-led or professional-led.

Regarding the professionals, the outcomes refer to the development, implementation and adherence to diabetes self-management programmes, the use of such interventions in routine clinical practice or any measures of the effectiveness of self-management interventions, strategies or theoretical frameworks used to develop these interventions.

Apart from the outcomes, the review is focused on exploring the factors influencing (ie, variables), strategies followed or practices related to self-management of type 2 DM. These variables may influence the practices as determinants, acting as facilitators or barriers to intervention use.

The setting for this scoping review will be the global literature addressing occupation-centred diabetes self-management programmes for community-dwelling older adults with type 2 DM.

Type of resources

For this scoping review, we will consider available resources on diabetes self-management programmes such as primary studies, systematic reviews, meta-analyses, mixed-methods studies, opinion articles, editorials and letters. The citation search will be conducted on 1 July 2024.

Search strategy

The search will be based on JBI’s three-step search methodology for scoping reviews. In the first step, a preliminary search was conducted in MEDLINE (via PubMed). The retrieved papers were checked and the relevant terms (in the title and abstract of the papers) and the key terms mentioned in the retrieved articles were used to build the search strategy for searching in other relevant databases such as EBSCO, CINAHL, Wiley Online, Cochrane Library, Scopus, ProQuest and Web of Science. The search strategy used for PubMed is given in the online supplemental file 1 . In the third step, the reference list of all the identified articles will be searched for additional studies. Authors of the studies/reports will be contacted if we need additional information on any article. We will have no limits or restrictions on the language or publication dates for including papers. There is no requirement for a comparator for any study to be included in this review. The three-step searching process is depicted in figure 2 .

Supplemental material

Three-step searching process for the scoping review.

Selection of evidence sources and data management

Two independent reviewers will conduct the screenings against the eligibility criteria. For stage 1 screening (titles and abstract screening), two reviewers will perform the independent reviewers’ role and a third reviewer will be approached to reach a consensus on the disagreements. At the same time, the third reviewer (not performing the level 1 screening) will decide whether to retain the article if the two level 1 reviewers cannot resolve the disagreement. For the level 2 screening (final eligibility based on full-text review), one reviewer will perform the first independent reviewer role and the other two reviewers will split the second reviewer role. The final included articles after the full-text screening will be available for data extraction. The entire process will be reported using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses flow chart. Data will be managed using Rayyan.ai and Zotero software and Microsoft Excel spreadsheets.

Extraction of results

Extraction or charting will be done independently to provide a descriptive and logical summary of the results, aligning with the scoping review’s objective. The extraction will be done using a charting table that will consist of bibliographical details such as publication year, journal, keywords, author affiliation and geographic details; study details such as objectives of the study, population characteristics, methodology of the study, details about diabetes self-management intervention, findings relevant to the review question. The charting table will be modified during the review and updated based on the data if required. Charting of the data will be a continuous process and the table will be updated continuously. The preliminary charting format is given in table 1 .

• View inline

Data extraction or charting table

Data analysis

This review will follow a parallel result convergent synthesis design in which two independent reviewers will extract quantitative and qualitative data related to the design or implementation of diabetes self-management programmes. Additionally, the same reviewers will extract strategies used to formulate the diabetes self-management programme, implementation process and acceptance of such programme among community-dwelling older and the service providers and caregivers. Later, both the qualitative and quantitative data will be further analysed and presented separately. The results will then be integrated and interpreted in the discussion. Both qualitative and quantitative papers will be reviewed separately and will be discussed.

Presentation of results

Results for different diabetes self-management intervention programmes will be presented in a table that will give information about the (1) name of the intervention, (2) theoretical principles, criteria and practices followed, (3) characteristics of the intervention including delivery of the intervention and (d) limitations of the intervention as presented in table 2 .

Details of the intervention programs from the studies included in the review

Patient and public involvement

The scoping review to follow on this protocol will not require the participation of any patients or the general public.

Ethics and dissemination plan

As a secondary analysis, this scoping review does not require ethics approval. The final review results will be submitted for publication in a peer-reviewed journal in the rehabilitation, diabetes, occupational therapy or health promotion-related fields. Other dissemination strategies may be an oral presentation at international conferences or through various social media networks.

The results of this review can inform occupational therapists about various principles and strategies used to develop self-management intervention programmes for community-dwelling older adults diagnosed with type 2 DM.

Ethics statements

Patient consent for publication.

Not applicable.

• World Health Organization
• Sinclair A ,
• Kaundal A , et al
• Ranasinghe P ,
• Jayawardena R ,
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Contributors All authors have made substantive intellectual contributions to developing this protocol. SM and RSS conceived the idea of this research, followed by a discussion that contributed to finalising the research idea. SM and SB drafted the methodology. Both worked on preparing the draft of this protocol and editing and finalising the manuscript. All three authors reviewed and edited the protocol draft. SM is responsible for the overall content as guarantor.

Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

Competing interests None declared.

Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

Provenance and peer review Not commissioned; externally peer reviewed.

Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

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Self-management assessment in multiple chronic conditions: A narrative review of literature

Affiliations.

• 1 School of Nursing, University of Wisconsin-Madison, 701 Highland Ave., Madison, WI, 53705, United States. Electronic address: [email protected].
• 2 School of Nursing, University of Wisconsin-Madison, 701 Highland Ave., Madison, WI, 53705, United States. Electronic address: [email protected].
• 3 School of Nursing, University of Wisconsin-Madison, 701 Highland Ave., Madison, WI, 53705, United States. Electronic address: [email protected].
• PMID: 29709734
• DOI: 10.1016/j.ijnurstu.2018.04.009

Objectives: Effective self-management in individuals with multiple chronic conditions is necessary to optimize health outcomes. Self-management in multiple chronic conditions involves an iterative process prioritizing multiple changing needs/conditions. However, self-management in multiple chronic conditions has been assessed with instruments designed to assess self-management of a single chronic illness. The instruments may not address the complexity of self-management in multiple chronic conditions. Thus, this review aimed to examine how self-management has been operationalized in the context of multiple chronic conditions.

Design: A narrative review method was used.

Data source: The online databases, Pubmed, CINAHL Plus, and PsycInfo, were searched. The search was conducted of the database from January 2006 through November 2017.

Review methods: Peer-reviewed research articles which operationalized self-management in adults with at least two or more chronic illnesses were selected for review. Two reviewers read full text of selected articles and extracted data regarding operational definitions of self-management and instruments used to assess self-management. Operational definitions were categorized to conceptualize how self-management has been assessed.

Results: A total of seven peer-reviewed research articles were selected for inclusion. This review found that self-management has been assessed through prerequisites of self-management and behaviors involved in self-management. Prerequisites of self-management included attitude, self-efficacy, perceived ability, and knowledge. Behaviors included an individual's engagement in self-management such as health-related behaviors, health service use, and medication adherence.

Conclusions: This review revealed that current literature does not operationalize self-management in multiple chronic conditions as a process, indicating incomplete assessments of self-management. To obtain a more comprehensive understanding of self-management in multiple chronic conditions, future studies should consider self-management as an iterative process in addition to prerequisites for self-management and behaviors. Such studies will inform the development of patient-centered self-management interventions for individuals with multiple chronic conditions.

Keywords: Assessment; Chronic illness; Literature review; Multiple chronic conditions; Self-management.

Copyright © 2018 Elsevier Ltd. All rights reserved.

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Vergara, D.; Lampropoulos, G.; Antón-Sancho, Á.; Fernández-Arias, P. Impact of Artificial Intelligence on Learning Management Systems: A Bibliometric Review. Multimodal Technol. Interact. 2024 , 8 , 75. https://doi.org/10.3390/mti8090075

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Vergara, Diego, Georgios Lampropoulos, Álvaro Antón-Sancho, and Pablo Fernández-Arias. 2024. "Impact of Artificial Intelligence on Learning Management Systems: A Bibliometric Review" Multimodal Technologies and Interaction 8, no. 9: 75. https://doi.org/10.3390/mti8090075

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Academic Achievement: Influences of University Students’ Self-Management and Perceived Self-Efficacy

Mohammed hasan ali al-abyadh.

1 Mental Health Department, College of Education, Prince Sattam bin Abdulaziz University, Alkharj 16273, Saudi Arabia

2 College of Education, Thamar University, Thamar 87246, Yemen

Hani Abdel Hafeez Abdel Azeem

3 Quality Unit at the Higher Institute of Administrative Sciences, Janaklis, Al Buhayrah 22732, Egypt

Associated Data

Not applicable.

Successful students are more than just those who have more effective and efficient learning techniques for acquiring and applying information. They can also motivate, evaluate, and adjust their behavior if they are not learning properly. Thus, the objective of this study was to investigate the influence of university students’ self-management during their learning experience and their self-efficacy on their academic achievement. Additionally, the study investigated the differences between the Egyptian and Saudi students’ perceptions of self-management skills and self-efficacy in their academic achievement within the two countries. A total of 889 students from two different Arab countries took part in the study (Egypt and the Kingdom of Saudi Arabia). The sample was given an online questionnaire to evaluate their self-management abilities, perceived self-efficacy, and academic achievement. A quantitative approach using SmartPLS-SEM was deployed. The findings demonstrate that self-management and self-efficacy have positive influences on students’ academic achievement in both countries. Further, self-management skills have been proven to influence self-efficacy, which in turn highly influences academic achievement. Moreover, the findings of the Multi-Group Analysis (MGA) did not report significant differences between the Egyptian and Saudi students in terms of their perception of self-management, self-efficacy, and academic achievement.

1. Introduction

In an effort to build the nation’s workforce for future rapid growth, the university education stage plays a vital role. According to Dev ( 2016 ), students’ learning outcomes, particularly at the university level, are a barometer of education’s success or ineffectiveness and a key predictor of youths’ and the nation’s future. Therefore, higher education should focus on the student’s whole development in terms of social, economic, and political environments, and it should be more than merely obtaining a certificate ( Harris 2001 ). Successful students are not only those who have more efficient and effective learning techniques for acquiring and applying their information. They can also encourage themselves and assess and adjust their behavior if they are not learning appropriately ( Kadiyono and Hafiar 2017 ). In this regard, Dembo ( 2004 ) identified six elements that students should manage to be good learners. These include self-motivation, learning techniques, social and physical environments, and time management. These elements serve as the foundation for structuring and integrating the essential skills to fulfill the academic expectations of university students learning. This concentration allows for the integration of both skill and academic-performance techniques. In addition, much self-motivation and self-discipline is required to achieve academic excellence ( Kadiyono and Hafiar 2017 ).

Recently, researchers, families, policymakers, and planners have focused on student academic achievement ( Dev 2016 ). Institutions should train students’ academic and life skills to ensure they can function at an appropriate learning level, according to previous research on comprehensive student development ( Wood and Olivier 2004 ). This has inspired various studies into more effective methods of increasing academic standards, and it has been discovered that proper self-management for students of higher education, among other criteria, improves learning and academic accomplishment ( Sikhwari 2014 ). Individuals with effective management skills, according to Kadiyono and Hafiar ( 2017 ), know where to place goals; how to solve problems effectively, think optimistically when presented with academic problems, utilize resources, manage their surroundings to meet their objectives; and may reflect on the causes of failure and establish objectives for future growth. Self-management is described as the ability to work efficiently toward significant goals while being adaptable in the face of difficulties ( Agolla and Ongori 2009 ). According to Stan ( 2021 ), self-management is a multidimensional umbrella concept that combines the personal qualities of the individual on which it can work through a behavioral transformation process. In this essence, Agolla and Ongori ( 2009 ) claimed that students with higher levels of self-reported behavioral self-management report better levels of self-reported academic success and adaptability to change.

In the same line, previous studies have found that willingness to attempt and tenacity are some of the characteristics of students with a good level of self-efficacy ( Ahmad and Safaria 2013 ). Students who have a good sense of self-efficacy will be able to pay close attention to, organize, and elaborate on content successfully due to their cognitive abilities ( Heslin and Klehe 2006 ). Such students work consistently; if they are unable to follow the course, they devise efficient ways to overcome obstacles to reaching their goals. Self-efficacy, or belief in one’s talents and capacities for performance and learning, is an important characteristic of university students’ success ( Hill 2002 ). Students who believe they can learn or complete an activity are more likely to accomplish the implementation of academic self-efficacy, study harder, persevere longer when faced with problems, and succeed at a better level than students who question their ability ( Schunk and Pajares 2002 ). According to Bandura ( 1997 ), self-efficacy beliefs determine task selection, effort, perseverance, resilience, and accomplishment.

In summary, students’ ideas about their skills and the outcomes of their efforts have an important impact on how they behave. As a result, it is not surprising that a large body of research indicates that student skills impact learning and achievement ( Meral et al. 2012 ). However, Novo and Calixto ( 2009 ) asserted that researchers do not provide deep and experimentally proven insights into the structure that lies at the foundation of learning processes and shape their growth, but rather about the challenges of the learning process. For example, several research studies in the United States ( Kuhfeld et al. 2020 ), the Netherlands ( Meeter 2021 ), Belgium ( Maldonado and de Witte 2022 ), and Germany ( Meeter 2021 ) have examined the difficulties imposed by COVID-19 on academic success ( Schult et al. 2022 ). The majority of these studies looked at student standardized test scores before and after the spring 2020 lockdown and showed slight but substantial drops. Academic achievement is frequently related to successful students’ particular talents and abilities. According to Díaz-Morales and Escribano ( 2015 ), academic achievement is the result of the complex interplay of the psychological, economic, and social factors that contribute to students’ optimal growth. One of the most important indicators of a student’s performance is their academic achievement; hence, research into the elements influencing academic achievement has long been highly regarded ( Rivkin et al. 2005 ). However, there is still a scarcity of studies on academic accomplishment and what factors should be developed ( Kadiyono and Hafiar 2017 ), which is surprising given that the goal of learning (education) is to assist each student in achieving their desired level of growth.

Within the context of the above-mentioned introductory framework, this study (1) investigates the influence of university students’ self-management during their learning experiences and their self-efficacy on their academic achievement in two different countries (Egypt and KSA), all of which appear to be key aspects of the learning process. Moreover, the study is considered pioneer research that (2) investigates the differences between the Egyptian and Saudi students’ perceptions of self-management skills and self-efficacy in their academic achievement. However, of the massive research studies that investigated each variable of the current framework with another, the current framework is considered novel due to studying the current three variables together within two different contexts in two different countries on different continents. This study also offers valuable advice to students on self-concept and soft skills, as well as acts as a roadmap for future research by potential researchers. In actuality, improving educational achievements necessitates the development of soft skills to promote human capacities, which is required to encourage the individual’s growth ( Levasseur 2013 ). Therefore, the interest in studying the aspects (skills) involved in academic performance stems primarily from the phenomenon’s complexity, the long-term impacts of which aim for high employability chances and good professional adaption.

2. Literature Review and Hypotheses Development

It is common knowledge that developing personal qualities during university education impacts a student’s later career and personal life since they are easily transferable. Subsequently, identifying individuals’ distinctive academic factors that contribute to achievement is critical since it aids academic success in higher education and potential career possibilities ( Sanchez-Ruiz et al. 2016 ). Academic success is influenced by a wide range of factors. The “Coleman Report”, a report on academic achievement from a large-scale study, was published in the 1960s ( Cheng et al. 2019 ), and numerous applications were produced based on this study as a result, which is essential for academic achievement difficulties. The elements influencing academic accomplishment can be loosely characterized as follows: psychological perceptions, student skills, and environmental perspectives ( Dijkstra and Peschar 2003 ). Moreover, some researchers think that four elements influence academic achievement: individual, family, educational institution, and the environment; the factors involved in individual factors can be further divided into cognitive functioning, learning mindset, motivation, and self-aspiration ( Hammouri 2004 ). Learning outcomes have become a phenomenon that everyone is interested in, which is why researchers have been working hard to uncover aspects that promote high academic achievement ( Aremu and Sokan 2003 ). As a result, we present a theoretical background on this triangular relationship among self-management abilities, self-efficacy, and academic-achievement motivation among university students in this section.

2.1. The Role of Student Self-Management in Increasing Student Self-Efficacy

In a wide sense, self-efficacy is described as a person’s belief in his/her abilities to plan and carry out the steps required to achieve specific objectives ( Bandura 1997 ). Bandura ( 2001 ) observed that students’ conduct is frequently best predicted by their ideas about their skills. Bandura ( 1997 ) proposed that self-efficacy influenced how students felt, thought, and acted. Self-efficacy, according to self-efficacy theory, is one’s belief in their capacity to plan and carry out a certain course of conduct to find a solution or complete a task ( Eccles and Wigfield 2002 ). Thus, a student’s self-efficacy refers to an individual’s belief in the ability to learn and perform behavior at a particular level. In addition, a high level of students’ self-efficacy promotes skill development, capacity building, and resilience by promoting task motivation and commitment, hard-working spirit, longer endurance, and resilience, especially when faced with difficulties ( Vermeiren et al. 2022 ).

In their conceptualization, Sharma and Nasa ( 2014 ) claimed that students’ abilities provide a method for explaining and predicting one’s feelings, thoughts, and behaviors, as well as organizing and carrying out courses of conduct to achieve certain goals. In this regard, self-management is described as the act of personally directing the dispositions, behavior, and recognition of persons toward achieving goals or tasks ( Amini and Noroozi 2018 ). Self-management is an important tool for all types of learning, including materials and academic courses, as well as other curriculum areas and abilities. It refers to the tactics, procedures, and methods that we use to successfully direct the actions and behaviors of students during their studies ( Jasim 2020 ). Self-management teaches students how to regulate their emotions, create objectives, and arrange themselves so that they may be powerful self-motivators ( Amini and Noroozi 2018 ). This concept has a significant meaning, in that self-management affects one’s level of ability and the amount of tenacity required to achieve a tough goal ( Bandura 2001 ). Therefore, self-management assists students in becoming effective students. Self-management enables students to stick to their strategies for completing tasks while remaining focused in the classroom ( Jasim 2020 ). As a result, the researchers present the hypothesis below.

Students with high self-management are more likely to achieve a higher academic self-efficacy.

2.2. The Role of Student Self-Management in Increasing Student Academic Achievement

In a determinate sense, self-management encompasses, among other things, self-discipline, self-control, self-regulation, willpower, ego strength, and effortful control ( Duckworth and Kern 2011 ). Along the same line, self-management, according to CASEL ( 2018 ), is defined as the capacity to control an individual’s emotions, ideas, gratification, and actions to motivate oneself and strive toward academic and personal objectives. On the other hand, the approaches used to describe student achievement vary with the concept’s complexity and breadth. It refers to a student’s acquisitions in a structured academic setting, as evidenced by the value placed on academic performance expressed in grades, standardized test results, or teachers’ recognitions in evaluations ( Erhuvwu and Adeyemi 2019 ). Academic achievement, operationally, indicates the set of learned knowledge, the degree of growth of capacities, and skills in the academic setting ( Jeynes 2008 ). Most studies in this field emphasize the relationships between student skills and academic achievement ( Di Fabio and Palazzeschi 2009 ) and occupational status ( Deary et al. 2007 ). Sanchez-Ruiz et al. ( 2016 ) developed another argument for comparing and generalizing the findings of studies on the influence of students’ ability on academic accomplishment that refers to personality characteristics as indicators of academic achievement. Robbins et al. ( 2004 ) suggest a composite social model that includes individual skills, social engagement, and academic-related abilities to explain the mechanism of academic achievement. According to previous research, students who utilize self-regulation tactics (such as self-regulated learning, time management, goal planning, and metacognition) perform better in class ( Stan 2021 ). In this essence, Claro and Loeb ( 2019 ) refer to self-management as the capacity to control an individual’s thoughts, emotions, and behaviors in a variety of settings. According to Balica et al. ( 2016 ) and Deming ( 2015 ), self-management is a powerful indicator of academic success, decision-making abilities, and competence in behavior modification. As a result, the following hypothesis is developed.

Students with high self-management are more likely to secure a higher academic achievement.

2.3. The Role of Self-Efficacy in Enhancing Student Academic Achievement

Academic achievement was originally regarded as the most essential consequence of the formal academic experience ( Kell et al. 2013 ); although there is little dispute about the importance of such achievements in student experience and later life, they are no longer the most important outcome ( Colmar et al. 2019 ; Martinez et al. 2019 ).

Students’ views on their capacity to master new abilities and activities, frequently in a particular academic topic, are referred to as self-efficacy ( Nasiriyan et al. 2011 ). In other words, Gardner ( 1983 ) defines a self-efficacious student as someone who believes in their ability to plan and carry out the steps necessary to achieve certain goals. According to Bandura ( 1997 ), perceived self-efficacy indicates people’s beliefs in their ability to achieve specific goals. Kryshko et al. ( 2022 ) argued that investigating the effect of self-efficacy on motivational adjustments to academic performance may be useful empirically. Thus, researchers pay little attention to this type of belief in effectiveness and its role in academic performance. Self-efficacy is a key element of Bandura ’s ( 2001 ) social-cognitive theory, which asserts that self-influence profoundly influences behavior. It increases grit when faced with problems, promotes purposeful behaviors, supports long-term vision and develops self-regulation and allows for self-correction when required within the context of social-cognitive theory. Previous research has identified cognitive skills and academic self-efficacy as well-established determinants of academic performance ( Köseoğlu 2015 ). According to Abouserie ( 1995 ), failure or success may be associated with weak or strong self-efficacy, and these links might influence university students’ performance. In previous research studies, belief in self-efficacy in various domains, along with various indicators of motivation and academic achievement, has emerged as an important determinant of students’ effective use of self-regulation skills and strategies ( Kim et al. 2021 ; Kryshko et al. 2022 ). Several studies have demonstrated that self-efficacy is a reliable predictor of motivation and academic performance that is unaffected by time, place, or community ( Duckworth et al. 2007 ). It is the motivational aspect of self-efficacy that appears to generate academic achievement ( Ashwin 2006 ). According to Miller and Brickman ( 2004 ), excellent educational success is related to improved confidence in one’s abilities, which encourages students to accept more responsibilities for the effective completion of assignments and projects. As a result, strong self-efficacy is widely acknowledged as an essential predictor of work-related achievements. More specifically, Honicke and Broadbent ( 2016 ) examined 59 self-efficacy studies conducted at universities and discovered a modest relationship between academic achievement and self-efficacy. In a similar vein, Schunk and Zimmerman ( Meral et al. 2012 ) identified a connection between academic achievement and self-efficacy, indicating that students’ academic achievement increases when they are taught to have stronger self-efficacy beliefs. As a consequence, we formulate the a hypotheses below.

Students who have a high level of self-efficacy are more likely to achieve higher academic achievement.

Perceived self-efficacy positively mediates the relationship between perceived self-management and students’ academic achievement.

Trautwein et al. ( 2006 ) suggested an academic achievement model in which a variety of factors impact the completion of certain academic tasks. In addition to class and social characteristics, they looked at personal and intellectual qualities such as IQ, consciousness, knowledge, and attitude. In our study, we focused on prioritizing the role of personal and intellectual ability in terms of self-management and self-efficacy to better represent the factors facing college students ( Figure 1 ). This adjustment is justified, since the involvement of student qualities (IQ, consciousness, knowledge) is expected to be equal at the same stage of education, especially if they are studying the same subject, even in different countries. This study was conducted on university students in two different countries (i.e., Egypt and the Kingdom of Saudi Arabia), to investigate the current research framework and to illustrate the differences between Egyptian and Saudi students, if applicable. Thus, we propose the following hypothesis.

The research conceptual framework and hypotheses.

There are no differences between Egyptian and Saudi students’ perceptions in terms of the direct and indirect relationships between self-management, self-efficacy, and academic achievement.

3. Materials and Methods

3.1. sampling and data collection.

University students in Egypt and the Kingdom of Saudi Arabia (KSA) are the participants of the current study to align with the research objectives. Egyptian and Saudi universities were chosen for the field study due to the development of the education sector in both countries to achieve their visions for 2030. Additionally, the well-recognized economic development in all different sectors in both countries, (i.e., service and industrial) encourages students to build their academic careers to hunt for job opportunities after graduation. Finally, the authors of the current paper are faculty members in these countries. Thus, an online survey was established through Google docs targeting only 1600 students virtually representing Prince Sattam Bin Abdulaziz and King Saud University students in the KSA and University of Sadat City and Menoufia University in Egypt. We contacted the information technology unit of each university to disseminate the questionnaire to students after obtaining official approvals. The online survey link was sent to students via their academic emails. Of the 1600 respondents who received the online survey, we received 1005 surveys with a response rate of 62.8%, only 889 (KSA = 419; Egypt = 470) were eventually usable for the statistical analysis. About 116 surveys were excluded due to incomplete responses. Table 1 presents the demographics of the study’s participants.

Sociodemographic characteristics of the students.

3.2. Measurements

We deployed a quantitative approach to investigate the research hypotheses. Thus, the questionnaire was built based on a thorough revision of related research studies. Consequently, the questionnaire includes four categories: self-management, perceived self-efficacy, academic achievement, and respondents’ profiles. First, self-management was measured by 10 items adapted from ( Öberg et al. 2019 ). Second, the perceived self-efficacy was measured by ten items retrieved from ( Sukmak et al. 2001 ). Third, twenty items adapted from Turner ( 2007 ) were used to measure the motivations of students for academic achievement. Finally, the fourth section contains the students’ demographics. Additionally, all of the items in the questionnaire were assessed using five-point Likert scales ranging from “strongly disagree = 1” to “strongly agree = 5. The questionnaire was translated from English to the Arabic language to fit all students and to guarantee a full understanding of the questionnaire statements. To confirm the context validity of the questionnaire items before disseminating, the Arabic version of the questionnaire was retranslated into English. We conducted a pilot study on one hundred students in both countries to check the validity and reliability of the questionnaire. The findings of the refined draft of the questionnaire showed slight modifications to some Arabic words.

3.3. Data Analysis and Hypotheses Testing

The SmartPLS-SEM software, version 3.2.8 (Oststeinbek, Germany), was run to analyze the research data and test the hypotheses. The PLS technique has been extensively operationalized in all research disciplines for several reasons ( Alsetoohy et al. 2019 , 2021 ; Alsetoohy and Ayoun 2018 ). PLS is more suitable for small sample sizes, predictions, and the development of theories in research studies. Additionally, PLS is non-sensitive to the normality of data distribution. Finally, the PLS technique works well with models that have a large number of indicators. A two-step process (i.e., the measurement model and the structural model) was deployed to test the research hypotheses using Smart PLS-SEM software, version 3.2.8 (Oststeinbek, Germany) ( Hair et al. 2012 ).

3.4. The Measurement Model

The validity and reliability of all latent variables of the study were assessed and checked to validate the research model relationships. To verify the internal reliability of the constructs, the Composite Reliability (CR) and Cronbach’s alpha were checked. The convergent validity of the model was assessed by the item loadings of the indicators, CR, and the average variance extracted (AVE). Furthermore, the Heterotrait–Monotrait (HTMT) ratio of correlation and the AVE were utilized to establish the discriminant validity. Finally, the variance inflation factor (VIF) was calculated to assess the collinearity of the constructions.

Table 2 illustrates that the Composite Reliability (CR) and Cronbach’s alpha values for all latent variables in the models were above the floor of .7 ( Hair et al. 2012 ). Thus, the internal consistency of the research models was achieved. Additionally, the item loadings were above .60 ( Hair et al. 2010 ). Two indicators (AA9 and AA10) were removed as their loadings were less than .60. The CR values were greater than .7 ( Hair et al. 2012 ), and the AVE values were above the value of .5 ( Fornell and Larcker 1981 ), which establishes the convergent validity. Likewise, the HTMT values ranged from .736 to .858, less than the floor of −.90 ( Hair et al. 2012 ) (see Table 3 ). Therefore, discriminant validity was established for all models. Finally, the highest value of VIF is 4.331, which is lower than 5, confirming that there are no multicollinearity issues between the models’ constructs ( Ringle et al. 2015 ).

Assessment results of the measurement model.

NB. AA9 and AA10 in italic were dropped.

Heterotrait–Monotrait Ratio (HTMT).

3.5. Multigroup Analysis

After all the research models passed the robustness check using the measurement models’ assessment, we applied a non-parametric structural equation-modeling approach to analyze the differences between the Egyptian and Saudi students using Henseler’s MGA and the permutation test ( Garson 2016 ; Henseler et al. 2016 ). Thus, the MICOM technique was run before the final step of the data analysis to test the invariance assessment to ensure the heterogeneity of the groups ( Henseler et al. 2016 ). This technique was used to confirm that the same indicators were used for each measurement model and an acceptable reliability of each construct was obtained for both groups. Hence, two groups of students were created: Egyptians ( n = 470) and Saudis ( n = 419). Table 1 displays the assessment results of the measurement model between the two datasets of Egyptians ( n = 470) and Saudis ( n = 419) along with the total students’ model ( n = 889). In step one, the assessment of configural invariance was achieved. Table 4 shows the results of the measurement invariance testing. The results of the compositional invariance assessment for Step two were established as none of the correlation (c) values are significantly different from 1. In Step 3, the composites’ equality of mean values and variances across the group was assessed. The results indicate that the confidence intervals of differences in mean values and variances partially include zero, which means the composite mean values and variances are partially equal. As such, achieving the establishment of the three steps of the MICOM procedure supports the partial measurement invariance of the two groups ( Garson 2016 ; Henseler et al. 2016 ). This indicates that the pooled data for each group meets the requirement for comparing and interpreting any differences in structural relationships. Thus, further analysis for comparing and interpreting the MGA group-specific differences of PLS-SEM can be performed.

3.6. Testing the Research Hypotheses and Results

To assess the structural model of the current research study, we checked the R 2 values, the p values, and the significance of the path coefficient (β) see Figure 2 , Figure 3 and Figure 4 . The results show that the R 2 values achieved ranged between 56.8% to 67% for the dependent variable, which represents the substantial explanatory power of the current models ( Chin 2010 ). The p values and the path coefficients refer to the statistical significances between the research variables. In general, the results of the research study show that perceived self-management has the strongest positive influence on the academic self-efficacy (β all = .804, β eg = .818, β sa = .794; p = .000) of all students. This supports hypothesis 1 (H1). Moreover, the findings of the current study reveal that perceived self-management has positive effects on students’ academic achievement (β all = .294, β eg = .279, β sa = .286; p = .000) in both countries. Thus, hypothesis 2 (H2) is supported. In the same context, the results of this study indicate that perceived self-efficacy is positively correlated with students’ academic achievement (β all = .516, β eg = .507, β sa = .286; p = .000). Thus, hypothesis 3 (H3) is further supported.

Results of the structural model with data from all students.

Results of the structural model with data from the Egyptian students.

Results of the structural model with data from the Saudi students.

To assess the significance/insignificance of the indirect effects of the current research model, bootstrapping tests with 5000 samples in SmartPLS-SEM were conducted to calculate the Bias-Corrected-Confidence Interval (BCCI), T-statistics, component weights, and observed significance values in the path coefficients to check the mediating effects of self-efficacy on the students’ academic achievement. The findings of the current study revealed a positive indirect significant relationship between perceived self-management (IV) and students’ academic achievement (DV) through perceived self-efficacy. Moreover, BBCI does not straddle zero between identified significant mediations, as shown in Table 5 . The results report that perceived self-efficacy (β all = .415, β eg = .415, β sa = .455; p = .000) positively mediates the relationship between self-management and students’ academic achievement, which supports hypothesis 4 (H4).

Results of hypotheses.

** p < 0.01; *** p < 0.001.

Results of invariance measurement testing using permutation.

As a prior step, the MGA was conducted using the Egyptian and Saudis datasets after completing the MICOM tests. In general, the MGA results showed non-significant differences between Egyptian and Saudis students for both direct relationships and indirect relationships of the research model, see Table 4 . This supports hypothesis 5 (H5). Thus, the results of the total participant students in the current study (Egyptian and Saudi students) can be generalized.

4. Discussion

The current research sought to measure the relative impact of the self-management concept on modeling students’ academic achievement via self-efficacy.

On the one hand, for students of developed countries, there is a clear path from academic self-management, self-efficacy, student dedication, patience, and goal setting to ultimate academic performance ( Bandura et al. 2001 ; Honicke and Broadbent 2016 ). Thus, the current research study examines the influence of self-management and self-efficacy on student academic achievement among students in two different developing countries. We attempted to overcome the shortcomings of previous studies in this area by (1) considering several theoretical and empirically distinct foundations of student achievement, (2) students’ self-management and self-efficacy, and (3) investigating predictors in two different domains, namely Egypt and the Kingdom of Saudi Arabia.

However, although the MGA results did not show significant differences between the Egyptian students (see Figure 2 ) and the Saudi students (see Figure 3 ), the results of Figure 1 (i.e., the total model) can be used to generalize this research results. The interpretation of the non-significant differences between the Saudi and Egyptian students may be due to both countries being in different regions and students speaking the same language (Arabic) and sharing the same traditions and customs. Additionally, a large number of Egyptian faculty members teach in Saudi universities, which in turn may lead to similar influences on students’ academic consciousnesses, knowledge, and academic accomplishments. These factors may contribute to diminishing the differences between students in both countries in terms of self-management, self-efficacy, and academic achievement. This finding is contrary to previous research studies ( Oettingen 1997 ; Scholz et al. 2002 ), which confirmed that there was a cultural variation in how people felt about their abilities.

Among the predictor factors, students’ self-efficacy explained the most variance in academic achievement. It is considered that students’ self-efficacy assessments have a significant impact on their learning-process success. Students’ self-efficacy contributed significantly to the variation in the criteria in our study. It was revealed that students who are self-assured and more confident are more likely to achieve higher academic achievements, confirming that self-efficacy beliefs play an essential role in explaining academic achievement. The relative superiority of students’ self-efficacy in this investigation is consistent with the literature on the subject (e.g., Affuso et al. 2017 ; Honicke and Broadbent 2016 ; Köseoğlu 2015 ; Meral et al. 2012 ; Travis et al. 2020 ) and with several studies that have looked at the antecedents that influence academic accomplishment (e.g., Ashwin 2006 ; Hennig-Thurau et al. 2001 ). Crain ( 2005 ) claims that, when students have doubts about their abilities, they are less active and more likely to have no problems.

Students develop academic self-efficacy by evaluating and interpreting their task performance, which represents a self-judgment of competence ( Bandura et al. 2001 ; Usher and Pajares 2009 ). Additionally, Ansong et al. ( 2019 ) argued that students’ self-efficacy is more likely to increase when students believe their academic abilities and efforts are successful and, conversely, are likely to diminish when they feel their efforts are insufficient. As a result, students with a high level of self-efficacy mastered their objectives, which included challenges and new information; performance quality, which included good grades; and outperforming peers. When they feel they are good at something, they work hard at it and stick with it despite failures ( Crain 2005 ).

Moreover, self-management was also found to have a key impact on self-efficacy. According to our findings, the degree of self-efficacy determines a high percentage of the variation in the self-efficacy criteria, which is consistent with other studies (e.g., Di Fabio and Palazzeschi 2009 ; Stan 2021 ). Self-management is a broad concept that encompasses qualities such as self-efficacy. Self-management is widely recognized as one of the required abilities that drive students toward becoming more self-determined youths who can responsibly and proactively manage the elements of their lives, both in and out of educational contexts, according to King-Sears ( 2006 ). As a result, our study’s perspective is that students who can create objectives and employ various self-management tactics have better self-efficacy.

Furthermore, this study demonstrates that self-efficacy is a mediating factor in the relationship between self-management and academic achievement. Although analyses of the specialized literature confirm that self-management predicts student success (because the relationship with self-management is stronger than any other component of self-efficacy) ( Stan 2021 ), our research results indicate that, without self-efficacy (mastery of skills and activities), academic achievement is relative. It might be claimed that academic self-efficacy is frequently used to prepare and carry out the procedures required to accomplish certain goals. Perceived self-efficacy, according to Bandura ( 1997 ), relates to students’ beliefs in their capacity to attain specified goals. So, the role of self-efficacy in explaining variation in academic achievement across students is a central theme in our study.

Furthermore, our research shows that students’ self-management has a modest influence on academic achievement. This outcome is consistent with the arguments of Kadiyono and Hafiar ( 2017 ), who believe that academic self-management may be utilized to motivate students to enhance their academic achievement, so that they can build a solid foundation to go forward and construct their futures. Nonetheless, given a well-established research background supporting self-management as an intervention, it appears that its usage among students must be encouraged by their instructors’ actions. Thus, when students are confident in their academic ability, they can set educational goals that drive them to academic excellence. On the other hand, students with little or no confidence in their abilities and capacities may be less likely to pursue higher levels of academic performance that require a higher level of effort, abilities, and skills; this confirms the findings of Ansong et al. ( 2019 ). In this regard, King-Sears ( 2006 ) argued that teachers play a critical role in enhancing students’ abilities to practice self-management.

5. Conclusions

The conclusions of this study have a variety of ramifications for educators, counselors, and students. This study attempted to investigate whether students’ self-management and self-efficacy produce excellent academic achievement when adopted by students working around a range of academic variables. The current study confirmed the significant relationships between self-management, self-efficacy, and academic achievement in two different domains (i.e., Egypt and KSA) through three models with identical significant results. Thus, academia and practitioners can use this research framework to guide their students to effective academic accomplishments. Additionally, our results did not show differences between students in terms of self-management, self-efficacy, and academic achievement according to country. This supports a fundamental conceptualization that students with different skills and motives can direct these positively toward their academic achievement regardless of their geographical domain and culture. Thus, the current study is considered a pioneer study that investigates the relationships between self-management, self-efficacy, and academic achievement among university students all in one model. This could be a guide for both students and educators who are seeking to optimize their (students’) academic achievements through self-management and efficacy. Additionally, this model was tested twice in two different countries which, in turn, helps generalize the results among all university students.

Due to the lack of orientation, self-management provides a fair to good degree of academic accomplishment, highlighting the need for treatments aimed at assisting students in developing a meaningful understanding of their self-management about their current views. The findings of this study confirm that self-management helps students control their impulses, set goals, organize themselves, and become strong self-motivators. Hence, students who can coordinate emotions and control and manage impulsivity stress are more likely to recognize goals and achieve them consistently. Additionally, students need to be aware of the purpose, the breadth, and the depth of self-management research and how expanding this skill can alleviate current problems. As a result, the current study elicits the role of educators, mentors, and counselors to empower and direct students’ motives, skills, and abilities to achieve both academic and life goals through facing and overcoming daily problems. Moreover, these findings affirmed that self-management is a powerful indicator of academic success, decision-making abilities, and competence in the behavior modification among students. This helps educators and students to modify students’ behaviors in a positive manner to establish academic achievement in both the short and long term. Nonetheless, the foundation of self-management plays a significant part in attaining students’ self-efficacy, due to its critical function in organizing all sorts of learning, including materials and academic courses. Such a finding is very noticeable in the overall evaluation of university students’ achievements. The results reveal that self-efficacy is a positive predictor of students’ academic achievement. Self-efficacy and academic achievement are reciprocally associated and mutually reinforcing, according to the mutual-effects model used in this study. Educators and university educators must create and use treatments that target self-management, self-efficacy, and academic achievement to put the model into effect. Finally, the positive relationship between the triangle-connection modeling could be used as a base for policymakers when establishing new curricula targeting efficient outcomes for students, educators, and the community.

Some limitations must be considered when evaluating the current study’s conclusions. Two distinct students’ behaviors were evaluated in this study, with different instructors adopting different teaching strategies. Future studies should aim to evaluate the triangle-connection modeling individually to obtain benchmark findings in each situation. The current study does not allow for a thorough conclusion about the underlying causes of the reciprocal impact of self-management, self-efficacy, and academic achievement. Further research should put to the test theoretically relevant antecedent models that might explain the relationships between self-management, self-efficacy, and academic achievement in greater depth. For example, engagement in supportive institutional–student connections in terms of teaching staff, teaching style, etc., can impact self-management, self-efficacy, and academic achievement all at the same time.

Acknowledgments

The authors would like to thank the University of Prince Sattam bin Abdulaziz for supporting the research.

Funding Statement

This project was supported by the Deanship of Scientific Research at the Prince Sattam bin Abdulaziz University under the research project 18820/02/2021.

Author Contributions

Conceptualization, M.H.A.A.-A. and H.A.H.A.A.; methodology, M.H.A.A.-A. and H.A.H.A.A.; software, M.H.A.A.-A. and H.A.H.A.A.; validation, M.H.A.A.-A. and H.A.H.A.A.; formal analysis, M.H.A.A.-A.; investigation, M.H.A.A.-A. and H.A.H.A.A.; resources, M.H.A.A.-A. and H.A.H.A.A.; data curation, M.H.A.A.-A.; writing—original draft preparation, M.H.A.A.-A. and H.A.H.A.A.; writing—review and editing, M.H.A.A.-A. and H.A.H.A.A.; visualization, M.H.A.A.-A. and H.A.H.A.A.; supervision, M.H.A.A.-A. and H.A.H.A.A.; project administration, M.H.A.A.-A. and H.A.H.A.A.; funding acquisition, M.H.A.A.-A. All authors have read and agreed to the published version of the manuscript.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki, and Ethics Committee) of both the university of Prince Sattam bin Abdulaziz, KSA and the Higher Institute of Administrative Sciences, Janaklis, Al Buhayrah, Egypt.

Informed Consent Statement

Written informed consent was obtained from the participant(s) to publish this paper.

Data Availability Statement

Conflicts of interest.

The authors declare no conflict of interest.

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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• Open access
• Published: 21 August 2024

Pediatric head injury guideline use in Sweden: a cross-sectional survey on determinants for successful implementation of a clinical practice guideline

• Fredrik Wickbom 1 , 2 ,
• William Berghog 1 ,
• Susanne Bernhardsson 3 , 4 , 5 ,
• Linda Persson 6 ,
• Stefan Kunkel 7 &
• Johan Undén 1 , 2  

BMC Health Services Research volume  24 , Article number:  965 ( 2024 ) Cite this article

55 Accesses

Metrics details

The Scandinavian Neurotrauma Committee guideline (SNC-16) was developed and published in 2016, to aid clinicians in management of pediatric head injuries in Scandinavian emergency departments (ED). The objective of this study was to explore determinants for use of the SNC-16 guideline by Swedish ED physicians.

This is a nationwide, cross-sectional, web-based survey in Sweden. Using modified snowball sampling, physicians managing children in the ED were invited via e-mail to complete the validated Clinician Guideline Determinants Questionnaire between February and May, 2023. Baseline data, data on enablers and barriers for use of the SNC-16 guideline, and preferred routes for implementation and access of guidelines in general were collected and analyzed descriptively and exploratory with Chi-square and Fisher's tests.

Of 595 invitations, 198 emergency physicians completed the survey (effective response rate 33.3%). There was a high reported use of the SNC-16 guideline (149/195; 76.4%) and a strong belief in its benefits for the patients (188/197; 95.4% agreement). Respondents generally agreed with the guideline's content (187/197; 94.9%) and found it easy to use and navigate (188/197; 95.4%). Some respondents (53/197; 26.9%) perceived a lack of organizational support needed to use the guideline. Implementation tools may be improved as only 58.9% (116/197) agreed that the guideline includes such. Only 37.6% (74/197) of the respondents agreed that the guideline clearly describes the underlying evidence supporting the recommendation. Most respondents prefer to consult colleagues (178/198; 89.9%) and guidelines (149/198; 75.3%) to gain knowledge to guide clinical decision making. Four types of enablers for guideline use emerged from free-text answers: ease of use and implementation, alignment with local guidelines and practice, advantages for stakeholders, and practicality and accessibility. Barriers for guideline use were manifested as: organizational challenges, medical concerns , and practical concerns.

Conclusions

The findings suggest high self-reported use of the SNC-16 guideline among Swedish ED physicians. In updated versions of the guideline, focus on improving implementation tools and descriptions of the underlying evidence may further facilitate adoption and adherence. Measures to improve organizational support for guideline use and involvement of patient representatives should also be considered.

Peer Review reports

Contributions to the literature

The pediatric Scandinavian Neurotrauma Committee head injury guideline from 2016 seems well known and well used by Swedish emergency department physicians, despite lack of formal implementation.

The study identified guideline implementation determinants that need to be addressed in both future guideline versions and in implementation strategies.

This study contributes reference data for the Clinician Guideline Determinants Questionnaire; a novel, validated tool for assessment of determinants for guideline use, with different results compared to previous reports utilizing the questionnaire.

Head trauma is a common cause to seek emergency department (ED) care among children in Sweden. In 2022, over 33,000 cases of head injury were registered in Sweden in children 0–17 years of age, according to the Swedish National Board of Health and Welfare [ 1 ]. Of these, 22.3% were diagnosed with an intracranial injury of varying severity (including concussion), yielding an overall incidence of 1521/100 000 patients with head injuries and an incidence of 340/100 000 patients with intracranial injury. Mild traumatic brain injury (mTBI) constitutes more than 80% of pediatric TBI cases globally [ 2 ]. Most of these injured children will recover without the need for acute intervention, e.g., neurosurgery or intensive care admission [ 2 , 3 , 4 , 5 ].

Cranial computed tomography (CT) utilizes ionizing radiation for imaging of the brain and is a valuable tool for excluding significant intracranial injuries, ordered in 4% of children with isolated head trauma in southern Sweden [ 6 ]. Radiation exposure in early life entails a risk of malignancy development later in life, and the selection of patients with mTBI for neuroimaging poses a clinical challenge [ 5 , 7 , 8 , 9 ]. Structured in-hospital observation is considered equally effective, although this is associated with higher resource use [ 10 , 11 ]. In Sweden (and similar to other countries), it is often junior physicians who initially manage these children, following a diverse range of local guidelines (or no guideline), resulting in an unstandardized approach to pediatric TBI on a national level [ 12 , 13 ].

The Scandinavian Neurotrauma Committee has recently developed a clinical practice guideline addressing the initial management of mTBI in children (SNC-16 guideline) in Scandinavia [ 14 ]. It was published in 2016 and has since then been passively disseminated into more than 50% of the Swedish emergency hospitals’ management routines [ 13 ]. Although validated in other settings, the SNC-16 guideline has not been validated in the Scandinavian population [ 15 , 16 ]. The SNC-16 guideline for managing patients with mTBI has been developed to help healthcare providers make informed management decisions. To assess the risk of intracranial injury, various factors such as clinical signs and symptoms (e.g., loss of consciousness, amnesia, neurological deficits) and current state of consciousness are considered in the guideline. If a patient's clinical status falls within the low-risk criteria, a CT scan or prolonged structured observation may be deemed unnecessary [ 14 ].

The process of clinically adapting research-based knowledge is widely acknowledged as intricate and non-self-regulating [ 17 , 18 , 19 ]. Clinical practice guidelines are considered valuable tools for integrating the latest medical evidence into clinical practice [ 20 , 21 ]. By identifying existing barriers and facilitators that influence the use of specific guidelines, it may be possible to tailor an implementation process and facilitate the uptake of a guideline into clinical settings and ensure adequate compliance [ 19 , 22 , 23 ].

In 2019, the Clinician Guideline Determinants Questionnaire (CGDQ) was developed and published by Gagliardi et al. [ 24 ]. This tool serves the purpose of providing a comprehensive and validated instrument for addressing factors relevant for the use or non-use of a specific guideline from a clinician's perspective. Knowledge about determinants for use and non-use specific for the SNC-16 guideline may support an implementation process and increase adherence to evidence-based practices in managing pediatric head trauma in Sweden. It may also give important information in future updates of the guideline.

The primary objective of this study was to identify barriers and enablers affecting use of the SNC-16 guideline by physicians in Sweden. Knowledge about these determinants is important as it allows development of tailored interventions in forthcoming implementation processes with the intention to promote uptake of research findings in routine care [ 24 ]. This study is part of a series of studies which embraces validation, development, and implementation of the SNC-16 guideline in Scandinavia.

Study design

This is a cross-sectional observational study in Sweden. Collection of data was performed using a validated questionnaire for implementation research [ 24 ]. Respondents were asked to assess the SNC-16 guideline based on the structured questions in the questionnaire. Reporting follows STROBE guidelines for cross-sectional studies (Additional file 1) [ 25 ]. An ethical advisory opinion was granted by the Swedish Ethical Review Authority (Dnr 2020 – 02 693).

The survey was sent to physicians in Swedish EDs of varying sizes nationwide, in which head trauma in pediatric patients is managed. Data were collected during February 23 to May 8, 2023.

Participants

Physicians from various medical specialties who regularly, at their own discretion, work in the ED of a Swedish hospital and assess pediatric acute head trauma, were included. Respondents not fulfilling the above criteria were excluded.

Potential participants were invited by an e-mail containing an information text and a link to the questionnaire. The initial e-mail recipient list of potential respondents was based on three different e-mail collection strategies: 1) a list of suggested respondents from a previous study, investigating management of pediatric TBI in Sweden at an organizational level [ 13 ]; 2) new e-mails to ED managers with a request to send us e-mail addresses to ED physicians working with pediatric mTBI in their ED (as the list from 2022 may contain irrelevant recipients or old e-mail addresses); and 3) screening of e-mail recipient lists accessible for our research team (identifying physicians in the department of general surgery in the Region of Halland, physicians in the department of emergency medicine in the Region of Halland and interns employed in the Region of Halland, Sweden). Only potential e-mail recipients suggested from a hospital that managed children with pediatric head trauma were included when extracting the e-mail list, drawn from the 66 hospitals included in the 2022 paper (370 e-mail addresses).

In summary, the final e-mail recipient list in the first block contained 502 unique e-mail addresses to potential respondents (Fig.  1 ). Non-responders were sent a total of five reminders during the time for data collection.

Flowchart describing structure for collection of the final data set

Before completing the survey, participants were asked to contribute with e-mail addresses to additional colleagues in their hospital or neighboring hospitals who they believed fulfilled the above inclusion criteria. Respondents not fulfilling the inclusion criteria were given the option to decline participation but still contribute with e-mail addresses to suitable colleagues. New e-mail addresses were added in blocks and generated in total five consecutive groups with new e-mail addresses to whom the survey was distributed. With this modified snowball sampling method, it was possible to control response rates. The study size was reached when no more new e-mail addresses were added by respondents with the snowball method, and no more non-respondents answered the survey despite multiple reminders. Respondents were pseudonymized at analysis and no patient data was recorded.

Respondents are by definition fluent in both Swedish and English as this is a criterion for admission to medical training in Swedish universities and hospitals. The medical literature in Sweden is also predominately in English.

The Clinician Guideline Determinants Questionnaire (CGDQ) was used for data collection [ 24 ]. It is a validated instrument for preparing and evaluating implementation of clinical practice guidelines. The CGDQ includes four sections exploring: 1) clinician demographic and background information; 2) attitudes to known determinants of guideline use; 3) open-ended items on additional determinants; and 4) a section examining preferred ways of distribution, access, and character of a guideline. The CGDQ was transcripted unchanged from the original version and presented in English in a digital questionnaire in the web-based survey system EsMaker (Entergate AB). As respondents have a high knowledge of the English language, we judged the risks associated with a translation of the questionnaire to Swedish greater than the risk that respondents would not understand the questions. Three questions exploring what size and type of hospital the respondent worked in, type of patients (children/adults/both) they managed, and their familiarity with assessing children with head injury were added to the background information section by the authors. The SNC-16 flow chart, a link to the original publication, and a link to an article in the Swedish medical journal Läkartidningen were presented at the beginning of the questionnaire [ 14 , 26 ]. The text “SNC-16 guideline” was inserted in the questionnaire where stated, “name guideline”. Some items have been truncated to improve readability in the results section of this paper, with a reference to the full questionnaire and complete items in Additional file 2.

To minimize the risk for introducing selection bias, purposive sampling was used to include respondents from varying parts of Sweden and from varying hospital sizes, and including both junior and senior physicians, when compiling the initial respondent mailing list.

Data analysis

Reported data are categorical nominal/dichotomous or categorical ordinal (on a 7-step Likert scale, including response option “not sure”), or in free text. Responses to categorical nominal items are summarized and presented as frequencies and percentages. Variables that are reported on an ordinal 7-step Likert scale were dichotomized into “disagree” if Likert response 1–4 or unsure, and into “agree” if Likert response 5–7. The unmerged response distribution is shown in Additional file 3. Results are presented for the four sections in the applied implementation tool (CGDQ). Merging of categories was performed if there were few responses in a response category.

Background data on respondents are presented descriptively for a) gender, b) career stage (as found most appropriate by the respondent), c) medical specialty, d) hospital category (local hospital, regional hospital, university hospital or children’s hospital – with local and regional merged as small hospitals and university and children’s as large), e) region in Sweden, f) managing only children or both children and adults, g) familiarity with assessing children with head injury (categorized as “daily” + “several times a week” = regularly; “1–3 times/month” = seldom; “5–10 times/year” + “1–4 times/year” + “less than once a year” = rarely), h) have participated in the development of one or more guidelines, i) belief in clinical benefit of guidelines, and j) actual use of SNC-16 guideline.

Frequencies and percentages for "agree” and “disagree” for determinants in Sect. 2 of the survey were calculated. The authors decided to perform further analysis on a subset of factors from the clinician and guideline specific determinants in Sect. 2, aiming to explore possible associations between determinants and background factors. The subset comprised six variables selected by the authors after reviewing initial results and considered most salient to grasp the respondent’s thoughts on the guideline and their knowledge about the relevant clinical condition, with the most clinically relevant imprint. Authors decided to not test all items as it would entail an unjustified risk for significant results by chance. Chi-square test, or Fisher’s exact test when appropriate, was used to assess associations.

The free-text responses obtained from questions 3.1 to 3.4 (additional file 2) were independently categorized into types of barriers and enablers by two of the authors (FW, WB) and then compiled in consensus.

The first invitation e-mail was sent on February 23, 2023. The final reminder was sent on April 20, 2023. Respondents suggested 93 additional unique potential respondents, resulting in invitations also sent to these individuals. In this group, 43 participants opened the e-mail and participated in the survey, yielding a response rate in the snowball sample group of 46.2%. The total response rate was 43.4% (258/595; opens and responds to request) with an effective response rate for analysable respondents of 33.3% (198/595) (Fig.  1 ).

Background information

The 198 responding physicians from 42 unique EDs had varying clinical experience, in a span from early career interns (14.1%; 28/198), mid-career residents (48.5%; 96/198), to late career consultants (37.4%; 74/198). The most common specialties represented were general surgery (52.0%; 103/198) and emergency medicine (31.8%; 63/198). A majority (82.3%; 163/198) of the respondents worked in small (local or regional hospitals) compared to 17.7% ( n  = 35) in large (university or children’s) hospitals. There was a high degree of familiarity with the SNC-16 guideline, as 84.3% (166/197) had “read all or some of the guideline on multiple occasions” and only 8.1% (16/197) were unaware of the guideline or “aware of the guideline but have not read it”. A high proportion (76.4%; 149/195) of respondents reported regular use of the SNC-16 guideline in their respective clinical settings, and almost all (95.4%; 188/197) believed that guideline use in general optimized healthcare delivery and outcomes (Table  1 ).

Determinants of guideline use

It was common among respondents to think that colleagues (77.8%; 154/198) expected them to use the SNC-16 guideline. Fewer believed that patients (12.1%; 24/198), managers/executives in their own organization (37.9%; 75/198), a monitoring agency (Swedish National Board of Health and Welfare: 15.7%; 31/198), the government (4.0%; 8/198), and/or the professional society (23.7%; 47/198) expected them to use the guideline.

The attitude towards use of the SNC-16 guideline was generally positive as 94.9% (187/197) agreed with the content of the guideline. Approximately one of four (26.9%; 53/197) disagreed to the statement “My organization provides support (leadership, resources, assistance, etc.) needed to use this guideline”. In statement Q2.25 and Q2.27, the respondents’ perceptions of the guideline’s consistency with available evidence and how clearly the guideline describes this underlying evidence as foundation for the recommendations was explored, and the uncertainty was relatively high for both statements (“Not sure”: 37.2%; 73/196, and 47.2%; 93/197 respectively) (Table  2 ).

Enablers and barriers

Four types of enablers for guideline use emerged from the compilation of the free-text responses: ease of use and implementation, alignment with local guidelines and practice, advantages for stakeholders, and practicality and accessibility. Barriers for guideline use were manifested as: organizational challenges, medical concerns , and practical concerns (Table  3 ).

This section provided participants an opportunity to share thoughts on other determinants that could enable or challenge their use of the guideline. Noteworthy examples of "Enablers" were suggestions to extend the formal implementation among nurses, aiming to achieve a widespread adherence and acceptance of the SNC-16 guideline within all categories of healthcare professionals managing these conditions. Regarding practical concerns, ease of accessibility, e.g. laminated plastic cards in the ED, online versions, simple and unambiguous instructions, were described as enabling use of the guideline. Additionally, the importance of including disseminated guidelines, such as the SNC-16 guideline, into official local guidelines and practices was highlighted. In a broader perspective, a suggestion to gather all relevant guidelines in a bundle of nationally endorsed clinical decision-making tools was also noted.

In contrast, the absence of official organizational endorsement, both on a local and national level, emerged as a potential barrier. A specific concern raised was the fact that many Swedish physicians use the Reaction Level Scale-85 (RLS-85) [ 27 ], as opposed to the Glasgow Coma Scale (GCS) [ 28 ] recommended in the SNC-16 guideline, for assessment of level of consciousness. This discord was suggested as a barrier to adopting the SNC-16 guideline rising from inexperience in using the GCS. Challenges related to organizational practices, such as the absence of observational units and ED overcrowding, were identified as barriers affecting guideline adherence, possibly instead increasing the use of CT scanning. Within the category of medical concerns , participants expressed concern about the risk of over-investigation, encompassing both excessive observation and CT scans, and that the guideline might result in decisions that contradict the clinical judgement of experienced physicians. Concerns about the lack of clinical validation and available evidence were also raised by the respondents. The "practical concerns" category was composed around issues of complexity of guideline, time constraints, and limited availability.

In summary, the free-text responses confirmed already reported key enablers and barriers. They also provided new suggestions regarding the value of interdisciplinary collaboration among healthcare professionals and the importance of organizational structures for guideline adherence.

Learning style

Most of the respondents reported a preference for consulting colleagues (89.9%; 178/198), guidelines (75.3%; 149/198), and the internet (65.2%; 129/198) to gain knowledge to guide their clinical decisions (Fig.  2 ). Educational meetings/conferences were the most popular way to learn about guidelines (78.3%; 155/198) (Fig.  3 ). No clear preference was apparent regarding the optimal format for distribution of guideline material (Fig.  4 ).

Key sources to guide clinical decision making. 198 respondents provided answers to the multiple-choice question (4.1 in additional file 2) about the usefulness of different sources when seeking support to guide clinical decision-making. *Other = Foamed (free open access medical education) and local guidelines ( n  = 2)

Preferred ways to learn about guidelines. A total of 198 respondents provided answers to this multiple-choice question (4.2 in additional file 2). *Other = Suggested national Swedish collection of guidelines, podcasts, official medical guideline database (“Internetmedicin”), educational lunch sessions, colleagues ( n  = 6)

Preferred formats for guidelines, guideline summaries, or guideline tools ( n  = 198, multiple choice)

Associations to demographic variables

Associations between background variables and a subset of determinants were explored in Table  4 . There were significant differences between respondents that managed pediatric head injuries regularly, seldom, or rarely in their view of whether following the SNC-16 guideline would improve care delivery (91%; 79/87 versus 94%; 90/96 versus 73%; 11/15) and their view on the support provided from their organization to enable them to use the guideline (73%; 63/86 versus 52%; 50/96 versus 47%; 7/15). Those respondents that believed that guidelines (in general) optimize healthcare delivery and outcomes also had a significantly higher belief in that following the SNC-16 guideline would improve delivered care. There were no significant differences regarding gender, career stage, specialty, size of hospital, location of the respondent’s hospital in Sweden, types of patients managed, or whether the respondent had experience in guideline development for the selected determinants.

This cross-sectional survey showed that reported regular use of the passively disseminated SNC-16 guideline for pediatric mTBI was high. The respondents also held a high belief in patient benefit if applying the guideline. Improvements in the reporting of the underlying evidence and appurtenant implementation tools were requested. Barriers, such as lack of organizational support and resources, emerged both in the qualitative and quantitative data. The conveyed perception of determinants for use of the SNC-16 guideline was generally homogenous among the respondents, and independent of varying grouping variables.

The high proportion of regular guideline use (76%) reported in this study is in contrast to other reports, with only 35% adhering to guidelines in a systematic review by Mickan et al. [ 29 ] and 43% of prenatal care physicians regularly using a hepatitis C virus screening guideline in a survey by Moore et al. [ 30 ]. In a recent report on management routines at an organizational level, 55% of Swedish hospitals based their local recommendation in part or fully on the SNC-16 guideline [ 13 ]. The reason for this seemingly successful non-facilitated dissemination of the SNC-16 guideline in Sweden is unclear, although some plausible causes can be hypothesized. There is a lack of alternative, validated guidelines in Scandinavia. Also, the guidelines were published in the most common national journal and on the most commonly used web tool for doctors [ 26 , 31 ]. Additionally, a recent, non-intervention multi-center study, validated a set of pediatric mTBI guidelines in the Scandinavian healthcare system [ 32 ].

Pathman et al. [ 33 ] developed a four-step model for “leakage” of guideline evidence, from awareness to final adherence, outlining the concept of progressive loss of research evidence from guideline publication to clinical practice. The drop-off, or “leakage”, in each step of the Pathman model was estimated to be 15% in the systematic review by Mickan et al. [ 29 ]. The first step, awareness of the SNC-16 guideline, is not explicitly measured in the CGDQ. The second step is agreement with the content. If assuming that “regular use” corresponds to adoption or adherence in the Pathman framework, the leakage in this study would be between 9.25% ( agreement to adoption to adherence ) and 18.5% ( agreement to adoption ). This may raise attention to a possible, although not ascertained, discrepancy worth some effort to address in future updates of the guideline, also when considering the design of an implementation strategy. There was, for example, an uncertainty among our respondents concerning the guideline’s consistency with available evidence, which may act as a barrier for adoption and adherence. The guideline format and layout were acknowledged as easy to navigate, with clear and unambiguous wording, which may on the other hand facilitate adoption and adherence and efforts to preserve it may be beneficial [ 17 ].

In pediatric guidelines for mTBI, there has been a successive development from dichotomous prediction models based on single assessments [ 34 , 35 ], to risk group stratification at several levels (three to five) at one single time-point [ 5 , 14 ], and more recently to multiple risk groups and assessments at several time-points under observation in ED [ 36 ]. Whether the ambition to increase diagnostic accuracy via increasingly complicated flow chart structures will, at some point, limit the accessibility, final adoption and adherence to a guideline remains to be investigated, even though there have been dedicated efforts to investigate optimal implementation pathways and implementation outcome for newer mTBI guidelines both in Australia/New Zealand [ 36 , 37 ] and the US [ 38 , 39 , 40 , 41 , 42 ]. Among the Swedish respondents, a high belief in the benefit for the patients of using the SNC-16 guideline was reported in this study, which may imply that the basic flowchart structure of the clinical decision rule that is central to the guideline is feasible for the Scandinavian setting. A recent systematic review of trends in guideline implementation showed that even if more studies investigate and tailor interventions to facilitate implementation of a guideline, with most studies reporting effect, studies that did not plan specific implementation measures also achieved impact [ 20 ]. Causes for a seemingly successful dissemination of the SNC-16 guideline could therefore be numerous.

Potential barriers for implementation of the SNC-16 guideline could be identified within different types of determinants. Over one quarter of our respondents stated a lack of organizational support needed to use the guideline. Organizational barriers affect uptake of recommendations and a top-down drive of change from medical managers is likely important for adoption of a guideline, identifying team and organization leaders as a target for interventions in future implementation planning [ 39 , 43 ]. Lack of resources (e.g., observational units, CT accessibility) also seems to pose an organizational challenge in Swedish health care.

Another relevant issue are the implementation tools accompanying the SNC-16 guideline. Respondents were unsure about which tools are included in the guideline and the helpfulness of these tools. This uncertainty was also expressed as a barrier in the free-text answers. Many respondents seem to prefer electronic tools and further improvements may include development of electronic educational tools/websites and integration with electronic health record-based systems, an aspect that has been identified in other populations [ 37 , 38 , 39 , 41 ]. The need for developing more concise implementation tools, both digital and in print, was identified in an interview study investigating experience and use of the CDC pediatric mTBI guidelines in rural areas in US [ 38 ]. Recently, an evaluation of a generic model to integrate decision aids for shared decision making into electronic evidence summaries with adjacent guidelines showed promising results and may be applicable also for pediatric TBI in the future [ 44 ]. Another area amenable to improvements is the description of the underlying evidence supporting the recommendations, where only 37.6% agreed that the description was clear. This finding is in contrast to a survey by Sawka et al. [ 45 ], also using the CGDQ, which showed that 92.3% agreed that the evidence underlying the evaluated US thyroid guideline was clearly described.

More than half of the respondents sought guidance for their clinical decision-making from colleagues (90%), guidelines (75%), or the internet (65%) and preferred to learn about guidelines via educational meetings and conferences (78%). Sawka et al. [ 45 ], reported somewhat different results regarding the thyroid guideline, where the most common sources for knowledge were medical literature (88.1%), guidelines (87.2%), and colleagues (65.6%). The reported need for discussion with colleagues and learning via meetings/conferences may underscore the need for understanding stakeholders’ views of how to manage mTBI in children. Many respondents were unsure about practice in other settings, and educational meetings may fill an important knowledge gap in this respect. Daugherty et al. [ 38 ], who evaluated the implementation of the CDC pediatric mTBI guideline in a rural area in the US, identified a perceived lack of access to mTBI specialists and discussed the telemonitoring ECHO model as an example where health care providers could meet in a virtual community and discuss cases. There are reports on the application of this model in pediatric emergency care and pediatric mTBI [ 46 , 47 ]. In a recent systematic review, education of professionals was a commonly utilized intervention in guideline implementation planning [ 20 ]. Another review by Chan et al. [ 48 ] reported a positive impact through specific interventions, namely educational outreach, audit, and feedback. There was a significant association between familiarity with assessing pediatric mTBI and the perceived benefit of adherence to the recommendations. This association might be explained by senior physicians managing this condition more seldom, and when doing so relying on their clinical judgement and solid experience rather than a clinical practice guideline [ 37 ].

There are several limitations to consider when interpreting the results from this survey. The low total response rate of 43.4% (analyzable response rate 33.3%) implies a potential responder bias. The high reported use of the guideline could be an effect of sampling bias due to the modified snowball sampling method, for example if the respondents more commonly recommended colleagues with similar education, value base, or within the same organization. Nevertheless, our sampling strategy and different e-mail address collection strategies offered a good opportunity to maximize and optimize respondent relevance by drawing on snowball sampling, the ED physician community, and the ongoing guideline implementation. The background information does not, however, indicate a widespread bias among respondents as the distribution of gender, career stage, category of hospital, part of Sweden, and types of patients managed is reasonable from a Swedish healthcare perspective. Another risk worth mentioning is that of contamination, in the form of an observer effect. There has been an intense focus in Sweden on pediatric mTBI management as an effect of the ongoing guideline validation efforts. The validation study [ 32 ] is strictly observational but has inevitably set focus on the SNC-16 guidelines and the investigators behind these. However, the use of an e-mail recipient list from the 2022 study [ 13 ] is unlikely to have contaminated the responses as there was only one respondent from each of the 66 hospitals in that study. Another limitation is the cross-sectional design, addressing the physicians’ perceptions of their own actions, leaving room for deviation from the reported views in actual patient management decisions.

This cross-sectional survey on determinants for use of the Scandinavian guideline for management of mild and moderate head injury in children suggests that use of the guideline is high in our sample of ED providers in Sweden. In updated versions of the guideline, focus on improving implementation tools and descriptions of the underlying evidence may further facilitate adoption and adherence. Measures to improve organizational support for guideline use and involvement of patient representatives should also be considered.

Availability of data and materials

Pseudonymized datasets used and analyzed during the current study are available from the corresponding author on reasonable request.

Abbreviations

Scandinavian Neurotrauma Committee

Computed tomography

Emergency department

Clinical Guideline Determinants Questionnaire

Mild traumatic brain injury

Glasgow Coma Scale

Reaction Level Scale -85

Centers for Disease Control

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Acknowledgements

We would like to thank the respondents in this survey for their valuable contribution and Region Halland for ongoing support with research efforts, especially the FoUU department.

Open access funding provided by Lund University. This study was non-commercially funded by the research and development department at Halland Hospital (FoUU Halland), Sweden.

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Contributions

FW, LP, SB and JU conceived and planned the study. FW, LP and WB developed the electronic questionnaire. FW and WB compiled the respondent list. WB collected the data, with supervision by FW. FW and WB analyzed the data, summarized the results, and wrote the first draft. SK contributed with statistical supervision throughout the process. SB and JU contributed with critical review of the manuscript. All authors have read and approved the final manuscript.

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Correspondence to Fredrik Wickbom .

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The study does not include individual patient or respondent data. Ethical advisory opinion/permission was granted by the Swedish Ethical Review Authority (Dnr 2020 – 02 693) and informed consent was given by each respondent as they fulfilled the electronic questionnaire.

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Competing interests

None of the authors have any financial competing interests. SB participated in the development of the Clinician Guideline Determinants Questionnaire. JU is a member of the SNC committee, a non-profit organization independent from financial company support, who are responsible for the SNC-16 guidelines.

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Wickbom, F., Berghog, W., Bernhardsson, S. et al. Pediatric head injury guideline use in Sweden: a cross-sectional survey on determinants for successful implementation of a clinical practice guideline. BMC Health Serv Res 24 , 965 (2024). https://doi.org/10.1186/s12913-024-11423-z

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DOI : https://doi.org/10.1186/s12913-024-11423-z

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