stress and health research paper

Stress and Health: A Review of Psychobiological Processes

Affiliations.

• 1 School of Psychology, University of Leeds, Leeds LS2 9JT, United Kingdom; email: [email protected].
• 2 Department of Psychological Science, School of Social Ecology, University of California, Irvine, California 92697, USA; email: [email protected].
• 3 Division of Primary Care, School of Medicine, University of Nottingham, Nottingham NG7 2UH, United Kingdom; email: [email protected].
• PMID: 32886587
• DOI: 10.1146/annurev-psych-062520-122331

The cumulative science linking stress to negative health outcomes is vast. Stress can affect health directly, through autonomic and neuroendocrine responses, but also indirectly, through changes in health behaviors. In this review, we present a brief overview of ( a ) why we should be interested in stress in the context of health; ( b ) the stress response and allostatic load; ( c ) some of the key biological mechanisms through which stress impacts health, such as by influencing hypothalamic-pituitary-adrenal axis regulation and cortisol dynamics, the autonomic nervous system, and gene expression; and ( d ) evidence of the clinical relevance of stress, exemplified through the risk of infectious diseases. The studies reviewed in this article confirm that stress has an impact on multiple biological systems. Future work ought to consider further the importance of early-life adversity and continue to explore how different biological systems interact in the context of stress and health processes.

Keywords: HPA axis; allostatic load; autonomic nervous system; cortisol; genomics.

Publication types

• Autonomic Nervous System / metabolism
• Hydrocortisone / metabolism
• Hypothalamo-Hypophyseal System / metabolism
• Pituitary-Adrenal System / metabolism
• Stress, Psychological / metabolism*
• Hydrocortisone

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• Published: 09 January 2023

Effect of breathwork on stress and mental health: A meta-analysis of randomised-controlled trials

• Guy William Fincham 1 ,
• Clara Strauss 1 , 2 ,
• Jesus Montero-Marin 3 , 4 , 5 &
• Kate Cavanagh 1 , 2  

Scientific Reports volume  13 , Article number:  432 ( 2023 ) Cite this article

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Deliberate control of the breath (breathwork) has recently received an unprecedented surge in public interest and breathing techniques have therapeutic potential to improve mental health. Our meta-analysis primarily aimed to evaluate the efficacy of breathwork through examining whether, and to what extent, breathwork interventions were associated with lower levels of self-reported/subjective stress compared to non-breathwork controls. We searched PsycInfo, PubMed, ProQuest, Scopus, Web of Science, ClinicalTrials.gov and ISRCTN up to February 2022, initially identifying 1325 results. The primary outcome self-reported/subjective stress included 12 randomised-controlled trials ( k  = 12) with a total of 785 adult participants. Most studies were deemed as being at moderate risk of bias. The random-effects analysis yielded a significant small-to-medium mean effect size, g  = − 0.35 [95% CI − 0.55, − 0.14], z  = 3.32, p  = 0.0009, showing breathwork was associated with lower levels of stress than control conditions. Heterogeneity was intermediate and approaching significance, χ 2 11  = 19, p  = 0.06, I 2  = 42%. Meta-analyses for secondary outcomes of self-reported/subjective anxiety ( k  = 20) and depressive symptoms ( k  = 18) showed similar significant effect sizes: g  = − 0.32, p  < 0.0001, and g  = − 0.40, p  < 0.0001, respectively. Heterogeneity was moderate and significant for both. Overall, results showed that breathwork may be effective for improving stress and mental health. However, we urge caution and advocate for nuanced research approaches with low risk-of-bias study designs to avoid a miscalibration between hype and evidence.

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Introduction.

Breathwork comprises various practices which encompass regulating the way that one breathes, particularly in order to promote mental, emotional and physical health (Oxford English Dictionary) 1 . These techniques have emerged worldwide with complex historical roots from various traditions such as yoga (i.e., alternate nostril breathing) and Tibetan Buddhism (i.e., vase breathing) along with psychedelic communities (i.e., conscious connected breathing) and scientific/medical researchers and practitioners (i.e., coherent/resonant frequency breathing). Recently, breathwork has been garnering public attention and popularity in the West due to supposed beneficial effects on health and well-being 2 in addition to the breathing-related pathology of covid-19, however it has only been partly investigated by clinical research and psychiatric medical communities.

Slow-paced breathing practices have gained most research attention thus far. Several psychophysiological mechanisms of action are proposed to underpin such techniques: from polyvagal theory and interoception literature 3 along with enteroception, central nervous system effects, and increasing heart-rate variability (HRV) via modulation of the autonomic nervous system (ANS) and increased parasympathetic activity 4 . ANS activity can be measured using HRV, the oscillations in heart rate connected to breathing (i.e., the fluctuation in the interval between successive heart beats) 5 . Fundamentally, as one inhales and exhales, heart rate increases and decreases, respectively. Higher HRV, arising from respiratory sinus arrhythmia 6 , is typically beneficial as it translates into robust responses to changes in breathing and thus a more resilient stress-response system 7 .

Stress-response dysfunction, associated with impaired ANS activity, and low HRV are common in stress, anxiety, and depression 8 , 9 , 10 , 11 , 12 . This may explain why techniques like HRV biofeedback can be helpful 13 , however, it is possible that simply pacing respiration slowly at approximately 5–6 breaths/minute, requiring no monitoring equipment, can elicit similar effects 14 . Polyvagal Theory 3 , for instance, posits that vagal nerves are major channels for bidirectional communication between body and brain. Bodily feedback has profound effects on mental states as 80% of vagus nerve fibres transmit messages from body to brain 15 . Further, the neurovisceral integration model states that high vagal tone is associated with improved health along with emotional and cognitive functioning 16 , 17 . Vagal nerves form the main pathway of the parasympathetic nervous system, and high HRV indicates greater parasympathetic activity 7 .

Modifying breathing alters communication sent from the respiratory system, rapidly influencing brain regions regulating behaviour, thought and emotion 18 . Likewise, respiration may entrain brain electrical activity 19 , with slow breathing resulting in synchrony of brain waves 20 , thereby enabling diverse brain regions to communicate more effectively 21 . It has been observed that adept long-term Buddhist meditation practitioners can achieve states where brain waves are synchronised continuously 22 .

Breathwork and stress

Stress, anxiety and depression have markedly exceeded pre-covid-19 pandemic population norms 23 . Thus, research is needed to address how this can be mitigated 24 . A recent survey based on more than 150,000 interviews in over 100 countries suggested that 40% of adults had experienced stress the day preceding the survey (Gallup, US) 25 . Prior to the pandemic, mental health difficulties were already a significant issue. For instance, stress has been identified by the World Health Organisation as contributing to several non-communicable diseases 26 and a 2014 survey, led in collaboration with Harvard, of over 115 million adults showed that 72% and 60% frequently experienced financial and occupational stress, respectively (Robert Wood Johnson Foundation, US) 27 .

Chronic stress is associated with, and can significantly contribute to, many physical and mental health conditions, from hypertension and cardiovascular disease to anxiety and depression 28 . For common mental health problems such as anxiety and depression, cognitive behavioural therapy (CBT) is widely recommended in treatment guidelines worldwide 29 , 30 , yet many do not recover and waiting times can be long 31 , 32 , in addition to extensive professional training and ongoing supervision being required for therapists. Moreover, such treatment is typically individualised and offered on a one-to-one basis making it resource intensive. The present state of global mental health coupled with the access barriers to psychological therapies requires interventions that are easily accessible and scalable 7 , and manualised practices such as breathwork may meet this remit.

Breathing exercises can be easily taught to both trainers and practitioners, and learned in group settings, increasingly via synchronous and asynchronous methods remotely/online. Therefore, given the need for effective treatments that can be offered at scale with limited resources, interventions focusing on deliberately changing breathing might have significant potential. Indeed, some government public health platforms already recommend deep breathing for stress, anxiety and panic symptoms (NHS and IAPT, UK) 33 , 34 . However, the evidence underlying this recommendation has not been scrutinised in a comprehensive systematic review and meta-analysis and this is the aim of the current study.

Moreover, it is not only slow-paced breathing which may help reduce stress. Fast-paced breathwork may also offer therapeutic benefit as temporary voluntarily induced stress is also known to be beneficial for health and stress resilience. For example, regular physical exercise can improve stress, anxiety and depression levels 35 , along with HRV 36 . Similarly, fast-paced breathing techniques can induce short-term stress that may improve mental health 37 , and have also been shown to volitionally influence the ANS, promoting sympathetic activity 38 . There are countless breathwork techniques—and such variation in their potential modalities and underlying principles warrants exploration.

Review aims

It is important that hype around breathwork is grounded in evidence for efficacy—and effects are not overstated to the public. Whilst some previous reviews of breathwork have been published, it is not possible to conclude the effectiveness of breathwork for stress (nor mental health in general) based on previous meta-analyses, since they have been restricted by certain factors. These include focusing on populations with impaired breathing (i.e., chronic obstructive pulmonary disease—COPD, and Asthma) 39 , 40 , insufficient focus on the breathwork intervention itself (i.e., including interventions where breathwork is combined with several other intervention components) 41 making it hard to elicit separate effects, along with spanning more literature on self-reported/subjective anxiety and depression compared to stress 14 . On the other hand, systematic reviews with narrative syntheses of quantitative data may have overlooked key studies because of too much focus on a specific technique (i.e., slow breathing or diaphragmatic breathing) 4 , 42 , an absence of randomised-controlled trials (RCTs), scanter literature on self-reported/subjective stress compared to self-reported/subjective symptoms of anxiety and depression, along with limited databases 4 , or exclusion of unpublished studies and grey literature (i.e., theses/dissertations) 43 .

Furthermore, in keeping with the participant, intervention, control, outcome and study design (PICOS) framework 44 , there is an absence of examining dose–response correlates with effects and subgroup analyses evaluating differential effects of different breathwork interventions and how they were delivered, what controls were used, effects on populations with differing health statuses and, finally, the psychological outcome measures used. All of these are crucial for an adequate ethical, precautional and practical implementation of breathwork interventions. Accordingly, subgroup analyses were explored to account for these, for the primary outcome of stress. It could be relevant to investigate potential sources of heterogeneity in terms of effects on stress, and this might be related to how some subgroups (such as mental/physical health populations, along with nonclinical/general populations) receive the intervention. Moreover, other subgroups such as the type of breathwork intervention (i.e., slow/fast) and how it is delivered (i.e., online/in-person or individual/group-based), along with the type of comparator (active/inactive control) and outcome measure (questionnaire) used to self-report on stress, may be sources of heterogeneity and thus warrant investigation.

So far, there is no existing meta-analysis of RCTs on the effect of breathwork on psychological stress. Thus, to fill this research gap, the aim of our meta-analysis was to estimate the effect of breathwork in targeting stress. Because prolonged stress can significantly contribute to anxiety and depressive symptoms and there is considerable overlap between them 45 , 46 , we included these two common mental health issues as secondary outcomes, to provide a bigger picture and greater context around the findings on stress. The primary outcome was pre-registered as stress since it is a transdiagnostic variable, relevant in a variety of disorders, and also in people without a diagnosis but suffering from high levels of psychological distress 47 . This makes stress a very interesting target for breathwork-based interventions.

In brief, our research question was the following: do breathwork interventions lead to lower self-reported/subjective stress (primary outcome), anxiety, and depression (secondary outcomes) in comparison to non-breathwork control conditions? We propose this work as a first comprehensive systematic review and meta-analysis exploring the effects of breathwork on stress and mental health, to help lay a solid foundation for the field to grow and evolve in an evidence-based manner.

We focused solely on RCTs reporting psychological measures, to gauge any potential efficacy or effectiveness of breathwork. We also explored sub-analyses for stress outcomes depending on the health status of the study population, technique, and delivery of breathwork, along with types of control groups and stress outcome measures used. Finally, we examined dose–response effects of breathwork on stress.

Pre-registration and search strategy

Our meta-analysis was pre-registered on the international prospective register of systematic reviews PROSPERO (2022 CRD42022296709). Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) standards were applied throughout. We searched published, unpublished, and grey literature in the following five databases: PsycInfo, PubMed, ProQuest, Scopus, and Web of Science, along with two clinical trial registers: ClinicalTrials.gov and ISRCTN. The search was run up to February 2022 for all seven electronic repositories, with no date restrictions, in line with the search criteria pre-registered on Prospero, including keywords such as: breath*, respir*, random*, RCT, and stress (see Online Appendix A for the detailed search). For purposes of feasibility in conducting the search, we maintained our focus on the pre-registered primary outcome, following Cochrane Collaboration guidelines to meet the highest criteria for self-reported/subjective stress outcomes by searching trial registers for unpublished studies. There is limited search functionality on trial registers and time involved in contacting researchers for trial data. Moreover, as mentioned above, some previous reviews have not searched unpublished, grey literature before and there are less data available on breathwork and self-reported/subjective stress, in comparison to self-reported/subjective anxiety and depression. In brief, given our focus on stress (paired with time and resource constraints), we conducted the most robust search possible for the primary outcome whilst secondary outcomes only included published data—and we were explicit about this from pre-registration onwards.

Inclusion and exclusion criteria

Inclusion criteria were that studies: (1) were published in the English language, (2) included a breathwork intervention where breathwork formed 50% or more of the intervention (and home practice/self-practice, if any), (3) were RCTs, (4) included an outcome measure of self-reported/subjective stress, anxiety, or depression, (5) included an adult participant sample 18 + years of age. For the five databases, studies with abstracts that did not include either the primary outcome keyword (stress), or a secondary outcome keyword (anxiety or depression), were excluded. For the two registers, if it was clear from the summary information that trials did not comprise the primary outcome of stress, they were excluded. As mentioned above, stress is a transdiagnostic health variable, relevant across various (clinical and nonclinical) populations and conditions, hence it was our primary interest. Additional rationale included the fact that there is far more limited research literature available on self-reported/subjective stress and breathwork (as opposed to anxiety and depression) and, since this was the primary outcome, because fewer (published) data were available, and to make the secondary search (which was only used in the present study to contextualise findings) more feasible, we used the referred search strategy, as this allowed us to find more information on stress from unpublished sources.

For all electronic repositories, studies with control conditions that comprised components of breathwork were excluded, except for studies which had time-points wherein data were collected before controls participated in breathwork (i.e., crossover RCTs). Only non-breathwork controls were used as post-intervention comparisons. Studies with interventions that comprised of equipment (oronasal or otherwise) which physically altered and/or assisted breathing activity were excluded. Breathwork was operationalised as techniques which involved conscious and volitional control or manipulation of one's breath (depth, pattern, speed or otherwise) through deliberate breathing practices. Interventions that affected breathing as a by-product, e.g., mindfulness, singing, and aerobic exercise, were excluded.

Review strategy and study selection

The first author conducted the search and initial screening against eligibility criteria along with full-text screening. Records were then screened, excluding reports based on review of titles and keywords in abstracts or summary information (for trials), or if the inclusion criteria were not met. Remaining reports were sought for retrieval and the full-text reports assessed for eligibility, before final eligibility decisions were made. Further identification of studies comprised forward and backward citation searching via Google Scholar and reference lists, respectively, of the final reports included from the database/registry search. For inter-rater consistency purposes, one of the authors (JMM) checked a random sample (10% of reports) after duplicates had been removed. Furthermore, where GWF was unsure after full-text screening, they consulted authors KC and CS to come to a collective decision on eligibility. Any discrepancies between authors were resolved by discussion and reaching consensus.

Data extraction

Our primary outcome was self-reported/subjective stress. Secondary outcomes were self-reported/subjective anxiety, depression, and global mental health (where two or more of stress, anxiety and depression were combined into a total measure without providing subscale data). We extracted the following data across the studies’ conditions: sample sizes, means, and standard deviations of outcome scores post-intervention (timepoint 1—T1, where T0 is pre-intervention/baseline) along with at latest follow-up where possible (a true follow-up was classed as when participants no longer received any instruction for the breathwork intervention). Where studies involved crossover designs, the midpoints were categorised as post-intervention (before the control group started the breathwork given initially to the intervention group). For studies which required multiple groups’ mean and standard deviation (M ± SD) scores to be combined, or for just SDs to be calculated, these were calculated in accordance with the Cochrane Collaboration handbook 48 . For example, calculating SDs from Ms and 95% confidence intervals (CIs) or combining multiple groups’ M ± SD scores if two or more groups completed an intervention that involved breathwork (but the study still comprised a non-breathwork control).

Risk of bias and quality assessment

The most recent, revised Cochrane Collaboration’s tool for assessing risk of bias in randomised trials (RoB 2) 49 was used for analysing studies on the primary outcome measure of self-reported/subjective stress. The studies were analysed across the following five domains for the stress outcomes: randomisation process, deviations from intended interventions, missing outcome data, measurement of the outcome, and selection of the reported result. Each domain produced an algorithmic judgement of “low risk of bias”, “some concerns”, or “high risk of bias”, resulting in an overall risk of bias judgement. For further inter-rater consistency purposes, both JMM and GWF completed bias scoring using RoB 2 on all included studies for stress, with any discrepancies resolved via discussion.

Data synthesis and analysis

To evaluate whether breathwork can effectively lower stress compared to non-breathwork controls and to quantify the estimation we ran a quantitative synthesis meta-analysis using standardised mean differences and a random-effects model. This used aggregate participant data of M ± SD scores on stress outcome measures for intervention and control conditions of each study at post-intervention (T1), along with the groups’ sample sizes. We also conducted a sensitivity analysis by removing one study at a time, to evaluate the robustness of effects. Separate random-effects meta-analyses were run for the secondary outcomes. The software Review Manager (RevMan) version 5.4 50 was used. For the between-group effect sizes (ESs) we computed Hedges’ g , based on the standardised between-group difference at post-intervention considering sampling variance among groups; an ES of 0.2 is classed as small, 0.5 medium and 0.8 large 51 . For each separate outcome, the ESs were calculated via comparison of post-breathwork intervention scores between the conditions. Intention-to-treat data were chosen over per-protocol data where available, since the former provides a more conservative estimate of between-group differences.

Heterogeneity of ESs variance was assessed using Cochran’s Q 52 based on a chi-square distribution ( χ 2 ) and Higgins’ I 2 53 . If χ 2 is significant and an I 2 index value is around 50%, this implies variance may be explained by variables other than breathwork and such statistical heterogeneity is moderate, respectively. A funnel plot was produced to examine publication bias for the primary outcome, and the software R (version 4) 54 was used to explore asymmetry of the funnel plot via the Egger’s test 55 (i.e., correlations between standard error and ESs). Moreover, Rosenthal’s fail-safe N was calculated (to estimate how many further studies yielding zero effect would be required to make the overall ES non-significant for stress) 56 . Kendall's tau-b (τ B ) correlations were used to detect any potential relationships between ESs of breathwork on stress and: estimated total duration of intervention/home practice, total number of intervention/home practice sessions, and intervention/home practice session frequency. If intervention time was not provided by a study (where participants only had home practice), we used the minimum estimated home practice duration (recommended in the study) to gauge the approximate time taken for participants to ‘learn’ the breathwork technique. Minimum recommended duration was used for most conservative estimates, helping account for common attrition found across behavioural studies.

Lastly, subgroup analyses were run for stress, again using a random-effects model. These subsets included: health status of population (physical, nonclinical, or mental health), technique type (fast or slow-paced breathing) and delivery method of the breathwork intervention (individual, group, or a combination of both, and remote (self-help), in-person, or combination) along with the type of control group (active or inactive; in line with Cochrane Collaboration guidelines 48 ), and outcome measure used (scale).

Search results

As shown in Fig.  1 , the search produced 1325 results: 1175 and 150 records from databases and registers, respectively. After duplicates were removed, the titles and abstracts (or summary information for registers) of 679 records were screened. During screening, the eligibility of 11% of reports were decided collectively among GWF, KC, and CS. All studies included by GWF were checked by KC and CS to ensure none were incorrectly included. One particular study 57 that comprised a global mental health measure only had to be excluded as there were insufficient studies to reliably interpret results ( n  < 5) 58 —the only other available was Goldstein et al. 59 (which also included a measure of self-reported/subjective stress). Accordingly, the global mental health secondary outcome was dropped from the analysis.

PRISMA flow diagram showing the identification of eligible studies via databases, registers, and citation searching. Self-reported/subjective stress was the primary outcome for the quantitative synthesis random-effects meta-analysis. Total number of included studies was 26. Trial registries searched primary outcome only.

Further data were required for eight reports; corresponding authors were contacted, and data from four studies were retrieved, but not the remaining half 60 , 61 , 62 , 63 subsequently excluded from the analysis. Thus, a total of 104 reports were screened and 81 were excluded, leaving 23. As a result of citation searching, a further three studies were included. Of the 26 total reports included in the quantitative synthesis meta-analyses, stress comprised 12 studies 59 , 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 , 72 , 73 , 74 . Secondary outcomes of self-reported/subjective anxiety and depression comprised of 20 studies 64 , 65 , 66 , 67 , 68 , 69 , 70 , 72 , 73 , 74 , 75 , 76 , 77 , 78 , 79 , 80 , 81 , 82 , 83 , 84 and 18 studies 64 , 65 , 66 , 67 , 69 , 70 , 71 , 72 , 74 , 78 , 79 , 80 , 81 , 82 , 85 , 86 , 87 , 88 , respectively. Please see Online Appendix B for more information on the secondary outcomes.

Summary of findings for stress

In terms of data extraction, all studies provided raw M ± SD scores apart from two 55 , 56 where estimated marginal M ± SDs were given (raw data was requested from corresponding authors but could not be obtained). One study 65 required SDs from Ms and 95% confidence intervals (CIs) provided, both of which were calculated in accordance with Cochrane Collaboration guidelines 48 . Furthermore, another study 70 required two groups’ M ± SD scores (there was one control group and two intervention groups) to be combined and two further studies 64 , 71 involved crossover designs (hence data were extracted at the midpoints of each study before controls started the breathwork intervention). Analyses of follow-up scores were not possible for self-reported/subjective stress as there were insufficient studies for results to be reliably interpreted 58 .

The 12 studies included in the meta-analysis for the primary outcome of stress were completed from 2012 to 2021 (seven, or 60%, were conducted from 2020 onwards). Half of these studies were conducted in the US 59 , 64 , 65 , 66 , 68 , 74 , two in India 71 , 72 , one globally 73 , and one each in: Israel 70 , Turkey 67 , and Canada 69 . The average age was 41.7 (± 8.47) and 75% identified as female, since the largest study 68 was for women only. Attrition rates (after the breathwork intervention began) ranged from 3 to 40%. Participant sample sizes ranged from 10 to 150, with the total number of participants analysed being 785. The number of participants randomised to a breathwork intervention or control condition was 417 and 368, respectively. The minimum total estimated durations of an intervention/home practice ranged from 80 to 5625 min.

Half of the studies comprised physical health, five nonclinical, and one mental health samples. Ten and two studies comprised interventions with a primary focus on slow-paced breathing and fast-paced breathing, respectively. Seven were individual-based interventions, four taught to groups, and one a combination of both modes. Half were remote/self-help interventions, five in-person, and one combination. Seven and five studies had inactive and active control groups, respectively. Eight studies used the perceived stress scale (PSS) 89 , three used the stress subscale from the depression anxiety stress scale (DASS) 90 , and one used the perceived stress questionnaire (PSQ) 91 .

Risk of bias for stress

Risk of bias scoring for the 12 studies on the primary outcome is reported using RoB 2 in Fig.  2 . Three studies’ overall assessment were algorithmically scored as being at high risk of bias, with domain two (deviations from the intended interventions) contributing to most bias. The remaining nine studies’ overall risk of bias were algorithmically scored as having some concerns. Only one study did not disclose how randomisation was conducted. Most of the domains, from randomisation to selection of the reported result, were scored as having some concerns or low risk of bias. We did not find reported adverse events or lasting bad effects directly attributed to breathwork interventions; four studies (six in total including secondary outcome studies) actively reported on this. Nonetheless, regarding safety and tolerability, a small subgroup of participants in Ravindran et al.’s study 71 focusing on fast-paced breathwork in unipolar and bipolar depression reported side effects such as hot flushes, shortness of breath and/or sweating. However, these participants opted to continue the intervention and no participants dropped out of the breathwork group due to adverse effects.

Risk of bias scoring using Cochrane Collaboration’s RoB 2 tool. Green and red colours correspond to low and high risk of bias, respectively. Yellow represents some concerns. D1 Randomisation process, D2 Deviations from the intended interventions, D3 Missing outcome data, D4 Measurement of the outcome, D5 Selection of the reported result.

As shown in Fig.  3 , the random-effects meta-analysis (k  = 12) displayed a small-medium but significant post-intervention between-group ES, g  = − 0.35 [95% CI − 0.55, − 0.14], z  = 3.32, p  = 0.0009, denoting breathwork was associated with lower levels of self-reported/subjective stress at post-intervention than controls. There were insufficient studies including follow-up measures for a meta-analysis. Heterogeneity was moderate but non-significant, χ 2 11  = 19, p  = 0.06, I 2  = 42%. Via removing one individual study at a time, the ES of breathwork on stress ranged from − 0.27 to − 0.39 and remained significant in all cases. Initial visual inspection of the funnel plot in Online Appendix  C suggested some skew due to studies with small samples; however, the Egger’s test was non-significant, z  = 0.03, p  = 0.947, indicating a low chance of publication bias. Fail-safe N  analysis denoted that a further 69 studies yielding zero effect would need to be added to make the overall ES non-significant for stress. On removal of the one potential outlier 67 the ES remained significant but became smaller: − 0.27. On removal of the two studies using estimated marginal M ± SDs, the ES remained significant and became larger: − 0.40.

Forest plot comparing breathwork interventions to non-breathwork control groups on primary outcome of self-reported/subjective stress at post-intervention. Squares and their size represent individual studies and their weight, respectively. Lines through squares are 95% CIs and diamond is the overall effect size with 95% CIs. More negative values denote larger effect of breathwork on self-reported/subjective stress in comparison to control condition. Effect sizes calculated using Hedges’ g . Figure produced using RevMan v5.4.

Subgroup analyses for stress

As displayed by Table 1 , we conducted five sub-analyses for the primary outcome self-reported/subjective stress. There were no significant differential effects between subgroups.

There was a significant effect of breathwork on stress in nonclinical samples, but not in mental (only one study) or physical health populations. Moreover, significant effects were yielded when breathwork was primarily focused on slow-paced breathing (but not for fast-paced breathing), taught to individuals alone, and when taught to groups (but not in combination, which comprised only one study). There were also significant effects of breathwork on stress when the intervention was taught remotely, in-person, and using a combination of these two delivery methods. Significant effects existed for both active and inactive control groups. There were significant effects for studies which used PSS and DASS measures (but not the PSQ, used by only one study).

Heterogeneity was high for studies with physical health samples, slow-paced breathwork, when breathwork was taught to groups and in-person, plus those studies with inactive controls, and when stress was measured by using the DASS, suggesting potential moderating factors that were not accounted for by the subgroup analyses. There was no significant correlation between estimated total duration of breathwork intervention/home practice and ES ( n  = 12) τ B  = − 0.05, p  = 0.418, number of intervention/home practice sessions and ES for stress ( n  = 12) τ B  = − 0.28, p  = 0.107, nor for intervention/home practice session frequency and ES ( n  = 12) τ B  = − 0.17, p  = 0.224.

Breathwork and secondary outcomes

In terms of data extraction, one study 79 had a measure with positively scored anxiety and depression subscales; accordingly, we subtracted the subscale score from the maximum score to reverse the polarity of the measure without changing the magnitude of difference. Another study 88 required two groups’ M ± SD scores to be combined. Analysis of follow-up scores were not possible for secondary outcomes as there were insufficient studies 58 ( n  < 5). Forest plots for the secondary outcomes are reported in Online Appendix  D . Random-effects analysis for anxiety ( k  = 20) showed a significant small-medium between-group ES in favour of breathwork, g  = − 0.32 [95% CI − 0.48, − 0.16], z  = 3.90, p  < 0.0001, with moderate and significant heterogeneity, χ 2 19  = 38.62, p  = 0.005, I 2  = 51%. Sensitivity analysis showed ESs ranging from − 0.29 to − 0.34, significant in all cases. No individual study was responsible for the significant heterogeneity. Random-effects analysis for depression ( k  = 18) displayed a significant small-medium ES in favour of breathwork, g  = − 0.40 [95% CI − 0.58, − 0.22], z  = 4.27, p  < 0.0001, and heterogeneity was moderate and significant, χ 2 17  = 40.5, p  = 0.001, I 2  = 58%. Sensitivity analysis showed ESs ranging from − 0.35 to − 0.44, significant in all cases. On removal of two potential outliers 85 , 88 , the ES remained the same. No single study was responsible for the significant heterogeneity.

We conducted the first comprehensive systematic review and meta-analysis of RCTs on the effect of breathwork on self-reported/subjective stress, analysing 12 studies which comprised a total of 785 participants. Breathwork yielded a significant post-intervention between-group effect of breathwork on stress compared to non-breathwork controls, denoting breathwork was associated with lower levels of stress than controls.

Statistical heterogeneity was moderate but not significant, meaning variance in ESs was likely explained by breathwork rather than other variables, although this non-significance could also be a consequence of the low number of studies included. This small-medium ES should be interpreted in the light of moderate risk of bias overall for the 12 studies. More than half of the studies included in our meta-analysis for stress were completed from 2020 onwards, suggesting a recent emergence of research into breathwork, which may have been accelerated by the covid-19 pandemic. Research on breathwork could be likened to that of meditation, which received an unprecedented surge in scientific exploration two decades ago 92 . We may be at a similar cusp with breathwork and anticipate considerable growth in the field. Given the close ties of breathwork to psychedelic research 93 , which is growing rapidly, this could accelerate growth further.

Regarding subgroup analyses for self-reported/subjective stress, heterogeneity was significant for studies with physical health samples, slow-paced breathwork interventions, inactive control groups, along with studies when breathwork was group-based and in-person. At present, there are too few studies within the sub-analyses to address this issue of statistical heterogeneity. Overall, point estimates were similar and sample sizes were small, hence where results were non-significant, it is unclear whether there was genuinely no effect, or lack of statistical power. Furthermore, no significant differential effects across subgroups were observed, but this could also be the result of the scarce number of studies.

While nonclinical samples showed a significant effect on self-reported/subjective stress outcomes and physical and mental health samples did not, between-subgroup differences were non-significant and the point estimates for these subgroups were similar (ranging from ES = 0.26–0.38). These findings could mean that breathwork is not effective for physical/mental health populations, however, it is also possible that this analysis was underpowered to detect effects given the relatively small number of studies contributing to the subgroups, as we have already mentioned. There were only two studies primarily focused on fast-paced breathwork and stress, insufficient to make a meaningful comparison with the ten studies primarily focused on slow-paced breathwork. Interestingly, delivery modes and styles did not seem to influence the results, which may suggest breathwork can be learned through several different formats. Half of the studies’ interventions were delivered remotely without instructors (self-help), hence breathwork could potentially be widely disseminated and thus accessible and probably scalable. The results were significant for both active and inactive controls, although it would be expected that breathwork would have less effect compared to active controls. This could be due to poor quality of the active controls. Lastly, results were significant for two of three stress outcome measures, most likely due to them being psychometrically well-validated—only one study used the third measure (PSQ).

Concerning dose–response, although associations were in the expected direction, there were no significant correlations between the minimum estimated durations of breathwork intervention/home practice and ES, for all outcomes. This apparent absence of dose–response effects was surprising as increased practice time might be expected to be associated with greater benefit, however compliance to intervention home practice was not reported for many studies and so true dose–response analysis was not possible. Moreover, intention-to-treat analysis data were used for the most conservative estimates of effect. Dhruva et al.’s study 64 included in our meta-analysis specifically investigated dose–response effects, finding a positive relationship between total amount of breathwork intervention/home practice and improvement in quality of life and chemotherapy-associated symptomology—there was a significant decrease in anxiety for each hour increase in breathwork. Alternatively, this could be indicative of breathwork being possibly able to help quickly, as suggested in very recent literature whereby just one session of slow, deep breathing had beneficial effects on anxiety and vagal tone in adults 94 , with vagal tone being measured, albeit indirectly, through HRV 6 . This may be likened to ‘micro dosing’ breathwork, similar to single session mindfulness meditation practices 95 .

The meta-analysis results are largely consistent with and extend upon previous work. For instance, our findings are somewhat in line with Malviya et al.’s recent review which provides some support for breathwork’s effectiveness in alleviating stress 43 . However, this review only included two studies for stress, one of which comprised of both groups incorporating breathing practices (and was thus excluded from our meta-analysis). Hopper et al.’s systematic review on diaphragmatic breathing found just one RCT for stress, however this used physiological measures 42 . Nonetheless, this study showed that the stress hormone cortisol was lower in people undergoing slow-paced breathwork compared to controls 96 . In a different study 38 , participants administered with bacterial endotoxin ( E. coli ) who performed fast-paced breathwork had higher spikes of cortisol compared to non-breathwork controls, during the intervention, but a quicker recovery and stabilisation of cortisol levels after cessation of breathwork. This could be another mechanism of action warranting further investigation.

Breathwork, anxiety and depression

Furthermore, meta-analyses comprising 20 and18 studies run for secondary outcome measures of self-reported/subjective anxiety and depressive symptoms, showed that breathwork interventions also yielded significant small-medium ESs in comparison to controls, favouring breathwork (see Online Appendix  D for results). However, heterogeneity was significant for both outcomes, meaning the variance in ESs may be due to other variables apart from breathwork. Thus, these ESs should be interpreted with caution and need further research. As per Malviya et al.’s review 43 , greater support was offered for breathwork in alleviating anxiety and depressive symptoms (eight studies for both outcomes). The review deemed findings pertaining to the efficacy of breathwork in decreasing anxiety and depression as promising. This was also consistent with Zaccaro et al.’s review findings on slow breathing (15 studies—no RCTs), that had lower self-reported anxiety and depression, possibly linked to increased HRV measured during interventions 4 . Ubolnuar et al.’s review of breathing exercises for COPD found no significant effect on anxiety and depression from a subgroup meta-analysis of two RCTs, however the interventions used for both were singing classes 39 . Nonetheless, a recent meta-analysis by Leyro et al. of 40 RCTs on interventions for anxiety, which comprised a respiratory component (ranging from diaphragmatic breathing to capnometry assisted respiratory training), showed such treatments were associated with significantly lower symptoms of anxiety compared to control groups 41 . Though non-respiratory controls were used, respiratory components did not have to form a significant part of the intervention, thus it is less possible to tease out the effects of such techniques. While some interventions used physically altering equipment such as training of musculature involved in respiration, this might provide further potential for breathwork-related work in clinical conditions.

Comparison to stress-reduction interventions

Through estimating statistically significant differences and 95% CIs among studies 97 , in comparison to interventions for stress, our findings suggest that breathwork might be associated with similar—and non-significantly different—effects. For instance, Heber et al.’s meta-analysis on computer- and online-based stress interventions, including CBT and third-wave CBT (e.g., inclusion of meditation, mindfulness, or acceptance of emotions) compared to controls in adults, found moderate effects on stress, d  = 0.43 [95% CI 0.31, 0.54], anxiety, d  = 0.32 [95% CI 0.17, 0.47], and depression, d  = 0.34 [95% CI 0.21, 0.48] 98 . Each of these effects overlap more than 25% with the width of either interval in our results for breathwork, denoting no indication of a clinically relevant difference between the interventions. Similar meta-analytic findings concerning effects on stress, anxiety and depression have been found for related and more analogous techniques such as mindfulness-based cognitive therapy and stress reduction (MBCT/MBSR) 99 along with self-help (MBSH) 100 . While Pizzoli et al.’s recent post-intervention HRVB meta-analysis (14 published RCTs) 13 found a significant effect on depression, another meta-analysis did not find a significant effect on stress, with the smallest ES being yielded for self-reported stress out of myriad outcomes 14 . Lastly, a meta-analysis of eight meta-analytic outcomes of RCTs on physical activity 99 showed similar significant effects on depression and anxiety. While we are not proposing breathwork as a substitute for other treatments, it could complement other therapeutic interventions, potentially leading to additive effects of such health behaviours.

People with stress and anxiety disorders tend to chronically breathe faster and more erratically, yet with increased meditation practice, respiration rate can become gradually slower, potentially translating into better health and mood, along with less autonomic activity 92 . Positive impacts on HRV may partially explain some of the mechanisms behind mindfulness meditation 101 , 102 . However, the above approaches like MBCT/MBSR and HRVB may be less accessible. MBCT/MBSR teacher training takes at least one year while HRVB is routinely taught by a qualified healthcare professional; this is usually a prerequisite and most certified biofeedback therapists are habitually licensed medical providers, including general practitioners, psychiatrists, dentists, nurses, and psychologists 103 . MBCT/MBSR and HRVB therapist training includes theoretical/practical curricula, while breathwork teacher training can be more quickly and easily taught (i.e., over days and weeks) online and remotely to both healthcare professionals and the general population, thus potentially proving cost-effective.

Two of our studies used the only Food and Drug Administration-approved portable electronic biofeedback device, which encourages deep, slow breathing 103 . However, HRV can be improved in the same way (tenfold) by simply breathing at a rate around 5–6 breaths/min 104 and some Zen Buddhist monks have been found to naturally respire around this rate during deep meditation 105 . It may be possible that breathing rate forms a key component of meditation’s known positive effects. Indeed, it has been shown that HRV can be modulated during the practice of meditation 106 . However, a recent meta-analysis on this exact matter found insufficient evidence suggesting mindfulness/meditation led to improvements in vagally mediated HRV, and more well-designed RCTs without high risk of bias are needed to clarify any such contemplative practices’ impact on this physiological metric 107 , along with potential mechanisms related to cortisol.

Traditional mindfulness-based programmes frequently involve meditation requiring observation of the breath, using it as an object of awareness, not voluntary regulation of respiration like in breathwork. Such breath-focus may be a key active ingredient and potential mechanism of action of the former contemplative practices, since highly experienced meditators have been found to breathe at over 1.5 times slower than nonmeditators, during meditation and at rest 108 . This translates into approximately 2000 less daily breaths for the former group of adept meditation practitioners (i.e., around 700,000 less breaths in a year), placing less demand on the ANS 92 . Meditation could also be complementary; voluntary upregulation of HRV through biofeedback may be improved by mental contemplative training 109 . While there is a possibility that it could simply be the cognitive-attentional components of both meditation and breathing practices that explain their effects, observation of the breath (i.e., most practices within mindfulness curricula) versus control of the breath (i.e., breathwork) warrants nuanced investigation.

Strengths, limitations and future directions

Our systematic review searched published, unpublished and grey literature across numerous electronic databases and the meta-analysis comprised several very recent RCTs with well-validated measures of self-reported/subjective stress. However, like most systematic reviews in this field, given the small sample size (likely due to the recent phenomena of breathwork in the West) and moderate risk of bias across the studies included in our meta-analysis, our results should be interpreted cautiously. Future studies exploring breathwork’s effectiveness should aim for research designs with low risk of bias. While this review attempted to bridge the gap and unify both old and new research, future low risk-of-bias studies are now needed in order to draw definitive conclusions of breathwork’s impact on mental health. There were also not enough studies for valuable subgroup comparisons, and therefore we did not identify any potential sources of heterogeneity. Furthermore, secondary outcomes were not scrutinised with the same level of detail as the primary outcome, as they were only used to provide complementary context and a bigger picture around stress and mental health in general.

Our meta-analysis is the first review of breathwork’s impact on self-reported/subjective stress and its therapeutic potential, and combining this quantitative synthesis of psychological effects of breathwork with other syntheses, i.e., of physiological effects 4 , could help build a stronger psychophysiological model of breathwork’s efficacy along with more robust mechanisms of action. Studies could use stress subscales in DASS as standard in addition to the anxiety/depression scales, as this could be important for nonclinical and subclinical populations experiencing stress and allow for direct comparison of effects across clinical/nonclinical populations. Additionally, psychophysiological RCTs combining both subjective and objective measures in line with proposed mechanisms of action (i.e., self-reported stress and ECG HRV/respiration rate measurements) should be conducted, along with further imaging (MRI, EEG, NIRS, etc.) studies on various breathwork techniques (only one fMRI study was available in Zaccaro et al.’s review 4 ). This could help better determine modalities and underlying principles of different breathwork techniques. Though validated scales were used for stress in the meta-analysis, our review lacks objective outcomes, which increases risk of bias further.

Comparison groups promoting observation versus control of the breath could yield interesting findings when exploring any differences between the effects of meditation and breathwork. However, robust scientific methods that align well with current methodological demands on meditation and contemplative psychological science 110 should be implemented. There was also limited scope to report on follow-up effects, hence more studies could include true follow-up timepoints and longitudinal designs, now more common in meditation and contemplative science research. On top of this, there could be cross-cultural differences in response to breathwork (i.e., between Eastern and Western modalities) which could be explored by future research, along with searching non-English language literature. There could also be differences between age categories (including children); this meta-analysis focused solely on adults across a broad age-range. Lastly, more studies should report on adverse events and lasting bad effects, with further research needed to gauge the safety profile of fast-paced breathwork in particular, so it not administered blindly to potentially vulnerable populations.

Clinical implications

For stress, though not many studies monitored home practice/self-practice, engagement with interventions appeared good, none reporting adverse effects directly attributed to breathwork. This suggests breathwork has a high safety profile and slow-paced breathing techniques can be recommended to subclinical populations or those experiencing high stress. However, regarding clinical populations, the findings from our meta-analysis show non-significant effects for mental and physical health populations, hence it could be premature to recommend breathwork in these contexts. If breathwork can indeed provide therapeutic benefit to specific populations, conducting research with strong, low risk-of-bias design is essential to understanding if breathwork is genuinely effective or not. Ethicality should always take centre stage, with first doing no harm being the priority. Nonetheless, in nonclinical settings (excluding those predisposed to mental and physical health conditions), the low cost and risk profiles make breathwork (primarily focused on slow-paced breathing), scalable, with evidence from this meta-analysis that some techniques can potentially be self-learned, not requiring an instructor in real-time. Providing future robust research shows positive effects of breathwork, only then can an evidence-based canon be borne out of breathwork, using standardised and manualised materials for both training and practicing various secular, accessible techniques. However, there is a possibility rigorous research demonstrates that breathwork is not effective. Moreover, precaution must be exercised at all times; clinicians should consider for the individual whether breathwork may exacerbate the symptoms of certain mental and/or physical health conditions (cf. Muskin et al. 111 ).

Conclusions

More accessible therapeutic approaches are needed to reduce, or build resilience to, stress worldwide. While breathwork has become increasingly popular owing to its possible therapeutic potential, there also remains potential for a miscalibration, or mismatch, between hype and evidence. This meta-analysis found significant small-medium effects of breathwork on self-reported/subjective stress, anxiety and depression compared to non-breathwork control conditions. Breathwork could be part of the solution to meeting the need for more accessible approaches, but more research studies with low risk-of-bias designs are now needed to ensure such recommendations are grounded in research evidence. Robust research will enable a better understanding of breathwork’s therapeutic potential, if any. The scientific research community can build on the preliminary evidence provided here and thus, potentially pave the way for effective integration of breathwork into public health.

Data availability

The datasets used and/or analysed during the current study available from the corresponding author on reasonable request.

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G.W.F. has a doctoral scholarship from—and is a Fellow of—The Ryoichi Sasakawa Young Leaders Fellowship Fund, Sylff Association, Tokyo. J.M.M. has a “Miguel Servet” research contract from the ISCIII (CP21/00080). J.M.M. is grateful to the CIBER of Epidemiology and Public Health (CIBERESP CB22/02/00052; ISCIII) for its support. Authors thank Dr. Patricia L. Gerbarg, M.D., and Dr. Frances Meeten for reading the manuscript and providing feedback prior to submission for publication. Thank you Dr. Daron A. Fincham for proofreading a final copy of the manuscript.

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G.W.F. was responsible for securing funding for the programme of work to which this contributes, conceived the initial idea, and was responsible for leading the meta-analysis. G.W.F. and J.M.M. conducted the literature search. C.S. and K.C. supervised the entire process. G.W.F. conducted the analysis with support from C.S., K.C., and J.M.M. All authors discussed the data and clinical implications of the study. G.W.F. and J.M.M. conducted the risk-of-bias evaluations. G.W.F. drafted the manuscript, with input from C.S., K.C., and J.M.M. All authors read and revised drafts and approved the final manuscript. Each section of the manuscript was discussed among all authors.

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Recent developments in stress and anxiety research

• Published: 01 September 2021
• Volume 128 , pages 1265–1267, ( 2021 )

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• Urs M. Nater 1 , 2  

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Stress and anxiety are virtually omnipresent in today´s society, pervading almost all aspects of our daily lives. While each and every one of us experiences “stress” and/or “anxiety” at least to some extent at times, the phenomena themselves are far from being completely understood. In stress research, scientists are particularly grappling with the conceptual issue of how to define stress, also with regard to delimiting stress from anxiety or negative affectivity in general. Interestingly, there is no unified theory of stress, despite many attempts at defining stress and its characteristics. Consequently, the available literature relies on a variety of different theoretical approaches, though the theories of Lazarus and Folkman ( 1984 ) or McEwen ( 1998 ) are relatively pervasive in the literature. One key issue in conceptualizing stress is that research has not always differentiated between the perception of a stimulus or a situation as a stressor and the subsequent biobehavioral response (often called the “stress response”). This is important, since, for example, psychological factors such as uncontrollability and social evaluation, i.e. factors that may influence how an individual perceives a potentially stressful stimulus or situation, have been identified as characteristics that elicit particularly powerful physiological stressful responses (Dickerson and Kemeny 2004 ). At the core of the physiological stress response is a complex physiological system, which is located in both the central nervous system (CNS) and the body´s periphery. The complexity of this system necessitates a multi-dimensional assessment approach involving variables that adequately reflect all relevant components. It is also important to consider that the experience of stress and its psychobiological correlates do not occur in a vacuum, but are being shaped by numerous contextual factors (e.g. societal and cultural context, work and leisure time, family and dyadic systems, environmental variables, physical fitness, nutritional status, etc.) and dispositional factors (e.g. genetics, personality, resilience, regulatory capacities, self-efficacy, etc.). Thus, a theoretical framework needs to incorporate these factors. In sum, as stress is considered a multi-faceted and inherently multi-dimensional construct, its conceptualization and operationalization needs to reflect this (Nater 2018 ).

The goal of the World Association for Stress Related and Anxiety Disorders (WASAD) is to promote and make available basic and clinical research on stress-related and anxiety disorders. Coinciding with WASAD’s 3rd International Congress held in September 2021 in Vienna, Austria, this journal publishes a Special Issue encompassing state-of-the art research in the field of stress and anxiety. This special issue collects answers to a number of important questions that need to be addressed in current and future research. Among the most relevant issues are (1) the multi-dimensional assessment that arises as a consequence of a multi-faceted consideration of stress and anxiety, with a particular focus on doing so under ecologically valid conditions. Skoluda et al. 2021 (in this issue) argue that hair as an important source of the stress hormone cortisol should not only be taken as a complementary stress biomarker by research staff, but that lay persons could be also trained to collect hair at the study participants’ homes, thus increasing the ecological validity of studies incorporating this important measure; (2) the incongruence between psychological and biological facets of stress and anxiety that has been observed both in laboratory and field research (Campbell and Ehlert 2012 ). Interestingly, there are behavioral constructs that do show relatively high congruence. As shown in the paper of Vatheuer et al. ( 2021 ), gaze behavior while exposed to an acute social stressor correlates with salivary cortisol, thus indicating common underlying mechanisms; (3) the complex dynamics of stress-related measures that may extend over shorter (seconds to minutes), medium (hours and diurnal/circadian fluctuations), and longer (months, seasonal) time periods. In particular, momentary assessment studies are highly qualified to examine short to medium term fluctuations and interactions. In their study employing such a design, Stoffel and colleagues (Stoffel et al. 2021 ) show ecologically valid evidence for direct attenuating effects of social interactions on psychobiological stress. Using an experimental approach, on the other hand, Denk et al. ( 2021 ) examined the phenomenon of physiological synchrony between study participants; they found both cortisol and alpha-amylase physiological synchrony in participants who were in the same group while being exposed to a stressor. Importantly, these processes also unfold over time in relation to other biological systems; al’Absi and colleagues showed in their study (al’Absi et al. 2021 ) the critical role of the endogenous opioid system and its relation to stress-related analgesia; (4) the influence of contextual and dispositional factors on the biological stress response in various target samples (e.g., humans, animals, minorities, children, employees, etc.) both under controlled laboratory conditions and in everyday life environments. In this issue, Sattler and colleagues show evidence that contextual information may only matter to a certain extent, as in their study (Sattler et al. 2021 ), the biological response to a gay-specific social stressor was equally pronounced as the one to a general social stressor in gay men. Genetic information is probably the most widely researched dispositional factor; Kuhn et al. show in their paper (Kuhn et al. 2021 ) that the low expression variant of the serotonin transporter gene serves as a risk factor for increased stress reactivity, thus clearly indicating the important role of dispositional factors in stress processing. An interesting factor combining both aspects of dispositional and contextual information is maternal care; Bentele et al. ( 2021 ) in their study are able to show that there was an effect of maternal care on the amylase stress response, while no such effect was observed for cortisol. In a similar vein, Keijser et al. ( 2021 ) showed in their gene-environment interaction study that the effects of FKBP5, a gene very closely related to HPA axis regulation, and early life stress on depressive symptoms among young adults was moderated by a positive parenting style; and (5) the role of stress and anxiety as transdiagnostic factors in mental disorders, be it as an etiological factor, a variable contributing to symptom maintenance, or as a consequence of the condition itself. Stress, e.g., as a common denominator for a broad variety of psychiatric diagnoses has been extensively discussed, and stress as an etiological factor holds specific significance in the context of transdiagnostic approaches to the conceptualization and treatment of mental disorders (Wilamowska et al. 2010 ). The HPA axis, specifically, is widely known to be dysregulated in various conditions. Fischer et al. ( 2021 ) discuss in their comprehensive review the role of this important stress system in the context of patients with post-traumatic disorder. Specifically focusing on the cortisol awakening response, Rausch and colleagues provide evidence for HPA axis dysregulation in patients diagnosed with borderline personality disorder (Rausch et al. 2021 ). As part of a longitudinal project on ADHD, Szep et al. ( 2021 ) investigated the possible impact of child and maternal ADHD symptoms on mothers’ perceived chronic stress and hair cortisol concentration; although there was no direct association, the findings underline the importance of taking stress-related assessments into consideration in ADHD studies. As the HPA axis is closely interacting with the immune system, Rhein et al. ( 2021 ) examined in their study the predicting role of the cytokine IL-6 on psychotherapy outcome in patients with PTSD, indicating that high reactivity of IL-6 to a stressor at the beginning of the therapy was associated with a negative therapy outcome. The review of Kyunghee Kim et al. ( 2021 ) also demonstrated the critical role of immune pathways in the molecular changes due to antidepressant treatment. As for the therapy, the important role of cognitive-behavioral therapy with its key elements to address both stress and anxiety reduction have been shown in two studies in this special issue, evidencing its successful application in obsessive–compulsive disorder (Ivarsson et al. 2021 ; Hollmann et al. 2021 ). Thus, both stress and anxiety are crucial transdiagnostic factors in various mental disorders, and future research needs elaborate further on their role in etiology, maintenance, and treatment.

In conclusion, a number of important questions are being asked in stress and anxiety research, as has become evident above. The Special Issue on “Recent developments in stress and anxiety research” attempts to answer at least some of the raised questions, and I want to invite you to inspect the individual papers briefly introduced above in more detail.

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Kyunghee Kim H, Zai G, Hennings J, Müller DJ, Kloiber S (2021) Changes in RNA expression levels during antidepressant treatment: a systematic review. J Neural Transm. https://doi.org/10.1007/s00702-021-02394-0

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• Ala’a B. Al-Tammemi 1 , 7 &
• László Róbert Kolozsvári   ORCID: orcid.org/0000-0001-9426-0898 1 , 7  

BMC Psychology volume  9 , Article number:  53 ( 2021 ) Cite this article

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In the case of people who carry an increased number of anxiety traits and maladaptive coping strategies, psychosocial stressors may further increase the level of perceived stress they experience. In our research study, we aimed to examine the levels of perceived stress and health anxiety as well as coping styles among university students amid the COVID-19 pandemic.

A cross-sectional study was conducted using an online-based survey at the University of Debrecen during the official lockdown in Hungary when dormitories were closed, and teaching was conducted remotely. Our questionnaire solicited data using three assessment tools, namely, the Perceived Stress Scale (PSS), the Ways of Coping Questionnaire (WCQ), and the Short Health Anxiety Inventory (SHAI).

A total of 1320 students have participated in our study and 31 non-eligible responses were excluded. Among the remaining 1289 participants, 948 (73.5%) and 341 (26.5%) were Hungarian and international students, respectively. Female students predominated the overall sample with 920 participants (71.4%). In general, there was a statistically significant positive relationship between perceived stress and health anxiety. Health anxiety and perceived stress levels were significantly higher among international students compared to domestic ones. Regarding coping, wishful thinking was associated with higher levels of stress and anxiety among international students, while being a goal-oriented person acted the opposite way. Among the domestic students, cognitive restructuring as a coping strategy was associated with lower levels of stress and anxiety. Concerning health anxiety, female students (domestic and international) had significantly higher levels of health anxiety compared to males. Moreover, female students had significantly higher levels of perceived stress compared to males in the international group, however, there was no significant difference in perceived stress between males and females in the domestic group.

The elevated perceived stress levels during major life events can be further deepened by disengagement from home (being away/abroad from country or family) and by using inadequate coping strategies. By following and adhering to the international recommendations, adopting proper coping methods, and equipping oneself with the required coping and stress management skills, the associated high levels of perceived stress and anxiety could be mitigated.

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Introduction

On March 4, 2020, the first cases of coronavirus disease were declared in Hungary. One week later, the World Health Organization (WHO) declared COVID-19 as a global pandemic [ 1 ]. The Hungarian government ordered a ban on outdoor public events with more than 500 people and indoor events with more than 100 participants to reduce contact between people [ 2 ]. On March 27, the government imposed a nationwide lockdown for two weeks effective from March 28, to mitigate the spread of the pandemic. Except for food stores, drug stores, pharmacies, and petrol stations, all other shops and educational institutions remained closed. On April 16, a week-long extension was further announced [ 3 ].

The COVID-19 pandemic with its high morbidity and mortality has already afflicted the psychological and physical wellbeing of humans worldwide [ 4 , 5 , 6 , 7 , 8 , 9 ]. During major life events, people may have to deal with more stress. Stress can negatively affect the population’s well-being or function when they construe the situation as stressful and they cannot handle the environmental stimuli [ 10 ]. Various inter-related and inter-linked concepts are present in such situations including stress, anxiety, and coping. According to the literature, perceived stress can lead to higher levels of anxiety and lower levels of health-related quality of life [ 11 ]. Another study found significant and consistent associations between coping strategies and the dimensions of health anxiety [ 12 ].

Health anxiety is one of the most common types of anxiety and it describes how people think and behave toward their health and how they perceive any health-related concerns or threats. Health anxiety is increasingly conceptualized as existing on a spectrum [ 13 , 14 ], and as an adaptive signal that helps to develop survival-oriented behaviors. It also occurs in almost everyone’s life to a certain degree and can be rather deleterious when it is excessive [ 13 , 14 ]. Illness anxiety or hypochondriasis is on the high end of the spectrum and it affects someone’s life when it interferes with daily life by making people misinterpret the somatic sensations, leading them to think that they have an underlying condition [ 14 ].

According to the American Psychiatric Association—Diagnostic and Statistical Manual of Mental Disorders (fifth edition), Illness anxiety disorder is described as a preoccupation with acquiring or having a serious illness, and it reflects the high spectrum of health anxiety [ 15 ]. Somatic symptoms are not present or if they are, then only mild in intensity. The preoccupation is disproportionate or excessive if there is a high risk of developing a medical condition (e.g., family history) or the patient has another medical condition. Excessive health-related behaviors can be observed (e.g., checking body for signs of illness) and individuals can show maladaptive avoidance as well by avoiding hospitals and doctor appointments [ 15 ].

Health anxiety is indeed an important topic as both its increase and decrease can progress to problems [ 14 ]. Looking at health anxiety as a wide spectrum, it can be high or low [ 16 ]. While people with a higher degree of worry and checking behaviors may cause some burden on healthcare facilities by visiting them too many times (e.g., frequent unnecessary visits), other individuals may not seek medical help at healthcare units to avoid catching up infections for instance. A lower degree of health anxiety can lead to low compliance with imposed regulations made to control a pandemic [ 17 ].

The COVID-19 pandemic as a major event in almost everyone’s life has posed a great impact on the population’s perceived stress level. Several studies about the relation between coping and response to epidemics in recent and previous outbreaks found higher perceived stress levels among people [ 18 , 19 , 20 , 21 ]. Being a woman, low income, and living with other people all were associated with higher stress levels [ 18 ]. Protective factors like being emotionally more stable, having self-control, adaptive coping strategies, and internal locus of control were also addressed [ 19 , 20 ]. The findings indicated that the COVID-19 crisis is perceived as a stressful event. The perceived stress was higher amongst people than it was in situations with no emergency. Nervousness, stress, and loss of control of one’s life are the factors that are most connected to perceived stress levels which leads to the suggestion that unpredictability and uncontrollability take an important part in perceived stress during a crisis [ 19 , 20 ].

Moreover, certain coping styles (e.g., having a positive attitude) were associated with less psychological distress experiences but avoidance strategies were more likely to cause higher levels of stress [ 21 ]. According to Lazarus (1999), individuals differ in their perception of stress if the stress response is viewed as the interaction between the environment and humans [ 22 ]. An Individual can experience two kinds of evaluation processes, one to appraise the external stressors and personal stake, and the other one to appraise personal resources that can be used to cope with stressors [ 22 , 23 ]. If there is an imbalance between these two evaluation processes, then stress occurs, because the personal resources are not enough to cope with the stressor’s demands [ 23 ].

During stressful life events, it is important to pay attention to the increasing levels of health anxiety and to the kind of coping mechanisms that are potential factors to mitigate the effects of high anxiety. The transactional model of stress by Lazarus and Folkman (1987) provides an insight into these kinds of factors [ 24 ]. Lazarus and Folkman theorized two types of coping responses: emotion-focused coping, and problem-focused coping. Emotion-focused coping strategies (e.g., distancing, acceptance of responsibility, positive reappraisal) might be used when the source of stress is not embedded in the person’s control and these strategies aim to manage the individual’s emotional response to a threat. Also, emotion-focused coping strategies are directed at managing emotional distress [ 24 ]. On the other hand, problem-focused coping strategies (e.g., confrontive coping, seeking social support, planful problem-solving) help an individual to be able to endure and/or minimize the threat, targeting the causes of stress in practical ways [ 24 ]. It was also addressed that emotion-focused coping mechanisms were used more in situations appraised as requiring acceptance, whereas problem-focused forms of coping were used more in encounters assessed as changeable [ 24 ].

A recent study in Hunan province in China found that the most effective factor in coping with stress among medical staff was the knowledge of their family’s well-being [ 25 ]. Although there have been several studies about the mental health of hospital workers during the COVID-19 pandemic or other epidemics (e.g., SARS, MERS) [ 26 , 27 , 28 , 29 ], only a few studies from recent literature assessed the general population’s coping strategies. According to Gerhold (2020) [ 30 ], older people perceived a lower risk of COVID-19 than younger people. Also, women have expressed more worries about the disease than men did. Coping strategies were highly problem-focused and most of the participants reported that they listen to professionals’ advice and tried to remain calm [ 30 ]. In the same study, most responders perceived the COVID-19 pandemic as a global catastrophe that will severely affect a lot of people. On the other hand, they perceived the pandemic as a controllable risk that can be reduced. Dealing with macrosocial stressors takes faith in politics and in those people, who work with COVID-19 on the frontline.

Mental disorders are found prevalent among college students and their onset occurs mostly before entry to college [ 31 ]. The diagnosis and timely interventions at an early stage of illness are essential to improve psychosocial functioning and treatment outcomes [ 31 ]. According to research that was conducted at the University of Debrecen in Hungary a few years ago, the students were found to have high levels of stress and the rate of the participants with impacted mental health was alarming [ 32 ]. With an unprecedented stressful event like the COVID-19 crisis, changes to the mental health status of people, including students, are expected.

Aims of the study

In our present study, we aimed at assessing the levels of health anxiety, perceived stress, and coping styles among university students amidst the COVID-19 lockdown in Hungary, using three validated assessment tools for each domain.

Methods and materials

Study design and setting.

This study utilized a cross-sectional design, using online self-administered questionnaires that were created and designed in Google Forms® (A web-based survey tool). Data collection was carried out in the period April 30, 2020, and May 15, 2020, which represents one of the most stressful periods during the early stage of the COVID-19 pandemic in Hungary when the official curfew/lockdown was declared along with the closure of dormitories and shifting to online remote teaching. The first cases of COVID-19 were declared in Hungary on March 4, 2020. On April 30, 2020, there were 2775 confirmed cases, 312 deaths, and 581 recoveries. As of May 15, 2020, the number of confirmed cases, deaths, and recovered persons was 3417, 442, and 1287, respectively.

Our study was conducted at the University of Debrecen, which is one of the largest higher education institutions in Hungary. The University is located in the city of Debrecen, the second-largest city in Hungary. Debrecen city is considered the educational and cultural hub of Eastern Hungary. As of October 2019, around 28,593 students were enrolled in various study programs at the University of Debrecen, of whom, 6,297 were international students [ 33 ]. The university offers various degree courses in Hungarian and English languages.

Study participants and sampling

The target population of our study was students at the University of Debrecen. Students were approached through social media platforms (e.g., Facebook®) and the official student administration system at the University of Debrecen (Neptun). The invitation link to our survey was sent to students on the web-based platforms described earlier. By using the Neptun system, we theoretically assumed that our survey questionnaire has reached all students at the University. The students who were interested and willing to participate in the study could fill out our questionnaire anonymously during the determined study period; thus, employing a convenience sampling approach. All students at the University of Debrecen whose age was 18 years or older and who were in Hungary during the outbreak had the eligibility to participate in our study whether undergraduates or postgraduates.

Study instruments

In our present study, the survey has solicited information about the sociodemographic profile of participants including age (in years), gender (female vs male), study program (health-related vs non-health related), and whether the student stayed in Hungary or traveled abroad during the period of conducting our survey in the outbreak. Our survey has also adopted three international scales to collect data about health anxiety, coping styles, and perceived stress during the pandemic crisis. As the language of instruction for international students at the University of Debrecen is English, and English fluency is one of the criteria for international students’ admission at the University of Debrecen, the international students were asked to fill out the English version of the survey and the scales. On the other hand, the Hungarian students were asked to fill out the Hungarian version of the survey and the validated Hungarian scales. Also, we provided contact information for psychological support when needed. Students who felt that they needed some help and psychological counseling could use the contact information of our peer supporters. Four International students have used this opportunity and were referred to a higher level of care. The original scales and their validated Hungarian versions are described in the following sections.

Perceived Stress Scale (PSS)

The Perceived Stress Scale (PSS) measures the level of stress in the general population who have at least completed a junior high school [ 34 ]. In the PSS, the respondents had to report how often certain things occurred like nervousness; loss of control; feeling of upset; piling up difficulties that cannot be handled; or on the contrary how often the students felt they were able to handle situations; and were on top of things. For the International students, we used the 10-item PSS (English version). The statements’ responses were scored on a 5-point Likert scale (from 0 = never to 4 = very often) as per the scale’s guide. Also, in the 10-item PSS, four positive items were reversely scored (e.g. felt confident about someone’s ability to handle personal problems) [ 34 ]. The PSS has satisfactory psychometric properties with a Cronbach’s alpha of 0.78, and this English version was used for international students in our study.

For the Hungarian students, we used the Hungarian version of the PSS, which has 14 statements that cover the same aspects of stress described earlier. In this version of the PSS, the responses were evaluated on a 5-point Likert scale (0–4) to mark how typical a particular behavior was for a respondent in the last month [ 35 ]. The Hungarian version of the PSS was psychometrically validated in 2006. In the validation study, the Hungarian 14-item PSS has shown satisfactory internal consistency with a Cronbach’s alpha of 0.88 [ 35 ].

Ways of Coping Questionnaire (WCQ)

The second scale we used was the 26-Item Ways of Coping Questionnaire (WCQ) which was developed by Sørlie and Sexton [ 36 ]. For the international students, we used the validated English version of the 26-Item WCQ that distinguished five different factors, including Wishful thinking (hoped for a miracle, day-dreamed for a better time), Goal-oriented (tried to analyze the problem, concentrated on what to do), Seeking support (talked to someone, got professional help), Thinking it over (drew on past experiences, realized other solutions), and Avoidance (refused to think about it, minimized seriousness of it). The WCQ examined how often the respondents used certain coping mechanisms, eg: hoped for a miracle, fantasized, prepared for the worst, analyzed the problem, talked to someone, or on the opposite did not talk to anyone, drew conclusions from past things, came up with several solutions for a problem or contained their feelings. As per the 26-item WCQ, responses were scored on a 4-point Likert scale (from 0 = “does not apply and/or not used” to 3 = “used a great deal”). This scale has satisfactory psychometric properties with Cronbach's alpha for the factors ranged from 0.74 to 0.81[ 36 ].

For the Hungarian students, we used the Hungarian 16-Item WCQ, which was validated in 2008 [ 37 ]. In the Hungarian WCQ, four dimensions were identified, which were cognitive restructuring/adaptation (every cloud has a silver lining), Stress reduction (by eating; drinking; smoking), Problem analysis (I tried to analyze the problem), and Helplessness/Passive coping (I prayed; used drugs) [ 37 ]. The Cronbach’s alpha values for the Hungarian WCQ’s dimensions were in the range of 0.30–0.74 [ 37 ].

Short Health Anxiety Inventory (SHAI)

The third scale adopted was the 18-Items Short Health Anxiety Inventory (SHAI). Overall, the SHAI has two subscales. The first subscale comprised of 14 items that examined to what degree the respondents were worried about their health in the past six months; how often they noticed physical pain/ache or sensations; how worried they were about a serious illness; how much they felt at risk for a serious illness; how much attention was drawn to bodily sensations; what their environment said, how much they deal with their health. The second subscale of SHAI comprised of 4 items (negative consequences if the illness occurs) that enquired how the respondents would feel if they were diagnosed with a serious illness, whether they would be able to enjoy things; would they trust modern medicine to heal them; how many aspects of their life it would affect; how much they could preserve their dignity despite the illness [ 38 ]. One of four possible statements (scored from 0 to 3) must be chosen. Alberts et al. (2013) [ 39 ] found the mean SHAI value to be 12.41 (± 6.81) in a non-clinical sample. The original 18-item SHAI has Cronbach’s alpha values in the range of 0.74–0.96 [ 39 ]. For the Hungarian students, the Hungarian version of the SHAI was used. The Hungarian version of SHAI was validated in 2011 [ 40 ]. The scoring differs from the English version in that the four statements were scored from 1 to 4, but the statements themselves were the same. In the Hungarian validation study, it was found that the SHAI mean score in a non-clinical sample (university students) was 33.02 points (± 6.28) and the Cronbach's alpha of the test was 0.83 [ 40 ].

Data analyses

Data were extracted from Google Forms® as an Excel sheet for quality check and coding then we used SPSS® (v.25) and RStudio statistical software packages to analyze the data. Descriptive and summary statistics were presented as appropriate. To assess the difference between groups/categories of anxiety, stress, and coping styles, we used the non-parametric Kruskal–Wallis test, since the variables did not have a normal distribution and for post hoc tests, we used the Mann–Whitney test. Also, we used Spearman’s rank correlation to assess the relationship between health anxiety and perceived stress within the international group and the Hungarian group. Comparison between international and domestic groups and different genders in terms of health anxiety and perceived stress levels were also conducted using the Mann–Whitney test. Binary logistic regression analysis was also employed to examine the associations between different coping styles/ strategies (treated as independent variables) and both, health anxiety level and perceived stress level (treated as outcome variables) using median splits. A p-value less than 5% was implemented for statistical significance.

Ethical considerations

Ethical permission was obtained from the Hungarian Ethical Review Committee for Research in Psychology (Reference number: 2020-45). All methods were carried out following the institutional guidelines and conforming to the ethical standards of the declaration of Helsinki. All participants were informed about the study and written informed consent was obtained before completing the survey. There were no rewards/incentives for completing the survey.

Sociodemographic characteristics of respondents

A total of 1320 students have responded to our survey. Six responses were eliminated due to incompleteness and an additional 25 responses were also excluded as the students filled out the survey from abroad (International students who were outside Hungary during the period of conducting our study). After exclusion of the described non-eligible responses (a total of 31 responses), the remaining 1289 valid responses were included in our analysis. Out of 1289 participants (100%), 73.5% were Hungarian students and around 26.5% were international students. Overall, female students have predominated the sample (n = 920, 71.4%). The median age (Interquartile range) among Hungarian students was 22 years (5) and for the international students was 22 years (4). Out of the total sample, most of the Hungarian students were enrolled in non-health-related programs (n = 690, 53.5%), while most of the international students were enrolled in health-related programs (n = 213, 16.5%). Table 1 demonstrates the sociodemographic profile of participants (Hungarian vs International).

Perceived stress, anxiety, and coping styles

For greater clarity of statistical analysis and interpretation, we created preferences regarding coping mechanisms. That is, we made the categories based on which coping factor (in the international sample) or dimension (in the Hungarian sample) the given person reached the highest scores, so it can be said that it is the person's preferred coping strategy. The four coping strategies among international students were goal-oriented, thinking it over, wishful thinking, and avoidance, while among the Hungarian students were cognitive restructuring, problem analysis, stress reduction, and passive coping.

The 26-item WCQ [ 31 ] contains a seeking support subscale which is missing from the Hungarian 16-item WCQ [ 32 ]; therefore, the seeking support subscale was excluded from our analysis. Moreover, because the PSS contained a different number of items in English and Hungarian versions (10 items vs 14 items), we looked at the average score of the answers so that we could compare international and domestic students.

In the evaluation of SHAI, the scoring of the two questionnaires are different. For the sake of comparability between the two samples, the international points were corrected to the Hungarian, adding plus one to the value of each answer. This may be the reason why we obtained higher results compared to international standards.

Among the international students, the mean score (± standard deviation) of perceived stress among male students was 2.11(± 0.86) compared to female students 2.51 (± 0.78), while the mean score (± standard deviation) of health anxiety was 34.12 (± 7.88) and 36.31 (± 7.75) among males and females, respectively. Table 2 shows more details regarding the perceived stress scores and health anxiety scores stratified by coping strategies among international students.

In the Hungarian sample, the mean score (± standard deviation) of perceived stress among male students was 2.06 (± 0.84) compared to female students 2.18 (± 0.83), while the mean score (± standard deviation) of health anxiety was 33.40 (± 7.63) and 35.05 (± 7.39) among males and females, respectively. Table 3 shows more details regarding the perceived stress scores and health anxiety scores stratified by coping strategies among Hungarian students.

Concerning coping styles among international students, the statements with the highest-ranked responses were “wished the situation would go away or somehow be finished” and “Had fantasies or wishes about how things might turn out” and both fall into the wishful thinking coping. Among the Hungarian students, the statements with the highest-ranked responses were “I tried to analyze the problem to understand better” (falls into problem analysis coping) and “I thought every cloud has a silver lining, I tried to perceive things cheerfully” (falls into cognitive restructuring coping).

On the other hand, the statements with the least-ranked responses among the international students belonged to the Avoidance coping. Among the Hungarians, it was Passive coping “I tried to take sedatives or medications” and Stress reduction “I staked everything upon a single cast, I started to do something risky” to have the lowest-ranked responses. Table 4 shows a comparison of different coping strategies among international and Hungarian students.

To test the difference between coping strategies, we used the non-parametric Kruskal–Wallis test, since the variables did not have a normal distribution. For post hoc tests, we used Mann–Whitney tests with lowered significance levels ( p  = 0.0083). Among Hungarian students, there were significant differences between the groups in stress ( χ 2 (3) = 212.01; p < 0.001) and health anxiety ( χ 2 (3) = 80.32; p  < 0.001). In the post hoc tests, there were significant differences everywhere ( p  < 0.001) except between stress reduction and passive coping ( p  = 0.089) and between problem analysis and passive coping ( p  = 0.034). Considering the health anxiety, the results were very similar. There were significant differences between all groups ( p  < 0.001), except between stress reduction and passive coping ( p  = 0.347) and between problem analysis and passive coping ( p  = 0.205). See Figs.  1 and 2 for the Hungarian students.

Perceived stress differences between coping strategies among the Hungarian students

Health anxiety differences between coping strategies among the Hungarian students

Among the international students, the results were similar. According to the Kruskal–Wallis test, there were significant differences in stress ( χ 2 (3) = 73.26; p  < 0.001) and health anxiety ( χ 2 (3) = 42.60; p  < 0.001) between various coping strategies. The post hoc tests showed that there were differences between the perceived stress level and coping strategies everywhere ( p  < 0.005) except and between avoidance and thinking it over ( p  = 0.640). Concerning health anxiety, there were significant differences between wishful thinking and goal-oriented ( p  < 0.001), between wishful thinking and avoidance ( p  = 0.001), and between goal-oriented and avoidance ( p  = 0.285). There were no significant differences between wishful thinking and thinking it over ( p  = 0.069), between goal-oriented and thinking it over ( p  = 0.069), and between avoidance and thinking it over ( p  = 0.131). See Figs.  3 and 4 .

Perceived stress differences between coping strategies among the international students

Health anxiety differences between coping strategies among the international students

The relationship between coping strategies with health anxiety and perceived stress levels among the international students

We applied logistic regression analyses for the variables to see which of the coping strategies has a significant effect on SHAI and PSS results. In the first model (model a), with the health anxiety as an outcome dummy variable (with median split; median: 35), only two coping strategies had a statistically significant relationship with health anxiety level, including wishful thinking (as a risk factor) and goal-oriented (as a protective factor).

In the second model (model b), with the perceived stress as an outcome dummy variable (with median split; median: 2.40), three coping strategies were found to have a statistically significant association with the level of perceived stress, including wishful thinking (as a risk factor), while goal-oriented and thinking it over as protective factors. See Table 5 .

The relationship between coping strategies with health anxiety and perceived stress levels among domestic students

By employing logistic regression analysis, with the health anxiety as an outcome dummy variable (with median split; median: 33.5) (model a), three coping strategies had a statistically significant relationship with health anxiety level among domestic students, including stress reduction and problem analysis (as risk factors), while cognitive restructuring (as a protective factor).

Similarly, with the perceived stress as an outcome dummy variable (with median split; median: 2.1429) (model b), three coping strategies had a statistically significant relationship with perceived stress level, including stress reduction and problem analysis (as risk factors), while cognitive restructuring (as a protective factor). See Table 6 .

Comparisons between domestic and international students

We compared health anxiety and perceived stress levels of the Hungarian and international students’ groups using the Mann–Whitney test. In the case of health anxiety, the results showed that there were significant differences between the two groups ( W  = 149,431; p  = 0.038) and international students’ levels were higher. Also, there was a significant difference in the perceived stress level between the two groups ( W  = 141,024; p  < 0.001), and the international students have increased stress levels compared to the Hungarian ones.

Comparisons between genders within students’ groups (International vs Hungarian)

Firstly, we compared the international men’s and women’s health anxiety and stress levels using the Mann–Whitney test. The results showed that the international women’s health anxiety ( W  = 11,810; p  = 0.012) and perceived stress ( W  = 10,371; p  < 0.001) levels were both significantly higher than international men’s values. However, in the Hungarian sample, women’s health anxiety was significantly higher than men’s ( W  = 69,643; p  < 0.001), but there was no significant difference in perceived stress levels among between Hungarian women and men ( W  = 75,644.5; p  = 0.064).

Relationship between health anxiety and perceived stress

We correlated the general health anxiety and perceived stress using Spearman’s rank correlation. There was a significant moderate positive relationship between the two variables ( p  < 0.001; ρ  = 0.446). Within the Hungarian students, there was a significant correlation between health anxiety and perceived stress ( p  < 0.001; ρ  = 0.433), similarly among international students as well ( p  < 0.001; ρ  = 0.465).

In our study, we found that individuals who were characterized by a preference for certain coping strategies reported significantly higher perceived stress and/or health anxiety than those who used other coping methods. These correlations can be found in both the Hungarian and international students. In the light of our results, we can say that 48.4% of the international students used wishful thinking as their preferred coping method while around 43% of the Hungarian students used primarily cognitive restructuring to overcome their problems.

Regulation of emotion refers to “the processes whereby individuals monitor, evaluate, and modify their emotions in an effort to control which emotions they have, when they have them, and how they experience and express those emotions” [ 41 ]. There is an overlap between emotion-focused coping and emotion regulation strategies, but there are also differences. The overlap between the two concepts can be noticed in the fact that emotion-focused coping strategies have an emotional regulatory role, and emotion regulation strategies may “tax the individual’s resources” as the emotion-focused coping strategies do [ 23 , 42 ]. However, in emotion-focused coping strategies, non-emotional tools can also be used to achieve non-emotional goals, while emotion regulation strategies may be used for maintaining or reinforcing positive emotions [ 42 ].

Based on the cognitive-behavioral model of health anxiety, emotion-regulating strategies can regulate the physiological, cognitive, and behavioral consequences of a fear response to some degree, even when the person encounters the conditioned stimulus again [ 12 , 43 ]. In the long run, regular use of these dysfunctional emotion control strategies may manifest as functional impairment, which may be associated with anxiety disorders. A detailed study that examined health anxiety in the view of the cognitive-behavioral model found that, regardless of the effect of depression, there are significant and consistent correlations between certain dimensions of health anxiety and dysfunctional coping and emotional regulation strategies [ 12 ].

Similar to our current study, other studies have found that health anxiety was positively correlated with maladaptive emotion regulation and negatively with adaptive emotion regulation [ 44 ], and in the case of state anxiety that emotion-focused coping strategies proved to be less effective in reducing stress, while active coping leads to a sense of subjective well-being [ 17 , 27 , 45 , 46 , 47 ]

SHAI values were found to be high in other studies during the pandemic, and the SHAI results of the international students in our study were found to be even slightly higher compared to those studies [ 44 , 48 ]. Besides, anxiety values for women were found to be higher than for men in several studies [ 44 , 48 , 49 , 50 ]. This was similar to what we found among the international students but not among the Hungarian ones. We can speculate that the ability to contact someone, the closeness of family and beloved ones, familiarity with the living environment, and maybe less online search about the coronavirus news could be factors counting towards that finding among Hungarian students. Also, most international students were enrolled in health-related study programs and his might have affected how they perceived stress/anxiety and their preferred coping strategies as well. Literature found that students of medical disciplines could have obstacles in achieving a healthy coping strategy to deal with stress and anxiety despite their profound medical knowledge compared to non-health-related students [ 51 , 52 ]. Literature also stressed the immense need for training programs to help students of medical disciplines in adopting coping skills and stress-reducing strategies [ 51 ].

The findings of our study may be a starting point for the exploration of the linkage between perceived stress, health anxiety, and coping strategies when people are not in their domestic context. People who are away from their home and friends in a relatively alien environment may tend to use coping mechanisms other than the adequate ones, which in turn can lead to increased levels of perceived stress.

Furthermore, our results seem to support the knowledge that deep-rooted health anxiety is difficult to change because it is closely related to certain coping mechanisms. It was also addressed in the literature that personality traits may have a significant influence on the coping strategy used by a person [ 53 ], revealing sophisticated and challenging links to be considered especially during training programs on effective coping and management skills. On the other hand, perceived stress which has risen significantly above the average level in the current pandemic, can be most effectively targeted by the well-formulated recommendations and advice of major international health organizations if people successfully adhere to them (e.g. physical activity; proper and adequate sleep; healthy eating; avoiding alcohol; meditation; caring for others; relationships maintenance, and using credible information resources about the pandemic, etc.) [ 1 , 54 ]. Furthermore, there may be additional positive effects of these recommendations when published in different languages or languages that are spoken by a wide range of nationalities. Besides, cognitive behavioral therapy techniques, some of which are available online during the current pandemic crisis, can further reduce anxiety. Also, if someone does not feel safe or fear prevails, there are helplines to get in touch with professionals, and this applies to the University of Debrecen in Hungary, and to a certain extent internationally.

Naturally, our study had certain limitations that should be acknowledged and considered. The temporality of events could not be assessed as we employed a cross-sectional study design, that is, we did not have information on the previous conditions of the participants which means that it is possible that some of these conditions existed in the past, while others de facto occurred with COVID-19 crisis. The survey questionnaires were completed by those who felt interested and involved, i.e., a convenience sampling technique was used, this impairs the representativeness of the sample (in terms of sociodemographic variables) and the generalizability of our results. Also, the type of recruitment (including social media) as well as the online nature of the study, probably appealed more to people with an affinity with this kind of instrument. Besides, each questionnaire represented self-reported states; thus, over-reporting or under-reporting could be present. It is also important to note that international students were answering the survey questionnaire in a language that might not have been their mother language. Nevertheless, English fluency is a prerequisite to enroll in a study program at the University of Debrecen for international students. As the options for gender were only male/female in our survey questionnaire, we might have missed the views of students who do not identify themselves according to these gender categories. Also, no data on medical history/current medical status were collected. Lastly, we had to make minor changes to the used scales in the different languages for comparability.

The COVID-19 pandemic crisis has imposed a significant burden on the physical and psychological wellbeing of humans. Crises like the current pandemic can trigger unprecedented emotional and behavioral responses among individuals to adapt or cope with the situation. The elevated perceived stress levels during major life events can be further deepened by disengagement from home and by using inadequate coping strategies. By following and adhering to the international recommendations, adopting proper coping strategies, and equipping oneself with the required coping and stress management skills, the associated high levels of perceived stress and anxiety might be mitigated.

Availability of data and materials

The datasets generated and/or analyzed during the current study are not publicly available due to compliance with institutional guidelines but they are available from the corresponding author (LRK) on a reasonable request.

Abbreviations

Centers for Disease Control and Prevention

Coronavirus Disease 2019

Perceived Stress Scale

Short Health Anxiety Inventory

Middle East Respiratory Syndrome

Severe Acute Respiratory Syndrome

Ways of Coping Questionnaire

World Health Organization

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Acknowledgments

We would like to provide our extreme thanks and appreciation to all students who participated in our study. ABA is currently supported by the Tempus Public Foundation’s scholarship at the University of Debrecen.

This research project did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

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Szabolcs Garbóczy, Szilvia Harsányi, Ala’a B. Al-Tammemi & László Róbert Kolozsvári

Department of Psychiatry, Faculty of Medicine, University of Debrecen, Debrecen, Hungary

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Department of Personality and Clinical Psychology, Institute of Psychology, University of Debrecen, Debrecen, Hungary

Anita Szemán-Nagy

Faculty of Medicine, University of Debrecen, Debrecen, Hungary

Mohamed S. Ahmad & Viktor Rekenyi

Department of Social and Work Psychology, Institute of Psychology, University of Debrecen, Debrecen, Hungary

Dorottya Ocsenás

Doctoral School of Human Sciences, University of Debrecen, Debrecen, Hungary

Department of Family and Occupational Medicine, Faculty of Medicine, University of Debrecen, Móricz Zs. krt. 22, Debrecen, 4032, Hungary

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All authors SG, ASN, MSA, SH, DO, VR, ABA, and LRK have worked on the study design, text writing, revising, and editing of the manuscript. DO, SG, and VR have done data management and extraction, data analysis. Drafting and interpretation of the manuscript were made in close collaboration by all authors SG, ASN, MSA, SH, DO, VR, ABA, and LRK. All authors read and approved the final manuscript.

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Garbóczy, S., Szemán-Nagy, A., Ahmad, M.S. et al. Health anxiety, perceived stress, and coping styles in the shadow of the COVID-19. BMC Psychol 9 , 53 (2021). https://doi.org/10.1186/s40359-021-00560-3

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Stress, anxiety, depression and sleep disturbance among healthcare professional during the COVID-19 pandemic: An umbrella review of 72 meta-analyses

Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing

Affiliation Fatima College of Health Sciences, Al Ain, United Arab Emirates

Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Writing – original draft, Writing – review & editing

Affiliation Faculty of Pharmacy, Department of Clinical Pharmacy and Therapeutics, Applied Science Private University, Amman, Jorden

Affiliation Institute of Nursing and Health Research School of Health Sciences, Ulster University, Belfast, United Kingdom

Affiliation University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America

* E-mail: [email protected]

Affiliations Midwifery and Health Faculty of Health and Life Sciences, Mental Health Nursing Department of Nursing, Northumbria University, Newcastle-Upon-Tyne, United Kingdom, Adjunct Professor Western Sydney University, Parramatta, NSW, Australia

• Mohammed Al Maqbali, 
• Ahmad Alsayed, 
• Ciara Hughes, 
• Eileen Hacker, 
• Geoffrey L. Dickens

• Published: May 9, 2024
• https://doi.org/10.1371/journal.pone.0302597
• Peer Review
• Reader Comments

The outbreak of SARS-CoV-2, which causes COVID-19, has significantly impacted the psychological and physical health of a wide range of individuals, including healthcare professionals (HCPs). This umbrella review aims provide a quantitative summary of meta-analyses that have investigated the prevalence of stress, anxiety, depression, and sleep disturbance among HCPs during the COVID-19 pandemic. An umbrella review of systematic reviews and meta-analyses reviews was conducted. The search was performed using the EMBASE, PubMed, CINAHL, MEDLINE, PsycINFO, and Google Scholar databases from 01 st January 2020 to 15 th January 2024. A random-effects model was then used to estimate prevalence with a 95% confidence interval. Subgroup analysis and sensitivity analyses were then conducted to explore the heterogeneity of the sample. Seventy-two meta-analyses involved 2,308 primary studies were included after a full-text review. The umbrella review revealed that the pooled prevalence of stress, anxiety, depression, and sleep disturbance among HCPs during the COVID-19 pandemic was 37% (95% CI 32.87–41.22), 31.8% (95% CI 29.2–34.61) 29.4% (95% CI 27.13–31.84) 36.9% (95% CI 33.78–40.05) respectively. In subgroup analyses the prevalence of anxiety and depression was higher among nurses than among physicians. Evidence from this umbrella review suggested that a significant proportion of HCPs experienced stress, anxiety, depression, and sleep disturbance during the COVID-19 pandemic. This information will support authorities when implementing specific interventions that address mental health problems among HCPs during future pandemics or any other health crises. Such interventions may include the provision of mental health support services, such as counseling and peer support programs, as well as the implementation of organizational strategies to reduce workplace stressors.

Citation: Al Maqbali M, Alsayed A, Hughes C, Hacker E, Dickens GL (2024) Stress, anxiety, depression and sleep disturbance among healthcare professional during the COVID-19 pandemic: An umbrella review of 72 meta-analyses. PLoS ONE 19(5): e0302597. https://doi.org/10.1371/journal.pone.0302597

Editor: Fadwa Alhalaiqa, Qatar University College of Nursing, QATAR

Received: January 21, 2024; Accepted: April 8, 2024; Published: May 9, 2024

Copyright: © 2024 Al Maqbali 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 data are in the paper and/or supporting information files.

Funding: The author(s) received no specific funding for this work.

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

1. Introduction

In December 2019, the coronavirus disease 2019 (COVID-19) pandemic emerged in Wuhan, China. The disease quickly spread worldwide, and the WHO declared a global health emergency in March 2020 [ 1 ]. Due to the COVID-19 pandemic, many countries implemented various measures to prevent the spread of the disease. These included implementing a partial or complete lockdown and social distancing strategies of varying intensity. The measures taken by these countries also affected the livelihood of individuals, an occurrence which might directly or indirectly also increase psychological morbidities. Undoubtedly, pandemics have a long history of impacting physical and mental health for different population groups, and HCPs are typically the most affected group in terms of bearing the burden of these illnesses [ 2 ]. In addition, several researchers have shown that work-related psychological disorders, including stress, anxiety, depression, and burnout, had already negatively affected the healthcare system before the COVID-19 pandemic, leading to low-quality care and high malpractice litigation [ 3 – 5 ].

As a result of the pandemic, HCPs experienced various changes in their personal and professional lives. For some, these included being given more responsibility, having to re-learn how to effectively control the infection, and dealing with the emotional impact of caring for infected and dying COVID-19 patients [ 6 ]. The alteration in their work environment, as well as the likelihood that they might acquire the infection themselves, can also affect their personal mental health. It is almost inevitable that the experiences of HCPs went through during the pandemic put them at heightened risk of stress, anxiety, depression, and sleep disturbance [ 7 , 8 ]. It is important to understand the effects of the pandemic on the mental health and well-being of HCPs in order to help plan strategies to prevent these individuals from experiencing detrimental effects, and to ensure that they can continue to deliver healthcare services.

During previous viral outbreaks including the Severe Acute Respiratory Syndrome (SARS) and the Middle East Respiratory Syndrome (MERS) epidemics, HCPs were placed under extraordinary amounts of pressure [ 9 , 10 ]. Indeed, evidence suggested that HCPs suffered from high levels of stress, anxiety, depression and sleep disturbance during these outbreaks [ 11 , 12 ]. A high prevalence of mental health problems can adversely impact the quality of life of HCPs, increase disability, turnover, absenteeism, and errors, and can deleteriously affect patient outcomes which may lead to low patient satisfaction [ 13 ]. Further, it might increase suicidal ideation or self-harming among HCPs [ 14 ].

In the present review, four phenomena were addressed. Sleep disturbance refers to a range of sleep-related problems, including disruptions in the body’s natural sleep-wake cycle, insufficient or poor-quality sleep, and sleep disorders [ 15 ]. The anxiety symptoms were defined as a state of excessive fear that translates to behavioural disturbances [ 16 ]. Major depressive disorder is a set of symptoms that includes depressed mood, loss of pleasure or interest, fatigue, changes in sleep and activity levels, and other symptoms, with a minimum duration of two weeks and at least five or more symptoms present according to the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) [ 16 ]. Cohen et al., [ 17 ] define stress as “the degree to which individuals appraise situations in their lives as stressful”. In this umbrella review, stress, anxiety, depression, and sleep disturbance symptoms were defined based on the validated scales/questionnaires that assess each phenomenon in the original studies.

Several primary studies and, subsequently, systematic reviews and meta-analyses have been carried out to identify the prevalence of mental health problems among HCPs during the COVID-19 pandemic. Additionally, three umbrella reviews of meta-analyses [ 18 – 20 ] have been published previously, but the number of meta-analyses included in both cases did not exceed twenty. Since their publication, further meta-analyses have estimated the prevalence of stress, anxiety, depression, and sleep disturbance during the COVID-19 pandemic. The advantages of umbrella reviews include their ability to provide a comprehensive analysis of the literature, in this case about the prevalence of various mental disorders in HCPs during the COVID-19 pandemic. In addition, the results can then be used to make policy-level decisions to improve the quality of clinical care in terms of making clinical risk predictions and can inform future research priorities. Therefore, the aim of this umbrella review is to quantify meta-analytic findings aimed at estimating the prevalence symptoms of stress, anxiety, depression, and sleep disturbance among HCPs during the COVID-19 pandemic.

The umbrella review and meta-analysis were carried out according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines [ 21 ]. The review protocol was registered with the International Prospective Register of Systematic Reviews (PROSPERO) database and can be accessed online (CRD42022364721).

2.1 Search strategy

A systematic search was conducted to identify relevant meta-analyses in various electronic databases published between 1 st January 2020 and 15 th January 2024. The databases searched were PubMed, CINAHL, MEDLINE, EMBASE, PsycINFO, and Google Scholar. The search terms strategy used Medical Subject Headings (MeSH) and free text words with Boolean operators and truncations (AND/OR/NOT). The key search terms included (MH "Coronavirus Infections+") OR "COVID-19” OR "COVID” OR "coronavir* OR "Coronavirus" OR "SARS-COV2" AND "Health care provider" OR "health care professional" OR "healthcare provider*" OR (MH "Nurses+") OR (MH "Medical Staff") OR (MH "Physician") OR (MH "Medical Doctor") OR (MH "Staff Nurses") OR "nursing staff" OR "health personnel or health professional or nurse" OR "health personnel or health professional or nurse" AND "Stress" OR "post-traumatic stress disorder" OR "panic disorder" OR "obsessive compulsive disorder OR "anxi*" OR (MH "Anxiety Disorders+") OR (MH "Anxiety+") OR (MH "Depression+") OR "depress*" OR (MH "Affective Symptoms+") OR (MH "Affective Disorders+") OR (MH "Bipolar Disorder+") OR "affective" OR "mood" OR "mental" OR (MH "Mental Disorders+") OR (MH "Mental OR "psycho*" OR (MH "Insomnia+") OR (MH "Circadian Rhythm+") OR (MH "Sleep Disorders+") OR (MH "Insomnia+") OR (MH "Sleep+") AND "Systematic Review" OR "Meta-Analysis" OR "Meta-Analytic". Additionally, the reference lists were searched to find any other studies.

2.2 Study selection

Two reviewers (A.M.; A.A.) independently extracted the data from the search, scrutinizing all titles and abstracts for eligibility against the inclusion and exclusion criteria. A third reviewer (G.D.) was available to resolve any disagreements through discussion. Systematic reviews incorporating meta-analyses were included according to the following criteria. The studies: (1) examined the prevalence of stress or anxiety or depression or sleep disturbance symptoms; (2) presented results for HCPs as a group or separately (e.g., nurses or physicians only); further, studies involving non-HCPs must have presented results for HCPs separately and not pooled with non-HCPs.; (3) were conducted during the COVID-19 pandemic; (4) were published in English; (5) involved a systematic review with meta-analysis. Studies were excluded if (1) these consisted of a systematic review without meta-analysis; (2) consisted of a literature review or a narrative review (3) the participants were general population or non-HCPs.

2.3 Quality assessment

The methodological quality assessment of each meta-analysis was blindly rated by two reviewers using the Assessment of Multiple Systematic Reviews (AMSTAR-2) tool [ 22 ]. This scale consists of 16 items that evaluate the risk of bias of a systematic review. Items 1, 3, 5, 6, 10, 13, 14, and 16 are evaluated with either a "Yes" or "No" response. Items 2, 4, 7, 8, and 9 are evaluated with "Yes," "Partial Yes," or "No" responses. Items 11, 12, and 15 are evaluated with "Yes," "No," or "No meta-analysis conducted" responses. The overall rating can be rated as "High," "Moderate," "Low," or "Critically low."

2.4 Credibility of evidence

The credibility of the evidence of each association provided was evaluated by the Fusar-Poli and Radua [ 23 ] classification criteria. The level of evidence as convincing (class I) when specific criteria were met, including more than 1000 cases, p<10 −6 , I 2 higher than 50%, 95% prediction intervals excluding the null, no small-study effects, and no publication bias. If the number of cases exceeded 1000, p<10 −6 , the largest study showed a statistically significant effect, but not all class I criteria were satisfied; the evidence level was considered highly suggestive (class II). When there were over 1000 cases, p<10 −3 , but no other class I or II criteria were met, the evidence level was termed suggestive (class III). If no class I-III criteria were met, the evidence level was classified as weak (class IV). The fourth level, termed weak evidence (class IV), included associations with a p ≤0.05, but these associations did not meet the criteria for class I, class II, or class III. The fifth level, denoted as non-significant (NS), comprised associations with a p˃0.05.

2.5 Data analyses

There are two methods exist for deriving effect size estimates from existing meta-analyses. The first approach involves conducting a meta-analysis on the effect size estimates taken from individual studies included in multiple prior meta-analyses [ 24 ]. However, this method demands significant time and resources. Furthermore, it contradicts the primary purpose of an umbrella review because it requires return to the original studies.

The second approach employs a statistical technique to efficiently summarize data from previous meta-analyses without the need to go back to the individual studies. This method relies solely on the summary effect sizes and their associated variances provided in the original meta-analyses [ 25 ]. It calculates an overall effect size for the combined meta-analyses by computing a weighted average of the summary effect sizes, with the weights determined by the inverse of the variances [ 26 ]. This approach is similar to the methods used in meta-analyses of primary studies. Although the second approach (combining summary effect sizes) may not achieve the same level of precision as the first method (combining all individual studies), empirical tests have confirmed its ability to generate a statistically valid estimate for the overall effect size [ 27 , 28 ]. In this umbrella review, we employed the second approach, which entailed the utilization of aggregate data derived from the meta-analyses.

The analyses were conducted using R software, version 4.3.1 (R Foundation for Statistical Computing), with packages used ‘meta’ [ 29 ], ‘metafore’ [ 30 ] and ‘metaumbrella’[ 31 ]. Pooled estimates prevalence with 95% Confidence Intervals (CIs) was conducted using random effect models, and the results were reported on a forest plot. In addition, the I-squared (I 2 ) test was used to assess the statistical heterogeneity of the included meta-analyses. A value of I 2 < 25% was considered low, 25–50% moderate, and ˃ 50% high [ 32 ]. Subgroup analyses were performed when there were at least four meta-analyses per subgroup.

Publication bias was assessed using Egger’s test with a p < 0.10 indicates a statistically significant small-study effect [ 33 ]. Statistical significance was set at p<0.05. If publication bias was identified, trim and fill methods were used to adjust the publication bias [ 34 ]. A sensitivity analysis was conducted in which individual meta-analyses were systematically removed one at a time to assess how they affected the overall combined prevalence of the remaining meta-analyses [ 35 ], with the aim of clarifying the stability and reliability of the finding [ 36 ].

A total of 1,987 papers were identified through the database search. Out of these, 1,843 were excluded at the abstract and title screening stage for the following reasons: 786 were duplicates, 443 did not include a meta-analysis, 392 lacked information about prevalence, 139 lacked information about HCP status, and 83 were not conducted during the period of the COVID-19 pandemic. A further 72 papers were excluded during the full text review process. As a result, 72 meta-analyses were eligible for umbrella review ( Fig 1 ).

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https://doi.org/10.1371/journal.pone.0302597.g001

3.1 General characteristics of the studies included

The included 72 meta-analyses [ 37 – 108 ]. Fifty-four of the meta-analyses dealt with HCPs in general, whereas two meta-analyses reported the situation only with regard to physicians or nurses [ 44 , 59 ], three meta-analyses dealt with nurses [ 49 , 79 , 91 ], and one dealt with physicians [ 88 ], while 17 meta-analyses included a mixed population (General and HCPs),(Only data specifically related to healthcare professionals were included in the umbrella review analysis). The most commonly used statistical software was STATA (n = 32), R (n = 17) and comprehensive meta-analysis (n = 11). Twenty-four meta-analyses used the Newcastle–Ottawa scale to assess the quality of the studies. Forty-six meta-analyses included mixed studies from different countries, twenty-five meta-analyses were conducted in specifical geographical areas: 10 for China, five for India, four for Asia two for Bangladesh and Ethiopia and one for each of the following: Egypt, South Asia, and Vietnam. The detailed characteristics of the studies including meta-analyses are shown in Table 1 .

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3.2 Quality appraisal

Each meta-analysis was assessed using the AMSTAR-2 tool. Twenty- nine meta-analyses were classified as moderate quality and thirty-seven as low quality. Only six meta-analyses were classified as critically low quality [ 37 , 44 , 45 , 76 , 97 , 101 ].

3.3 Prevalence of stress

Stress was reported in 42 meta-analyses among HCPs. The estimation of prevalence for stress varied between 11% [ 72 ] and 66.6% [ 58 ] ( Fig 2 : Forest Plots). The pooled prevalence of stress from was 37% (292,245/854,852 participants, 95% CI 32.87–41.22) with 95% PI: 14.86–66.3. There was significant heterogeneity between meta-analyses when it came to estimating the prevalence of stress ( p < 0.0001, I 2 = 99.9%). In the subgroup analysis, the prevalence of anxiety among nurses was determined to be 42.6% (n = 5; 95% CI = 30.49–55.27, I 2 = 99%), as shown in Fig 3 : Forest Plots. However, the analysis for physicians was not conducted due to an insufficient number of available meta-analyses. In sensitivity analysis, none of the meta-analyses resulted in changes to the pooled prevalence estimates greater than a 2%. The prevalence rate estimates for stress were considered to be suggestive evidence (class III) (Seen Table 2 ).

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3.4 Prevalence of anxiety

Fifty-five meta-analyses estimated the prevalence of anxiety among HCPs, and ranged from 11.4% [ 40 ] to 71.9% [ 58 ]. The pooled prevalence of anxiety was 31.8% (734,036/2,310,774 participants, 95% CI 29.2–34.61) with 95% PI: 15.24–54.83 ( Fig 4 : Forest Plots) among all HCPs and there was considerable heterogeneity ( p < 0.0001, I 2 = 99.9%). In the subgroup analyses, in terms of professional status, the pooled prevalence of anxiety was 31.6% (n = 12; 95% CI = 28.33–35.14, I 2 = 99%) and 26.3% (n = 9; 95% CI = 22.89–30.10, I 2 = 99%) for nurses, and physicians respectively (Figs 5 and 6 : Forest Plots). A sensitivity analysis, specifically a leave-one-out analysis, revealed that none of the meta-analyses had an impact on the global prevalence estimate of anxiety symptoms greater than 1%. Suggestive evidence (class III) was found for the estimated prevalence of anxiety in the case of HCPs, nurses and physicians.

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3.5 Prevalence of depression

A total of 54 meta-analyses examined the prevalence of depression among HCPs during the COVID-19 pandemic and results ranged from 14% [ 52 ] to 65.6% [ 58 ]. The pooled prevalence was 29.4% (698,808/2,349,613 participants, 95% CI 27.13–31.84) with 95% PI: 15.01–49.62 ( Fig 7 : Forest Plots) and there was a significant result in terms of the study heterogeneity ( p < 0.0001, I 2 = 99.9%). In subgroups analyses, the prevalence of depression was higher among nurses 32% (n = 11; 95% CI = 28–36.35, I 2 = 99%) compared with physicians 28.4% (n = 8; 95% CI = 24.32–32.78, I 2 = 99%) (Figs 8 and 9 : Forest Plots). In the sensitivity analysis, the pooled prevalence remained stable when one meta-analysis was excluded at a time, with variations of less than 1%. Class III evidence revealed suggestive findings regarding the estimated prevalence of depression among HCPs, nurses, and physicians.

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3.6 Prevalence of sleep disturbance

Sleep disturbance was assessed in 36 meta-analyses, with a calculated pooled prevalence of 36.9% (191,673/502,780 participants, 95% CI 33.78–40.05) with 95% PI: 19.99–57.70 ( Fig 10 : Forest Plots) with significant differences in terms of the meta-analyses heterogeneity presented (p< 0.0001, I 2 = 99.7%). The prevalence of sleep disturbance ranged from 15.01% [ 93 ] to 47.3% [ 95 ]. In subgroup analyses, the prevalence of sleep disturbance was found to be higher among nurses at 37.1% (n = 5; 95% CI = 30.71–44.1, I 2 = 99%) compared to physicians, where it was 30.6% (n = 4; 95% CI = 20.04–43.77, I 2 = 99%) (Figs 11 and 12 : Forest Plots). The estimated prevalence rate of sleep disturbance was deemed to be suggestive evidence (Class III). The pooled prevalence did not change in sensitivity analysis by excluding one meta-analyses each time by less than 3%.

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3.7 Publication bias

The result of Egger’s regression test for all pooled prevalence indicates that publication bias was insignificant, showing no evidence of publication bias Table 2 .

4. Discussion

To the best of our knowledge, this is the first umbrella review to provide a comprehensive synthesis of the estimate of the aggregate data prevalence symptoms of stress, anxiety, depression, and sleep disturbance among HCPs, physicians, and nurses during the entire COVID-19 pandemic.

In the present umbrella review, which utilizes aggregate data from 71 meta-analyses, the most prevalent problems among healthcare professionals (HCPs) were found to be stress (37%), followed by sleep disturbance (36.9%), anxiety (31.8%), and depression (29.4%). The findings among HCPs are slightly higher than the prevalence estimates from the general population (prevalence estimates of 27% for sleep disturbance; 36% for stress; 26% for anxiety and 28% for depression) during the COVID-19 pandemic [ 109 ]. In addition, a report by the World Health Organization prior to the COVID-19 pandemic estimated that the global prevalence of anxiety and depression was 4.4% and 3.6% respectively [ 110 ]. While some of this disparity may result from different methodological approaches used, the prevalence of depression and anxiety during the COVID-19 pandemic appears to have been higher than before the outbreak. The rise in mental health problems among HCPs may have been triggered by the uncertainty surrounding the pandemic, increased workload, and the fear of family transmission, any, or all of which may also contribute to the higher prevalence of these conditions.

The results of this umbrella review revealed higher prevalence rates compared with two previous reviews of meta-analyses [ 18 , 20 ]. These include 10 meta-analyses which reported prevalence rates during COVID-19 among HCPs: 25% for anxiety and 24% for depression [ 18 ]. Another umbrella review involving 18 meta-analyses found stress in 36% of the sample, depression in 26%, anxiety in 27% and sleep disturbance in 32% among HCPs during the COVID-19 pandemic [ 20 ]. It is important to highlight that the previous reviews included meta-analyses published before March 2021, while this current review included studies published until January 2024. As a result, the current umbrella review includes more meta-analyses compared to the two previous umbrella reviews [ 18 , 20 ]. This umbrella review therefore extends the scientific knowledge of the impact of COVID on mental health of HCPs.

The results of our study suggest that the psychological trauma experienced by HCPs during the SARS and MERS epidemics was lower than that experienced during the COVID-19 pandemic [ 111 – 114 ]. However, the difference between COVID-19 and previous pandemics could be explained by the high mortality rate and infectious potential of the COVID-19 pandemic. The results of this study suggest that the COVID-19 pandemic has had a significant negative effect on the psychological health of HCPs. One important lesson that should be learned is that early detection and treatment are carried out to prevent these types of psychological issues developing into more complex ones.

The result of this analysis demonstrates a higher level of anxiety, depression and sleep disturbance among nurses compared to physicians. One explanation for this may be that nurses are involved in more prolonged and closer contact to COVID-19 patients than physicians [ 115 – 117 ]. Another possible reason might be due to the higher number of nurses included in original studies.

The current review found that the overall pooled prevalence varied between the meta-analyses, for example ranging between 1% [ 72 ] and 66.6% [ 58 ] for stress, 11.% [ 40 ] and 71.9% [ 58 ] for anxiety, 14% [ 52 ] and 65.6% [ 58 ] for depression, and 15% [ 93 ] and 47.3% [ 95 ] for sleep disturbance. This could be linked to the varying COVID-19 infection and mortality rates in the countries in which the studies were conducted. Other possible reasons might relate to the healthcare system, cultural norms of HCPs, and their perceptions of stress, anxiety, depression, and sleep disturbance which in turn might be influenced by their working conditions, exposure to pandemics, intensity of lockdown and social distancing strategies, and perceived support. For instance, the result of the meta-analysis by El-Qushayri [ 58 ] showed the highest prevalent rate in terms of stress, anxiety and depression. This may be because this meta-analysis included only HCPs from Egypt, which in turn might indicate that the Egyptian healthcare system was severely affected by COVID-19 compared to other countries [ 118 ].

The finding of this umbrella review highlights significant negative effect that the COVID-19 pandemic has had on the psychological health of HCPs, further emphasizing the need for regular mental health assessment and management in this population. Due to the increasing number of complex traumas that HCPs are experiencing, special attention should be paid to the development of positive traumatic growth. The higher prevalence of stress, anxiety, depression, and sleep disturbance among HCPs have important implications for both the policies and practices of the healthcare system under consideration. It is important to identify effective interventions for HCPs such as the behavioural and educational interventions that have been suggested, including the development of a sense of coherence, positive thinking, and social support [ 119 – 121 ]. Currently there is a lack of evidence about the effectiveness of some psychological interventions that were adapted for use during COVID-19 pandemic specifically for healthcare workers [ 122 , 123 ].

Heterogeneity was significant in the majority of the analyses; several reasons can be attributed to this prominence. Firstly, the individual studies within each meta-analysis might differ substantially in terms of their design, sample sizes, interventions or exposures, and outcome measures. These variations can lead to differing effect sizes or conclusions, making the integration of results into a cohesive summary more complex. Furthermore, heterogeneity can arise from variations in the quality of these studies. While some research might have been meticulously conducted with strict inclusion criteria and rigorous methodologies, other studies on healthcare workers may have inherent biases or confounding factors due to the rapidly changing nature of the pandemic, the pressures of lockdowns, and their effects.

The unique characteristics and experiences of healthcare workers during the COVID-19 crisis, compounded by the challenges of lockdown measures, have the potential to further amplify this variability. Factors such as age, gender, ethnicity, and underlying health conditions, when combined with the stress, increased workload, and challenges of the pandemic and lockdown situations, can significantly influence study outcomes. Additionally, methodological differences in individual studies, like the use of a wide variety of questionnaires to measure symptoms, varied cut-off points, and severity thresholds, as well as the absence of a consistent ’gold standard’ for diagnostic interviews, can contribute to increased heterogeneity. In the context of the umbrella review, synthesizing findings from such a diverse collection of meta-analyses, particularly those focused on healthcare workers during this unparalleled period marked by fluctuating lockdown measures, poses a formidable challenge. Such complexity may constrain the robustness and precision of the conclusions drawn.

One of the most critical factors that policymakers need to consider when it comes to implementing effective interventions is the availability of organizational support. This can be done through various work-based interventions such as implementing shorter working hours and having buddy systems [ 124 ]. In addition, other measures such as providing mental health consultants and tele counselling can also help reduce the impact of the outbreak of disease on the well-being of staff members [ 125 , 126 ].

4.1 Limitations

Several limitations must be taken into consideration when interpreting the results of this umbrella review even though one strength of this methodology is that it provides comprehensive evidence regarding the mental health problems that were faced by HCPs during the COVID-19 pandemic, First, there is a possibility of selection bias. For example, non-English language meta-analyses were not included in this umbrella review, and this may introduce a selection bias. Second, it may be the case that some meta-analyses may have included the same primary studies and that there is consequently a significant study overlap between the meta-analyses included in this review. However, since the results of the studies were then combined with other studies, and a new result was presented, these were regarded as being new studies [ 25 ]. Further, several researchers address overlapping by removing some of the reviews with higher rates of overlapping [ 26 , 127 ]. Although removing the overlapping meta-analyses solves the problem of dependent effects, it might introduce a bias of its own. Excluding one of two overlapping meta-analyses from an umbrella review will bias the overall estimate [ 128 , 129 ]. In addition, Hennessy and Johnson [ 127 ] clearly mention that the overlap of primary studies included in a meta-review is not necessarily a bias but often can be a benefit.

Third, the various methodologies of the primary studies that were included in the meta-analyses, in terms of sampling methods, assessment tools, operational definitions of the symptoms and study length, might have affected the sensitivity and specificity with regard to detecting the prevalence estimations of stress, anxiety, depression, and sleep disturbance [ 130 ]. Finally, it should be noted that stress, anxiety, depression, and sleep disturbance varied between the HCPs studied. Therefore, future research should focus on the difference contexts of estimation prevalence between HCPs and should report the prevalence in each group.

5. Conclusion

In summary, this umbrella review systematically analyses the currently available evidence on the prevalence of stress, anxiety, depression, and sleep disturbance among HCPs in relation to COVID-19. It revealed that the incidence of these symptoms is high in the HCP population. However, there is wide variation in the degree of these conditions among this HCP population. This may be due to the varying experiences of COVID-19 and the cultural differences in the countries where the studies have been carried out. It is clear from the current evidence that strategies involving multi-level interventions are required to develop effective interventions that can help improve the mental health and well-being of HCPs and foster post-traumatic growth. Further research needs to address the limitations of the existing literature, in order to enable the authorities, providers, and patients to improve the quality of mental health on the part of HCPs.

Supporting information

S1 checklist. prisma 2020 checklist..

https://doi.org/10.1371/journal.pone.0302597.s001

S1 Table. Quality assessment result of meta analysis using the AMSTAR-2 (N = 72).

https://doi.org/10.1371/journal.pone.0302597.s002

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• Published: 24 February 2024

Physical activity improves stress load, recovery, and academic performance-related parameters among university students: a longitudinal study on daily level

• Monika Teuber 1 ,
• Daniel Leyhr 1 , 2 &
• Gorden Sudeck 1 , 3  

BMC Public Health volume  24 , Article number:  598 ( 2024 ) Cite this article

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Physical activity has been proven to be beneficial for physical and psychological health as well as for academic achievement. However, especially university students are insufficiently physically active because of difficulties in time management regarding study, work, and social demands. As they are at a crucial life stage, it is of interest how physical activity affects university students' stress load and recovery as well as their academic performance.

Student´s behavior during home studying in times of COVID-19 was examined longitudinally on a daily basis during a ten-day study period ( N  = 57, aged M  = 23.5 years, SD  = 2.8, studying between the 1st to 13th semester ( M  = 5.8, SD  = 4.1)). Two-level regression models were conducted to predict daily variations in stress load, recovery and perceived academic performance depending on leisure-time physical activity and short physical activity breaks during studying periods. Parameters of the individual home studying behavior were also taken into account as covariates.

While physical activity breaks only positively affect stress load (functional stress b = 0.032, p  < 0.01) and perceived academic performance (b = 0.121, p  < 0.001), leisure-time physical activity affects parameters of stress load (functional stress: b = 0.003, p  < 0.001, dysfunctional stress: b = -0.002, p  < 0.01), recovery experience (b = -0.003, p  < 0.001) and perceived academic performance (b = 0.012, p  < 0.001). Home study behavior regarding the number of breaks and longest stretch of time also shows associations with recovery experience and perceived academic performance.

Conclusions

Study results confirm the importance of different physical activities for university students` stress load, recovery experience and perceived academic performance in home studying periods. Universities should promote physical activity to keep their students healthy and capable of performing well in academic study: On the one hand, they can offer opportunities to be physically active in leisure time. On the other hand, they can support physical activity breaks during the learning process and in the immediate location of study.

Peer Review reports

Introduction

Physical activity (PA) takes a particularly key position in health promotion and prevention. It reduces risks for several diseases, overweight, and all-cause mortality [ 1 ] and is beneficial for physical, psychological and social health [ 2 , 3 , 4 , 5 ] as well as for academic achievement [ 6 , 7 ]. However, PA levels decrease from childhood through adolescence and into adulthood [ 8 , 9 , 10 ]. Especially university students are insufficiently physically active according to health-oriented PA guidelines [ 11 ] because of academic workloads as well as difficulties in time management regarding study, work, and social demands [ 12 ]. Due to their independence and increasing self-responsibility, university students are at a crucial life stage. In this essential and still educational stage of the students´ development, it is important to study their PA behavior. Furthermore, PA as health behavior represents one influencing factor which is considered in the analytical framework of the impact of health and health behaviors on educational outcomes which was developed by the authors Suhrcke and de Paz Nieves [ 13 , 14 ]. In light of this, the present study examines how PA affects university students' academic situations.

Along with the promotion of PA, the reduction of sedentary behavior has also become a crucial part of modern health promotion and prevention strategies. Spending too much time sitting increases many health risks, including the risk of obesity [ 15 ], diabetes [ 16 ] and other chronic diseases [ 15 ], damage to muscular balances, bone metabolism and musculoskeletal system [ 17 ] and even early death [ 15 ]. University students are a population that has shown the greatest increase in sedentary behavior over the last two decades [ 18 ]. In Germany, they show the highest percentage of sitting time among all working professional groups [ 19 ]. Long times sitting in classes, self-study learning, and through smartphone use, all of which are connected to the university setting and its associated behaviors, might be the cause of this [ 20 , 21 ]. This goes along with technological advances which allow students to study in the comfort of their own homes without changing locations [ 22 ].

To counter a sedentary lifestyle, PA is crucial. In addition to its physical health advantages, PA is essential for coping with the intellectual and stress-related demands of academic life. PA shows positive associations with stress load and academic performance. It is positively associated with learning and educational success [ 6 ] and even shows stress-regulatory potential [ 23 ]. In contrast, sedentary behavior is associated with lower cognitive performance [ 24 ]. Moreover, theoretical derivations show that too much sitting could have a negative impact on brain health and diminish the positive effects of PA [ 16 ]. Given the theoretical background of the stressor detachment model [ 25 ] and the cybernetic approach to stress management in the workplace [ 26 ], PA can promote recovery experience, it can enhance academic performance, and it is a way to reduce the impact of study-related stressors on strain. Load-related stress response can be bilateral: On the one hand, it can be functional if it is beneficial to help cope with the study demands. On the other hand, it can be dysfunctional if it puts a strain on personal resources and can lead to load-related states of strain [ 27 ]. Thus, both, the promotion of PA and reduction of sedentary behavior are important for stress load, recovery, and performance in student life, which can be of particular importance for students in an academic context.

A simple but (presumably) effective way to integrate PA and reduce sedentary behavior in student life are short PA breaks. Due to the exercises' simplicity and short duration, students can perform them wherever they are — together in a lecture or alone at home. Short PA breaks could prevent an accumulation of negative stressors during the day and can help with prolonged sitting as well as inactivity. Especially in the university setting, evidence of the positive effects of PA breaks exists for self-perceived physical and psychological well-being of the university students [ 28 ]. PA breaks buffer university students’ perceived stress [ 29 ] and show positive impacts on recovery need [ 30 ] and better mood ratings [ 31 , 32 ]. In addition, there is evidence for reduction in tension [ 30 ], overall muscular discomfort [ 33 ], daytime sleepiness or fatigue [ 33 , 34 ] and increase in vigor [ 34 ] and experienced energy [ 30 ]. This is in line with cognitive, affective, behavioral, and biological effects of PA, all categorized as palliative-regenerative coping strategies, which addresses the consequences of stress-generating appraisal processes aiming to alleviate these consequences (palliative) or restore the baseline of the relevant reaction parameter (regenerative) [ 35 , 36 ]. This is achieved by, for example, reducing stress-induced cortisol release or tension through physical activity (reaction reduction) [ 35 ]. Such mechanisms are also in accordance with the previously mentioned stressor detachment model [ 25 ]. Lastly, there is a health-strengthening effect that impacts the entire stress-coping-health process, relying on the compensatory effects of PA which is in accordance to the stress-buffering effect of exercise [ 37 ]. Health, in turn, effects educational outcomes [ 13 , 14 ]. Therefore, stress regulating effects are also accompanied with the before mentioned analytical framework of the impact of health and health behaviors on educational outcomes [ 13 , 14 ].

Focusing on the effects of PA, this study is guided by an inquiry into how PA affects university students' stress load and recovery as well as their perceived academic performance. For that reason, the student´s behavior during home studying in times of COVID-19 is examined, a time in which reinforced prolonged sitting, inactivity, and a negative stress load response was at a high [ 38 , 39 , 40 , 41 , 42 ]. Looking separately on the relation of PA with different parameters based on the mentioned evidence, we assume that PA has a positive impact on stress load, recovery, and perceived academic performance-related parameters. Furthermore, a side effect of the home study behavior on the mentioned parameters is assumed regarding the accumulation of negative stressors during home studying. These associations are presented in Fig.  1 and summarized in the following hypotheses:

Overview of the assumed effects and investigated hypotheses of physical activity (PA) behavior on variables of stress load and recovery and perceived academic performance-related parameters

Hypothesis 1 (path 1): Given that stress load always occurs as a duality—beneficial if it is functional for coping, or exhausting if it puts a strain on personal resources [ 27 ] – we consider two variables for stress load: functional stress and dysfunctional stress. In order to reduce the length of the daily surveys, we focused the measure of recovery only on the most obvious and accessible component of recovery experience, namely psychological detachment. PA (whether performed in leisure-time or during PA breaks) encourages functional stress and reduce dysfunctional stress (1.A) and has a positive effect on recovery experience through psychological detachment (1.B).

Hypothesis 2 (path 2): The academic performance-related parameters attention difficulties and study ability are positively influenced by PA (whether done in leisure-time or during PA breaks). We have chosen to assess attention difficulties for a cognitive parameter because poor control over the stream of occurring stimuli have been associated with impairment in executive functions or academic failure [ 43 , 44 , 45 , 46 ]. Furthermore, we have assessed the study ability to refer to the self-perceived feeling of functionality regarding the demands of students. PA reduces self-reported attention difficulties (2.A) and improves perceived study ability, indicating that a student feels capable of performing well in academic study (2.B).

Hypothesis 3: We assume that a longer time spent on studying at home (so called home studying) could result in higher accumulation of stressors throughout the day which could elicit immediate stress responses, while breaks in general could reduce the influence of work-related stressors on strain and well-being [ 47 , 48 ]. Therefore, the following covariates are considered for secondary effects:

the daily longest stretch of time without a break spent on home studying

the daily number of breaks during home studying

Study setting

The study was carried out during the COVID-19 pandemic containment phase. It took place in the middle of the lecture period between 25th of November and 4th of December 2020. Student life was characterized by home studying and digital learning. A so called “digital semester” was in effect at the University of Tübingen when the study took place. Hence, courses were mainly taught online (e.g., live or via a recorded lecture). Other events and actions at the university were not permitted. As such, the university sports department closed in-person sports activities. For leisure time in general, there were contact restrictions (social distancing), the performance of sports activities in groups was not permitted, and sports facilities were closed.

Thus, the university sports department of the University of Tübingen launched various online sports courses and the student health management introduced an opportunity for a new digital form of PA breaks. This opportunity provided PA breaks via videos with guided physical exercises and health-promoting explanations for a PA break for everyday home studying: the so called “Bewegungssnack digital” [in English “exercise snack digital” (ESD)] [ 49 ]. The ESD videos took 5–7 min and were categorized into three thematic foci: activation, relaxation, and coordination. Exercises were demonstrated by one or two student exercise leaders, accompanied by textual descriptions of the relevant execution features of each exercise.

Participants

Participants were recruited within the framework of an intervention study, which was conducted to investigate whether a digital nudging intervention has a beneficial effect on taking PA breaks during home study periods [ 49 ]. Students at the University of Tübingen which counts 27,532 enrolled students were approached for participation through a variety of digital means: via an email sent to those who registered for ESD course on the homepage of the university sports department and to all students via the university email distribution list; via advertisement on social media of the university sports department (Facebook, Instagram, YouTube, homepage). Five tablets, two smart watches, and one iPad were raffled off to participants who engaged actively during the full study period in an effort to motivate them to stick with it to the end. In any case, participants knew that the study was voluntary and that they would not suffer any personal disadvantages should they opt out. There was a written informed consent prompt together with a prompt for the approval of the data protection regulations immediately within the first questionnaire (T0) presented in a mandatory selection field. Positive ethical approval for the study was given by the first author´s institution´s ethics committee of the faculty of the University of Tübingen.

Participants ( N  = 57) who completed the daily surveys on at least half of the days of the study period, were included in the sample (male = 6, female = 47, diverse = 1, not stated = 3). As not all subjects provided data on all ten study days, the total number of observations was between 468 and 540, depending on the variable under study (see Table  1 ). The average number of observations per subject was around eight. Their age was between 18 and 32 years ( M  = 23.52, SD  = 2.81) and they were studying between the 1st to 13th semester ( M  = 5.76, SD  = 4.11) within the following major courses of study: mathematical-scientific majors (34.0%), social science majors (22.6%), philosophical majors (18.9%), medicine (13.2%), theology (5.7%), economics (3.8%), or law (1.9%). 20.4% of the students had on-site classroom teaching on university campus for at least one day a week despite the mandated digital semester, as there were exceptions for special forms of teaching.

Design and procedures

To examine these hypothesized associations, a longitudinal study design with daily surveys was chosen following the suggestion of the day-level study of Feuerhahn et al. (2014) and also of Sonnentag (2001) measuring recovery potential of (exercise) activities during leisure time [ 50 , 51 ]. Considering that there are also differences between people at the beginning of the study period, initial base-line value variables respective to the outcomes measured before the study period were considered as independent covariates. Therefore, the well-being at baseline serves as a control for stress load (2.A), the psychological detachment at baseline serves as a control for daily psychological detachment (2.B), the perception of study demands serves as a control for self-reported attention difficulties (1.A), and the perceived study ability at baseline serves as a control for daily study ability (2.B).

Subjects were asked to continue with their normal home study routine and additionally perform ESD at any time in their daily routine. Data were collected one to two days before (T0) as well as daily during the ten-day study period (Wednesday to Friday). The daily surveys (t 1 -t 10 ) were sent by email at 7 p.m. every evening. Each day, subjects were asked to answer questions about their home studying behavior, study related requirements, recovery experience from study tasks, attention, and PA, including ESD participation. The surveys were conducted online using the UNIPARK software and were recorded and analyzed anonymously.

Measures and covariates

In total, five outcome variables, two independent variables, and seven covariates were included in different analyses: three variables were used for stress load and recovery parameters, two variables for academic performance-related parameters, two variables for PA behavior, two variables for study behavior, four variables for outcome specific baseline values and one variable for age.

Outcome variables

Stress load & recovery parameters (hypothesis 1).

Stress load was included in the analysis with two variables: functional stress and dysfunctional stress. Followingly, a questionnaire containing a word list of adjectives for the recording of emotions and stress during work (called “Erfassung von Emotionen und Beanspruchung “ in German, also known as EEB [ 52 ]) was used. It is an instrument which were developed and validated in the context of occupational health promotion. The items are based on mental-workload research and the assessment of the stress potential of work organization [ 52 ]. Within the questionnaire, four mental and motivational stress items were combined to form a functional stress scale (energetic, willing to perform, attentive, focused) (α = 0.89) and four negative emotional and physical stress items were combined to form dysfunctional stress scale (nervous, physically tensioned, excited, physically unwell) (α = 0.71). Participants rated the items according to how they felt about home studying in general on the following scale (adjustment from “work” to “home studying”): hardly, somewhat, to some extent, fairly, strongly, very strongly, exceptionally.

Recovery experience was measured via psychological detachment. Therefore, the dimension “detachment” of the Recovery Experience Questionnaire (RECQ [ 53 ]) was adjusted to home studying. The introductory question was "How did you experience your free time (including short breaks between learning) during home studying today?". Students responded to four statements based on the extent to which they agreed or disagreed (not at all true, somewhat true, moderately true, mostly true, completely true). The statements covered subjects such as forgetting about studying, not thinking about studying, detachment from studying, and keeping a distance from student tasks. The four items were combined into a score for psychological detachment (α = 0.94).

Academic performance-related parameters (hypothesis 2)

Attention was assessed via the subscale “difficulty maintaining focused attention performance” of the “Attention and Performance Self-Assessment” (ASPA, AP-F2 [ 54 ]). It contains nine items with statements about disturbing situations regarding concentration (e.g. “Even a small noise from the environment could disturb me while reading.”). Participants had to answer how often such situations happened to them on a given day on the following scale: never, rarely, sometimes, often, always. The nine items were combined into the AP-F2 score (α = 0.87).

The perceived study ability was assessed using the study ability index (SAI [ 55 ]). The study ability index captures the current state of perceived functioning in studying. It is based on the Work Ability Index by Hasselhorn and Freude ([ 56 ]) and consists of an adjusted short scale of three adapted items in the context of studying. Firstly, (a) the perceived academic performance was asked after in comparison to the best study-related academic performance ever achieved (from 0 = completely unable to function to 10 = currently best functioning). Secondly, the other two items were aimed at assessing current study-related performance in relation to (b) study tasks that have to be mastered cognitively and (c) the psychological demands of studying. Both items were answered on a five-point Likert scale (1 = very poor, 2 = rather poor, 3 = moderate, 4 = rather good, 5 = very good). A sum index, the SAI, was formed which can indicate values between 2 and 20, with higher values corresponding to higher assessed functioning in studies (α = 0.86). In a previous study it already showed satisfying reliability (α = 0.72) [ 55 ].

Independent variables

Pa behavior.

Two indicators for PA behavior were included via self-reports: the time spent on ESD and the time spent on leisure-time PA (LTPA). Participants were asked the following overarching question daily: “How much time did you spend on physical activity today and in what context”. For the independent variable time spent on PA breaks, participants could answer the option “I participated in the Bewegungssnack digital” with the amount of time they spent on it (in minutes). To assess the time spent on LTPA besides PA breaks, participants could report their time for four different contexts of PA which comprised two forms: Firstly, structured supervised exercise was reported via time spent on (a) university sports courses and (b) other organized sports activities. Secondly, self-organized PA was indicated via (c) independent PA at home, such as a workout or other physically demanding activity such as cleaning or tidying up, as well as via (d) independent PA outside, like walking, cycling, jogging, a workout or something similar. Referring to the different domains of health enhancing PA [ 57 ], the reported minutes of these four types of PA were summed up to a total LTPA value. The total LTPA value was included in the analysis as a metric variable in minutes.

Covariates (hypothesis 3)

Regarding hypothesis 3 and home study behavior, the longest daily stretch of time without a break spent on home studying (in hours) and the daily number of breaks during home studying was assessed. Therein, participants had to answer the overarching question “How much time did you spend on your home studying today?” and give responses to the items: (1) longest stretch of time for home studying (without a break), and (2) number of short and long breaks you took during home studying.

In principle, efforts were made to control for potential confounders at the individual level (level 2) either by including the baseline measure (T0) of the respective variable or by including variables assessing related trait-like characteristics for respective outcomes. The reason why related trait-like characteristics were used for the outcomes was because brief assessments were used for daily surveys that were not concurrently employed in the baseline assessment. To enable the continued use of controlling for person-specific baseline characteristics in the analysis of daily associations, trait-like characteristics available from the baseline assessment were utilized as the best possible approximation.To sum up, four outcome specific baseline value variables were measured before the study period (at T0). The psychological detachment with the RECQ (α = 0.87) [ 53 ] was assessed at the beginning to monitor daily psychological detachment. Further, the SAI [ 55 ] was assessed at the beginning of the study period to monitor daily study ability. To monitor daily stress load, which in part measures mental stress aspects and negative emotional stress aspects, the well-being was assessed at the beginning using the WHO-Five Well-being Index (WHO-5 [ 58 ]). It is a one-dimensional self-report measure with five items. The index value is the sum of all items, with higher values indicating better well-being. As the well-being and stress load tolerance may linked with each other, this variable was assumed to be a good fit with the daily stress load indicating mental and emotional stress aspects. With respect to student life, daily academic performance-related attention was monitored with an instrument for the perception of study demands and resources (termed “Berliner Anforderungen Ressourcen-Inventar – Studierende” in German, the so-called BARI-S [ 59 ]). It contains eight items which capture overwork in studies, time pressure during studies, and the incompatibility of studies and private life. All together they form the BARI-S demand scale (α = 0.85) which was included in the analysis. As overwork and time pressure may result in attention difficulties (e.g. Elfering et al., 2013), this variable was assumed to have a good fit with academic performance-related attention [ 60 ]. Additionally, age in years at T0 was considered as a sociodemographic factor.

Statistical analysis

Since the study design provided ten measurement points for various people, the hierarchical structure of the nested data called for two-level analyses. Pre-analyses of Random-Intercept-Only models for each of the outcome variables (hypothesis 1 to 3) revealed an Intra-Class-Correlation ( ICC ) of at least 0.10 (range 0.26 – 0.64) and confirmed the necessity to perform multilevel analyses [ 61 ]. Specifically, the day-level variables belong to Level 1 (ESD time, LTPA time, longest stretch of time without a break spent on home studying, daily number of breaks during home studying). To analyze day-specific effects within the person, these variables were centered on the person mean (cw = centered within) [ 50 , 62 , 63 , 64 ]. This means that the analyses’ findings are based on a person’s deviations from their average values. The variables assessed at T0 belong to Level 2, which describe the person level (psychological detachment baseline, SAI baseline, well-being, study demands scale, age). These covariates on person level were centered around the grand mean [ 50 ] indicating that the analyses’ findings are based how far an individual deviates from the sample's mean values. As a result, the models’ intercept reflects the outcome value of an average student in the sample at his/her daily average behavior in PA and home study when all parameters are zero. For descriptive statistics SPSS 28.0.1.1 (IBM) and for inferential statistics R (version 4.1.2) were used. The hierarchical models were calculated using the package lme4 with the lmer-function in R in the following steps [ 65 ]. The Null Model was analyzed for all models first, with the corresponding intercept as the only predictor. Afterwards, all variables were entered. The regression coefficient estimates (”b”) were considered for statistical significance for the models and the respective BIC was provided.

In total, five regression models with ‘PA break time’ and ‘LTPA time’ as independent variables were computed due to the five measured outcomes of the present study. Three models belonged to hypothesis 1 and two models to hypothesis 2.

Hypothesis 1: To test hypothesis 1.A two outcome variables were chosen for two separate models: ‘functional stress’ and ‘dysfunctional stress’. Besides the PA behavior variables, the ‘number of breaks’, the ‘longest stretch of time without a break spent on home studying’, ‘age’, and the ‘well-being’ at the beginning of the study as corresponding baseline variable to the output variable were also included as independent variables in both models. The outcome variable ‘psychological detachment’ was utilized in conjunction with the aforementioned independent variables to test hypotheses 1.B, with one exception: psychological detachment at the start of the study was chosen as the corresponding baseline variable.

Hypothesis 2: To investigate hypothesis 2.A the outcome variable ‘attention difficulties’ was selected. Hypothesis 2.B was tested with the outcome variables ‘study ability’. Both models included both PA behavior variables as well as the ‘number of breaks’, the ‘longest stretch of time without a break spent on home studying’, ‘age’ and one corresponding baseline variable each: the ‘study demand scale’ at the start of the study for ‘attention difficulties’ and the ‘SAI’ at the beginning of the study for the daily ‘study ability’.

Hypothesis 3: In addition to both PA behavior variables, age and one baseline variable that matched the outcome variable, the covariates ‘daily longest stretch of time spent on home studying’ and ‘daily number of breaks during home studying’ were included in the models for all five outcome variables.

Handling missing data

The dataset had up to 18% missing values (most exhibit the variables ‘daily longest stretch of time without a break spent on home studying’ with 17.89% followed by ‘daily number of breaks during homes studying’ with 16.67%, and ‘functional / dysfunctional stress’ with 12.45%). Therefore, a sensitivity analysis was performed using the multiple imputation mice-package in the statistical program R [ 66 ], the package howManyImputation based on Von Hippel (2020, [ 67 ]), and the additional broom package [ 68 ]. The results of the models remained the same, with one exception for the Attention Difficulties Model: The daily longest stretch of time without a break spent on home studying showed a significant association (Table  1 in supplement). Due to this almost perfect consistency of results between analyses based on the dataset with missing data and those with imputed data alongside the lack of information provided by the packages for imputed datasets, we decided to stick with the main analysis including the missing data. Thus, in the following the results of the main analysis without imputations are presented.

Table 1 shows the descriptive statistics of the variables used in the analysis. An overview of the analysed models is presented in Table  2 .

Effects on stress load and recovery (hypothesis 1)

Hypothesis 1.A: The Model Functional Stress explained 13% of the variance by fixed factors (marginal R 2  = 0.13), and 52% by both fixed and random factors (conditional R 2  = 0.52). The time spent on ESD as well as the time spent on PA in leisure showed a positive significant influence on functional stress (b = 0.032, p  < 0.01). The same applied to LTPA (b = 0.003, p  < 0.001). The Model Dysfunctional Stress (marginal R 2  = 0.027, conditional R 2  = 0.647) showed only one significant result. The dysfunctional stress was only significantly negatively influenced by the time spent on LTPA (b = 0.002, p  < 0.01).

Hypothesis 1.B: With the Model Detachment, fixed factors contributed 18% of the explained variance and fixed and random factors 46% of the explained variance for psychological detachment. Only the amount of time spent on LTPA revealed a positive impact on psychological detachment (b = 0.003, p  < 0.001).

Effects on academic performance-related parameters (hypothesis 2)

Hypothesis 2.A: The Model Attention Difficulties showed 13% of the variance explained by fixed factors, and 51% explained by both fixed and random factors. It showed a significant negative association only for the time spent on LTPA (b = 0.003, p  < 0.001).

Hypothesis 2.B: The Model SAI showed 18% of the variance explained by fixed factors, and 39% explained by both fixed and random factors. There were significant positive associations for time spent on ESD (b = 0.121, p  < 0.001) and time spent on LTPA (b = 0.012, p  < 0.001). The same applied to LTPA (b = 0.012, p  < 0.001).

Effects of home study behavior (hypothesis 3)

Regarding the independent covariates for the outcome variables functional and dysfunctional stress, there were no significant results for the number of breaks during homes studying or the longest stretch of time without a break spent on home studying. Considering the outcome variable ‘psychological detachment’, there were significant results with negative impact for both study behavior variables: breaks during home studying (b = 0.058, p  < 0.01) and daily longest stretch of time without a break (b = 0.120, p  < 0.01). Evaluating the outcome variables ‘attention difficulties’, there were no significant results for the number of breaks during home studying or the longest stretch of time without a break spent on home studying. Testing the independent study behavior variables for the SAI, it increased with increasing number in daily breaks during homes studying relative to the person´s mean (b = 0.183, p  < 0.05). No significant effect was found for the longest stretch of time without a break spent on home studying ( p  = 0.07).

The baseline covariates of the models showed expected associations and thus confirmed their inclusion. The baseline variables well-being showed a significant impact on functional stress (b = 0.089, p  < 0.001), psychological detachment showed a positive effect on the daily output variables psychological detachment (b = 0.471, p  < 0.001), study demand scale showed a positive association on difficulties in attention (b = 0.240, p  < 0.01), and baseline SAI had a positive effect on the daily SAI (b = 0.335, p  < 0.001).

The present study theorized that PA breaks and LTPA positively influence the academic situation of university students. Therefore, impact on stress load (‘functional stress’ and ‘dysfunctional stress’) and ‘psychological detachment’ as well as academic performance-related parameters ‘self-reported attention difficulties’ and ‘perceived study ability’ was taken into account. The first and second hypotheses assumed that both PA breaks and LTPA are positively associated with the aforementioned parameters and were confirmed for LTPA for all parameters and for PA breaks for functional stress and perceived study ability. The third hypothesis assumed that home study behavior regarding the daily number of breaks during home studying and longest stretch of time without a break spent on home studying has side effects. Detected negative effects for both covariates on psychological detachment and positive effects for the daily number of breaks on perceived study ability were partly unexpected in their direction. These results emphasize the key position of PA in the context of modern health promotion especially for students in an academic context.

Regarding hypothesis 1 and the detected positive associations for stress load and recovery parameters with PA, the results are in accordance with the stress-regulatory potential of PA from the state of research [ 23 ]. For hypothesis 1.A, there is a positive influence of PA breaks and LTPA on functional stress and a negative influence of LTPA on dysfunctional stress. Given the bilateral role of stress load, the results indicate that PA breaks and LTPA are beneficial for coping with study demands, and may help to promote feelings of joy, pride, and learning progress [ 27 ]. This is in line with previous evidence that PA breaks in lectures can buffer university students’ perceived stress [ 29 ], lead to better mood ratings [ 29 , 31 ], and increase in motivation [ 28 , 69 ], vigor [ 34 ], energy [ 30 ], and self-perceived physical and psychological well-being [ 28 ]. Looking at dysfunctional stress, the result point that LTPA counteract load-related states of strain such as inner tension, irritability and nervous restlessness or feelings of boredom [ 27 ]. In contrast, short PA breaks during the day could not have enough impact in countering dysfunctional stress at the end of the day regarding the accumulation of negative stressors during home studying which might have occurred after the participant took PA breaks. Other studies have been able to show a reduction in tension [ 30 ] and general muscular discomfort [ 33 ] after PA breaks. However, this was measured as an immediate effect of PA breaks and not with general evening surveys. Blasche and colleagues [ 34 ] measured effects immediately and 20 min after different kind of breaks and found that PA breaks led to an additional short‐ and medium‐term increase in vigor while the relaxation break lead to an additional medium‐term decrease in fatigue compared to an unstructured open break. This is consistent with the results of the present study that an effect of PA breaks is only observed for functional stress and not for dysfunctional stress. Furthermore, there is evidence that long sitting during lectures leads to increased fatigue and lower concentration [ 31 , 70 ], which could be counteracted by PA breaks. For both types of stress loads, functional and dysfunctional stress, there is an influence of students´ well-being in this study. This shows that the stress load is affected by the way students have mentally felt over the last two weeks. The relevance of monitoring this seems important especially in the time of COVID-19 as, for example, 65.3% of the students of a cross-sectional online survey at an Australian university reported low to very low well-being during that time [ 71 ]. However, since PA and well-being can support functional stress load, they should be of the highest priority—not only as regards the pandemic, but also in general.

Looking at hypothesis 1.B; while there is a positive influence of LTPA on experienced psychological detachment, no significant influence for PA breaks was detected. The fact that only LTPA has a positive effect can be explained by the voluntary character of the activity [ 50 ]. The voluntary character ensures that stressors no longer affect the student and, thus, recovery as detachment can take place. Home studying is not present in leisure times, and thus detachment from study is easier. The PA break videos, on the other hand, were shot in a university setting, which would have made it more difficult to detach from study. In order to further understand how PA breaks affect recovery and whether there is a distinction between PA breaks and LTPA, future research should also consider other types of recovery (e.g. relaxation, mastery, and control). Additionally, different types of PA breaks, such as group PA breaks taken on-site versus video-based PA breaks, should be taken into account.

Considering the confirmed positive associations for academic performance-related parameters of hypothesis 2, the results are in accordance with the evidence of positive associations between PA and learning and educational success [ 6 ], as well as between PA breaks and better cognitive functioning [ 28 ]. Looking at the self-reported attention difficulties of hypothesis 2.A, only LTPA can counteract it. PA breaks showed no effects, contrary to the results of a study of Löffler and collegues (2011, [ 31 ]), in which acute effects of PA breaks could be found for higher attention and cognitive performance. Furthermore, the perception of study demands before the study periods has a positive impact on difficulties in attention. That means that overload in studies, time pressure during studies, and incompatibility of studies and private life leads to higher difficulties with attention in home studying. In these conditions, PA breaks might have been seen as interfering, resulting in the expected beneficial effects of exercise on attention and task-related participation behavior [ 72 , 73 ] therefore remaining undetected. With respect to the COVID-19 pandemic, accompanying education changes, and an increase in student´s worries [ 74 , 75 ], the perception of study demands could be affected. This suggests that especially in times of constraint and changes, it is important to promote PA in order to counteract attention difficulties. This also applies to post-pandemic phase.

Regarding the perceived academic performance of hypothesis 2.B, both PA breaks and LTPA have a positive effect on perceived study ability. This result confirms the positive short-term effects on cognition tasks [ 76 ]. It is also in line with the positive function of PA breaks in interrupting sedentary behavior and therefore counteracting the negative association between sitting behavior and lower cognitive performance [ 24 ]. Additionally, this result also fits with the previously mentioned positive relationship between LTPA and functional stress and between PA breaks and functional stress.

According to hypothesis 3, in relation to the mentioned stress load and recovery parameters, there are negative effects of the daily number of breaks during home studying and the longest stretch of time without a break spent on home studying on psychological detachment. As stressors result in negative activation, which impede psychological detachment from study during non-studying time [ 25 ], it was expected and confirmed that the longest stretch of time without a break spent on home studying has a negative effect on detachment. Initially unexpected, the number of breaks has a negative influence on psychological detachment, as breaks could prevent the accumulation of strain reactions. However, if the breaks had no recovery effect through successful detachment, the number might not have any influence on recovery via detachment. This is indicated by the PA breaks, which had no impact on psychological detachment. Since there are other ways to recover from stress besides psychological detachment, such as relaxation, mastery, and control [ 53 ], PA breaks must have had an additional impact in relation to the positive results for functional stress.

In relation to the mentioned academic performance-related parameters, only the number of breaks has a positive influence on the perceived study ability. This indicates that not only PA breaks but also breaks in general lead to better perceived functionality in studying. Paulus and colleagues (2021) found out that an increase in cognitive skills is not only attributed to PA breaks and standing breaks, but also to open breaks with no special instructions [ 28 ]. Either way, they found better improvement in self-perceived physical and psychological well-being of the university students with PA breaks than with open breaks. This is also reflected in the present study with the aforementioned positive effects of PA breaks on functional stress, which does not apply to the number of breaks.

Overall, it must be considered that the there is a more complex network of associations between the examined parameters. The hypothesized separate relation of PA with different parameters do not consider associations between parameters of stress load / recovery and academic performance although there might be a interdependency. Furthermore, moderation aspects were not examined. For example, PA could be a moderator which buffer negative effects of stress on the study ability [ 55 ]. Moreover, perceived study ability might moderate stress levels and academic performance. Further studies should try to approach and understand the different relationships between the parameters in its complexity.

Limitations

Certain limitations must be taken into account. Regarding the imbalanced design toward more female students in the sample (47 female versus 6 male), possible sampling bias cannot be excluded. Gender research on students' emotional states during COVID-19, when this study took place, or students´ acceptance of PA breaks is diverse and only partially supplied with inconsistent findings. For example, during the COVID-19 pandemic, some studies reported that female students were associated with lower well-being [ 71 ] or worse mental health trajectories [ 75 , 77 ]. Another study with a large sample of students from 62 countries reported that male students were more strongly affected by the pandemic because they were significantly less satisfied with their academic life [ 74 ]. However, Keating and colleges (2020) discovered that, despite the COVID-19 pandemic, females rated some aspects of PA breaks during lectures more positively than male students did. However, this was also based on a female slanted sample [ 78 ]. Further studies are needed to get more insights into gender bias.

Furthermore, the small sample size combined with up to 16% missing values comprises a significant short-coming. There were a lot of possibilities which could cause such missing data, like refused, forgotten or missed participation, technical problems, or deviation of the personal code for the questionnaire between survey times. Although the effects could be excluded by sensitive analysis due to missing data, the sample is still small. To generalize the findings, future replication studies are needed.

Additionally, PA breaks were only captured through participation in the ESD, the specially instructed PA break via video. Effects of other short PA breaks were not include in the study. However, participants were called to participate in ESD whenever possible, so the likelihood that they did take part in PA breaks in addition to the ESD could be ignored.

With respect to the baseline variables, it must be considered that two variables (stress load, attention difficulties) were adjusted not with their identical variable in T0, but with other conceptually associated variables (well-being index, BARI-S). Indeed, contrary to the assumption the well-being index does only show an association with functional stress, indicating that it does not control dysfunctional stress. Although the other three assumed associations were confirmed there might be a discrepancy between the daily measured variables and the variables measured in T0. Further studies should either proof the association between these used variables or measure the same variables in T0 for control the daily value of these variables.

Moreover, the measuring instruments comprised the self-assessed perception of the students and thus do not provide an objective information. This must be considered, especially for measuring cognitive and academic-performance-related measures. Here, existing objective tests, such as multiple choice exams after a video-taped lecture [ 72 ] might have also been used. Nevertheless, such methods were mostly used in a lab setting and do not reflect reality. Due to economic reasons and the natural learning environment, such procedures were not applied in this study. However, the circumstances of COVID-19 pandemic allowed a kind of lab setting in real life, as there were a lot of restrictions in daily life which limited the influence of other covariates. The study design provides a real natural home studying environment, producing results that are applicable to the healthy way that students learn in the real world. As this study took place under the conditions of COVID-19, new transformations in studying were also taken into account, as home studying and digital learning are increasingly part of everyday study.

However, the restrictions during the COVID-19 pandemic could result in a greater extent of leisure time per se. As the available leisure time in general was not measured on daily level, it is not possible to distinguish if the examined effects on the outcomes are purely attributable to PA. It is possible that being more physical active is the result of having a greater extent of leisure time and not that PA but the leisure time itself effected the examined outcomes. To address this issue in future studies, it is necessary to measure the proportion of PA in relation to the leisure time available.

Furthermore, due to the retrospective nature of the daily assessments of the variables, there may be overstated associations which must be taken into account. Anyway, the daily level of the study design provides advantages regarding the ability to observe changes in an individual's characteristics over the period of the study. This design made it possible to find out the necessity to analyze the hierarchical structure of the intraindividual data nested within the interindividual data. The performed multilevel analyses made it possible to reflect the outcome of an average student in the sample at his/her daily average behavior in PA and home study.

Conclusion and practical implications

The current findings confirm the importance of PA for university students` stress load, recovery experience, and academic performance-related parameters in home studying. Briefly summarized, it can be concluded that PA breaks positively affect stress load and perceived study ability. LTPA has a positive impact on stress load, recovery experience, and academic performance-related parameters regarding attention difficulties and perceived study ability. Following these results, universities should promote PA in both fashions in order to keep their students healthy and functioning: On the one hand, they should offer opportunities to be physically active in leisure time. This includes time, environment, and structural aspects. The university sport department, which offers sport courses and provides sport facilities on university campuses for students´ leisure time, is one good example. On the other hand, they should support PA breaks during the learning process and in the immediate location of study. This includes, for example, providing instructor videos for PA breaks to use while home studying, and furthermore having instructors to lead in-person PA breaks in on-site learning settings like universities´ libraries or even lectures and seminars. This not only promotes PA, but also reduces sedentary behavior and thereby reduces many other health risks. Further research should focus not only on the effect of PA behavior but also of sedentary behavior as well as the amount of leisure time per se. They should also try to implement objective measures for example on academic performance parameters and investigate different effect directions and possible moderation effects to get a deeper understanding of the complex network of associations in which PA plays a crucial role.

Availability of data and materials

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

Abbreviations

Attention and Performance Self-Assessment

"Berliner Anforderungen Ressourcen-Inventar – Studierende" (instrument for the perception of study demands and resources)

Centered within

Grand centered

“Erfassung von Emotionen und Beanspruchung “ (questionnaire containing a word list of adjectives for the recording of emotions and stress during work)

Exercise snack digital (special physical activity break offer)

Intra-Class-Correlation

Leisure time physical activity

• Physical activity

Recovery Experience Questionnaire

Study ability index

World Health Organization-Five Well-being index

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Acknowledgements

We would like to thank Juliane Moll, research associate of the Student Health Management of University of Tübingen, for the support in the coordination and realization study. We would like to express our thanks also to Ingrid Arzberger, Head of University Sports at the University of Tübingen, for providing the resources and co-applying for the funding. We acknowledge support by Open Access Publishing Fund of University of Tübingen.

Open Access funding enabled and organized by Projekt DEAL. This research regarding the conduction of the study was funded by the Techniker Krankenkasse, health insurance fund.

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Monika Teuber, Daniel Leyhr & Gorden Sudeck

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M.T. and G.S. designed the study. M.T. coordinated and carried out participant recruitment and data collection. M.T. analyzed the data and M.T. and D.L. interpreted the data. M.T. drafted the initial version of the manuscript and prepared the figure and all tables. All authors contributed to reviewing and editing the manuscript and have read and agreed to the final version of the manuscript.

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Teuber, M., Leyhr, D. & Sudeck, G. Physical activity improves stress load, recovery, and academic performance-related parameters among university students: a longitudinal study on daily level. BMC Public Health 24 , 598 (2024). https://doi.org/10.1186/s12889-024-18082-z

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Transforming stress through awareness, education and collaboration.

Stress Research

“The difficulty in science is often not so much how to make the discovery but rather to know that one has made it.” – J.D. Bernal

2024 Stress Statistics

The 2024 results of the American Psychiatric Association’s annual mental health poll show that U.S. adults are feeling increasingly anxious. In 2024, 43% of adults say they feel more anxious than they did the previous year, up from 37% in 2023 and 32% in 2022. Adults are particularly anxious about current events (70%) — especially the economy (77%), the 2024 U.S. election (73%), and gun violence (69%).

When asked about a list of lifestyle factors potentially impacting mental health, adults most commonly say stress (53%) and sleep (40%) have the biggest impact on their mental health. Younger adults (18-34 years old) are more likely than older adults (50+) to say social connection has the biggest impact on their mental health. Despite the increasing anxiety, most adults have not sought professional mental health support. In 2024, just one in four (24%) adults say they talked with a mental health care professional in the past year. Notably, younger adults (18-34) are more than twice as likely as older adults (50+) to have done so.

“Living in a world of constant news of global and local turmoil, some anxiety is natural and expected,” said APA President Petros Levounis, M.D., M.A. “But what stands out here is that Americans are reporting more anxious feelings than in past years. This increase may be due to the unprecedented exposure that we have to everything that happens in the world around us, or to an increased awareness and reporting of anxiety. Either way, if people have these feelings, they are not alone, and they can seek help from us.”

Among adults who have used mental health care this year, more than half prefer to meet with a mental health professional in person (55%) rather than via telehealth; 30% prefer telehealth; and 15% have no preference. Also among adults who have used mental healthcare this year, more than half (59%) are worried about losing access to mental healthcare, and 39% of insured adults are worried about losing their health insurance, as a result of the election this year.

Americans perceive broad impacts of untreated mental illness: 83% of adults say it negatively impacts families and 65% say it negatively impacts the U.S. economy. Also, 71% of adults feel that children and teens have more mental health problems than they did 10 years ago. That said, more than half of adults (55%) think there is less mental health stigma than 10 years ago.

“Over the past ten years, we’ve grown more comfortable talking about mental health, and that’s absolutely key to helping us through the current crisis,” said APA CEO and Medical Director Saul Levin, M.D., M.P.A. “The continued work of APA is to ensure that people can access care when they need it, especially in areas that need it badly, like child and adolescent psychiatry.”

Other issues people said they were anxious about include:

• Keeping themselves or their families safe, 68%.
• Keeping their identity safe, 63%.
• Their health, 63%.
• Paying bills or expenses, 63%.
• The opioid epidemic, 50%.
• The impact of emerging technology on day-to-day life, 46%.

In addition, 57% of adults are concerned about climate change.

This annual poll was conducted April 9 to 11, 2024, among a sample of more than 2,200 adults. This annual survey is complemented by APA’s Healthy Minds Monthly series, conducted by Morning Consult on behalf of APA. See  past Healthy Minds Monthly polls . For a copy of the results, contact us at  [email protected] .

American Psychiatric Association

The American Psychiatric Association, founded in 1844, is the oldest medical association in the country. The APA is also the largest psychiatric association in the world with more than 38,900 physician members specializing in the diagnosis, treatment, prevention, and research of mental illnesses. APA’s vision is to ensure access to quality psychiatric diagnosis and treatment.

Causes and Sources of Stress

Living conditions, the political climate, financial insecurity, and work issues are some stressors US adults cite as the cause of their stress. Ineffective communications increase work stress to the point of frustration that workers want to quit.  These stressors, unfortunately, are not something people can just ignore. Quitting a job would result in debt and financial instability which, in turn, would be added stressors.

• 35% of workers say their boss is a cause of their workplace stress.
• 80% of US workers experience work stress because of ineffective company communications.
• 39% of North American employees report their workload the main source of the work stress.
• 49% of 18 – 24 year olds who report high levels of stress felt comparing themselves to others is a stressor.
• 71% of US adults with private health insurance say the cost of healthcare causes them stress while 53% with public insurance say the same.
• 54% of Americans want to stay informed about the news but following the news causes them stress.
• 42% of US adults cite personal debt as a source of significant stress.
• 1 in 4 American adults say discrimination is a significant source of stress.
• Mass shootings are a significant source of stress across all races; 84% of Hispanic report this, the highest among the races.

Stress and Relationships

People under stress admit to taking out their frustration on other people. Targets for venting out include strangers and those they have personal relationships with. Men and women report different levels of how work stress affects their relationships with their spouses.

• 76% of US workers say their workplace stress has had a negative impact on their personal relationships.
• Seven in 10 adults report work stress affects their personal relationships.
• 79% of men report work stress affects their personal relationship with their spouse compared to 61% for women.
• 36% of adults reported experiencing stress caused by a friend or loved one’s long-term health condition.

Stress Management Statistics

A look at the stress management techniques employed by US adults to deal with their stress, an overwhelming majority are self-care practices. Though very helpful, it does not address the stressor at the root of the problem. Stress management programs would be beneficial not only for employees but for the company in the long run.

• 30% of Us adults eat comfort food “more than the usual” when faced with a challenging or stressful event.
• 51% of US adults engage in prayer—a routine activity—when faced with a challenge or stressful situation.
• Coping mechanisms of Gen Z and Millenials experiencing stress in the US 44% of Gen Z and 40% of Millenials sleep in while exercising counts for 14% and 20% respectively.
• 49% of US adults report enduring stressful situations as a coping behavior to handle stress.
• Less than 25% of those with depression worldwide have access to mental health treatments.

CompareCamp

American Psychological Association

Cardiac Coherence and Post-traumatic Stress Disorder in Combat Veterans

Jay P. Ginsberg, Ph.D.; Melanie E. Berry, M.S.; Donald A Powell, Ph.D.

Alternative Therapies in Health and Medicine, A Peer-Reviewed Journal, 2010;16 (4):52-60. PDF version of the complete paper: Cardiac Coherence and PTSD in Combat Veterans

Abstract-PTSD

Background: The need for treatment of posttraumatic stress disorder (PTSD) among combat veterans returning from Afghanistan and Iraq is a growing concern. PTSD has been associated with reduced cardiac coherence (an indicator of heart rate variability [HRV]) and deficits in early-stage information processing (attention and immediate memory) in different studies. However, the co-occurrence of reduced coherence and cognition in combat veterans with PTSD has not been studied before.

Primary Study Objective: A pilot study was undertaken to assess the covariance of coherence and information processing in combat veterans. An additional study goal was an assessment of the effects of HRV biofeedback (HRVB) on coherence and information processing in these veterans.

Methods/Design: A two-group (combat veterans with and without PTSD), a pre-post study of coherence and information processing was employed with baseline psychometric covariates.

Setting: The study was conducted at a VA Medical Center outpatient mental health clinic.

Participants: Five combat veterans from Iraq or Afghanistan with PTSD and five active-duty soldiers with comparable combat exposure who were without PTSD.

Intervention: Participants met with an HRVB professional once weekly for 4 weeks and received visual feedback in HRV patterns while receiving training in resonance frequency breathing and positive emotion induction.

Primary Outcome Measures: Cardiac coherence, word list learning, commissions (false alarms) in go—no go reaction time, digits backward.

Results: Cardiac coherence was achieved in all participants, and the increase in coherence ratio was significant post-HRVB training. Significant improvements in the information processing indicators were achieved. Degree of increase in coherence was the likely mediator of cognitive improvement.

Conclusion: Cardiac coherence is an index of the strength of control of parasympathetic cardiac deceleration in an individual that has cardinal importance for the individual’s attention and affect regulation.

The Effect of a Biofeedback-based Stress Management Tool on Physician Stress: A Randomized Controlled Clinical Trial

Jane B. Lemaire, Jean E. Wallace, Adriane M. Lewin, Jill de Grood, Jeffrey P. Schaefer

Open Medicine 2011; 5(4)E154. PDF version of the complete paper: physician-stress-randomized-controlled-clinical-trial

Abstract- Biofeedback-based Stress Management

Background: Physicians often experience work-related stress that may lead to personal harm and impaired professional performance. Biofeedback has been used to manage stress in various populations.

Objective: To determine whether a biofeedback-based stress management tool, consisting of rhythmic breathing, actively self-generated positive emotions and a portable biofeedback device, reduces physician stress.

Design: Randomized controlled trial measuring the efficacy of a stress-reduction intervention over 28 days, with a 28-day open-label trial extension to assess effectiveness.

Setting: Urban tertiary care hospital.

Participants: Forty staff physicians (23 men and 17 women) from various medical practices (1 from primary care, 30 from a medical specialty and 9 from a surgical specialty) were recruited by means of electronic mail, regular mail and posters placed in the physicians’ lounge and throughout the hospital.

Intervention: Physicians in the intervention group were instructed to use a biofeedback-based stress management tool three times daily. Participants in both the control and intervention groups received twice-weekly support visits from the research team over 28 days, with the intervention group also receiving re-inforcement in the use of the stress management tool during these support visits. During the 28-day extension period, both the control and the intervention groups received the intervention, but without intensive support from the research team.

Main outcome measure: Stress was measured with a scale developed to capture short-term changes in global perceptions of stress for physicians (maximum score 200).

Results: During the randomized controlled trial (days 0 to 28), the mean stress score declined significantly for the intervention group (change -14.7, standard deviation [SD] 23.8; p = 0.013) but not for the control group (change -2.2, SD 8.4; p = 0.30). The difference in mean score change between the groups was 12.5 (p = 0.048). The lower mean stress scores in the intervention group were maintained during the trial extension to day 56. The mean stress score for the control group changed significantly during the 28-day extension period (change -8.5, SD 7.6; p < 0.001).

Conclusion: A biofeedback-based stress management tool may be a simple and effective stress-reduction strategy for physicians.

Coherence Training In Children With Attention-Deficit Hyperactivity Disorder: Cognitive Functions and Behavioral Changes

Anthony Lloyd, Ph.D.; Davide Brett, B.Sc.; Ketith Wesnes, Ph.D.

Alternative Therapies in Health and Medicine, A Peer-Reviewed Journal, 2010; 16 (4):34-42

PDF version of the complete paper: coherence-training-in-children-with-adhd

Abstract-ADHD

Attention-deficit hyperactivity disorder (ADHD) is the most prevalent behavioral diagnosis in children, with an estimated 500 000 children affected in the United Kingdom alone. The need for an appropriate and effective intervention for children with ADHD is a growing concern for educators and childcare agencies. This randomized controlled clinical trial evaluated the impact of the HeartMath self-regulation skills and coherence training program (Institute of HeartMath, Boulder Creek, California) on a population of 38 children with ADHD in academic year groups 6, 7, and 8. Learning of the skills was supported with heart rhythm coherence monitoring and feedback technology designed to facilitate self-induced shifts in cardiac coherence. The cognitive drug research system was used to assess cognitive functioning as the primary outcome measure. Secondary outcome measures assessed teacher and student reposted changes in behavior. Participants demonstrated significant improvements in various aspects of cognitive functioning such as delayed word recall, immediate word recall, word recognition, and episodic secondary memory. Significant improvements in behavior were also found. The results suggest that the intervention offers a physiologically based program to improve cognitive functioning in children with ADHD and improve behaviors that is appropriate to implement in a school environment.

Coherence and Health Care Cost – RCA Actuarial Study: A Cost-Effectiveness Cohort Study

Woody Bedell; Mariette Kaszkin-Bettag, Ph.D.

Alternative Therapies in Health and Medicine, A Peer-Reviewed Journal, 2010;16 (4):26-31. PDF version of the complete paper: rca-actuarial-study-coherence-and-health-care

Abstract-Health and Medicine

Chronic stress is among the most costly health problems in terms of direct health costs, absenteeism, disability, and performance standards. The Reformed Church in America (RCA) identified stress among its clergy as a major cause of higher-than-average health claims and implemented HeartMath (HM) to help its participants manage stress and increase physiological resilience. The 6-week HM program Revitalize You! was selected for the intervention including the emWave Personal Stress Reliever technology.

From 2006 to 2007, completion of a health risk assessment (HRA) provided eligible clergy with the opportunity to participate in the HM program or a lifestyle management program (LSM). Outcomes for that year were assessed with the Stress and Well-being Survey. Of 313 participants who completed the survey, 149 completed the Revitalize You! The program and 164 completed the LSM. Well-being, stress management, resilience, and emotional vitality were significantly improved in the HM group as compared to the LSM group.

In an analysis of the claims costs data for 2007 and 2008, 144 pastors who had participated in the HM program were compared to 343 non-participants (control group). Adjusted medical costs were reduced by 3.8% for HM participants in comparison with an increase of 9.0% for the control group. For the adjusted pharmacy costs, an increase of 7.9% was found compared with an increase of 13.3% for the control group. Total 2008 savings as a result of the HM program are estimated at $585 per participant, yielding a return on investment of 1.95:1. These findings show that HM stress-reduction and coherence-building techniques can reduce health care costs.

View my collection, “Stress and Cardiovascular Disease” from NCBI

View my collection, “Stress and Cancer” from NCBI

View my collection, “Stress and Diabetes” from NCBI

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The effects of chronic stress on health: new insights into the molecular mechanisms of brain–body communication

Agnese mariotti.

1 Science Writer in Lausanne, Switzerland

Today's life rhythms and demands are often challenging and require intense physical and psychological efforts in order to be sustained. An individual reacts to physical and mental strain that is potentially health threatening by activating interconnected neuroendocrine circuits. This response allows the body to face and deal with the challenge and re-establish homeostatic equilibrium. If the individual perceives a noxious stimulus as too intense, or its duration as too long, he may fail coping with it, and incur maladaptation. In this case, the stress response does not resolve into a state of balance (either similar or new, i.e., adapted, compared with the state before stress hits), neuroendocrine parameters remain altered, and illness may ensue.

It is clear that stress has both a physical (objective) and a psychological (subjective) component: the latter, as described by Koolhaas and colleagues, depends on the individual perception of its predictability and controllability [ 1 ]. The way a person can anticipate a certain stressor and then control it, largely defines the resulting stress response, how promptly and efficiently it is activated promoting adaptation, and how fast it is turned off once equilibrium has been recovered.

The time course of the stress response, characterized by measurable neuroendocrine and behavioral indexes, thus reveals whether a destabilizing stimulus is manageable, or conversely, cannot be handled and consequently becomes harmful.

This implies that not all stimuli that elicit strong neuroendocrine responses are real stressors, but only those that exceed the individual's ability to change and adapt.

Cortical centers in the brain sense a disturbing stimulus and respond by activating pathways that through the limbic system stimulate peripheral networks, including the sympathetic–adrenal–medullary axis and the renin-angiotensin system, and later the hypothalamic–pituitary–adrenal (HPA) axis [ 2 ]. A cascade of events follows that results in the orchestration of a complex response. Adrenaline and other hormones, and neuropeptides are produced and regulate cardiovascular and metabolic functions (inducing, for instance, increases in heart rate, breath frequency, glucose release) for a prompt response concerted to overcome the challenge.

If the distressing stimulus persists, the HPA axis kicks in to sustain the immediate reaction mediated by the centrally activated peripheral systems. The HPA response starts with the hypothalamus delivering corticotropin-releasing hormone to the pituitary and culminates with the stimulation of the adrenal cortex by the pituitary-derived adrenocorticotropic hormone to produce glucocorticoids (GCs). Most organs and tissues, including sympathetic nerves, immune cells and several brain regions express GC receptors and are responsive to GCs induced by stress. Consequently, these hormones participate in the regulation of disparate stress-associated processes, from the modulation of cardiovascular effects and the immune function, to the eventual dampening of the stress response through inhibition of the HPA axis when adaptation is attained.

In situations in which the stressor is overwhelming and cannot be resolved, stress becomes chronic. In this case, the GC-dependent negative feedback mechanism that controls the stress response does not work, GC receptor resistance develops, and the systemic levels of the molecular mediators of stress remain high, compromising the immune system and damaging in the long-term multiple organs and tissues [ 3 ].

What is the actual impact of chronic stress on health?

When considering the numerous cellular targets of the chemical mediators of stress, one would expect that protracted, stress-dependent neuroendocrine dysregulation may damage directly or through functional circuits practically all organs and tissues. To clarify this assumption and identify the biochemical pathways significantly impaired by chronic stress to the extent of producing illness, researchers have on one hand searched for putative morphological tissue alterations associated with stress, and on the other analyzed the molecular mechanisms of action of the main stress hormones.

Effects of chronic stress on brain structure

It has been shown that chronic stress is linked to macroscopic changes in certain brain areas, consisting of volume variations and physical modifications of neuronal networks. For example, several studies in animals have described stress-related effects in the prefrontal cortex (PFC) and limbic system, characterized by volume reductions of some structures, and changes in neuronal plasticity due to dendritic atrophy and decreased spine density [ 4 ]. These morphological alterations are similar to those found in the brains of depressed patients examined postmortem, suggesting that they could also be at the basis of the depressive disorders that are often associated with chronic stress in humans. This hypothesis is supported by imaging studies that evidenced structural changes in the brain of individuals suffering from various types of stress-related disorders, such as those linked to severe traumas, major negative life events or chronic psychosocial strain. In particular, Blix and colleagues observed atrophy of the basal ganglia and significantly reduced gray matter in certain areas of the PFC in subjects afflicted with long-term occupational stress [ 5 ]. In general, the consequences of these alterations in a brain region can expand to other functionally connected areas, and potentially cause those cognitive, emotional and behavioral dysfunctions that are commonly associated with chronic stress, and that may increase vulnerability to psychiatric disorders.

Interlink between the brain & the immune system

The understanding of the molecular circuits that underlie brain architectural changes and medical conditions linked to chronic stress is just at the beginning. Research in this area has centered primarily on the signaling functions of those molecules that are directly induced by stress through the activation of the sympathetic-adrenal-medullary and HPA networks, focusing on their possible cellular targets. Since receptors for stress neuropeptides and hormones are broadly expressed in immune cells [ 6 ], most studies have concentrated on the effects of stress on the immune system (IS). In fact, psychological stress can induce the acute phase response commonly associated with infections and tissue damage, and increase the levels of circulating cytokines and of various biomarkers of inflammation [ 2 ]. As suggested by Maier and Watkins, the interlink between the stress response and inflammation elicited by the IS can be explained from the evolutionary perspective by considering that the stress response is an adaptive process developed by co-opting the IS mechanisms of defense [ 7 ]. In this frame, a psychological stressor, perceived by the brain as ‘danger’, that is, potentially harming, sets in motion a neuroimmune circuit that stimulates the IS to mount a protective reaction intended to prevent damage, repair it and restore homeostasis.

This neuroimmune communication is bidirectional because the cytokines produced by stress-stimulated immune cells also convey a feedback to the nervous system, further modulating the release of stress hormones in the brain, as well as brain activity that regulates behavior and cognitive functions. In a situation of chronic stress, the neuroimmune axis can be overstimulated and breaks down, thus causing neuroendocrine/immune imbalances that establish a state of chronic low-grade inflammation, a possible prelude to various illnesses [ 8 ].

Diseases whose development has been linked to both stress and inflammation include cardiovascular dysfunctions, diabetes, cancer, autoimmune syndromes and mental illnesses such as depression and anxiety disorders.

Persistent, abnormal levels of cytokines and stress chemical mediators in the brain may also damage the parenchyma and cause neuronal death, thus contributing to the brain structural changes associated with chronic stress that are described above [ 9 ].

Despite the large number of studies that have addressed the biological effects of chronic stress and their impact on human health, the emerging picture still merely outlines the biochemical and functional responses of the nervous and immune systems to long-term stress, highlighting some nodes of information exchange between the two networks, but still lacking essential elements concerning additional cellular players, and functional and molecular mechanisms.

Some recent studies have, however, significantly improved our knowledge of how chronic stress promotes two of the diseases that have long been associated with it: atherosclerosis and depression.

Effects of chronic stress on hematopoietic stem cells in cardiovascular diseases

Heidt and colleagues demonstrated how stress increases the levels of circulating inflammatory leukocytes by direct stimulation of hematopoietic stem cell proliferation [ 10 ]. In this new pathway, stress induces the release of noradrenaline by sympathetic nerve fibers targeting blood vessels in the bone marrow of mice. The catecholamine then acts on mesenchymal stem cells located in the hematopoietic niche, which express high levels of the β3 adrenergic receptors. One of the consequences of this interaction is the downregulation of the chemokine CXCL12, a known target of noradrenaline, which is normally produced by several types of niche cells, including mesenchymal stem cells. This releases the inhibition typically exerted by CXCL12 on the proliferation of hematopoietic stem and progenitor cells and on leukocyte migration, thus promoting cell division and leukocyte mobilization into the bloodstream.

Predictably, the inflammatory response induced by the activation of this neuroimmune pathway may have adverse health effects, in particular by exacerbating pre-existing medical conditions. Specifically, the study demonstrated that this mechanism became activated when atherosclerosis-prone mice ApoE -/- were subjected to long-term stress, leading to enhanced recruitment of inflammatory cells in atherosclerotic plaques, higher levels of proteases and increased plaque fragility. Most interestingly, β3-adrenergic receptor blockers opposed leukocyte production and mobilization, thus counteracting plaque inflammation.

When shifting their attention to human subjects, the scientists determined that individuals under considerable occupational stress had significantly more circulating leukocytes compared with when they were not working, suggesting that the neuroimmune mechanism they discovered might be set off by chronic stress and sustain an inflammatory reaction also in humans. If demonstrated, this would open the way to conceptually new therapeutic possibilities not only for atherosclerosis and its related complications, but also for other stress-related diseases that are aggravated by chronic inflammation.

Mechanisms of chronic stress-associated depression & brain–skeletal muscle communication

The mechanisms by which stress chemicals may induce depression are mostly undetermined. Research in this field is starting to define how multiple, independent, though often interconnected biochemical pathways affected by chronic stress concur to promote this disease.

Ota and colleagues have identified a molecular mechanism triggered by chronic stress that contributes to neuronal atrophy in specific brain areas, an anomaly that is typically observed in depressed patients, independent of the cause of depression [ 11 ]. In their study, they observed that persistent high levels of GCs, resulting from stress-induced hyperactivation of the HPA axis, stimulate the production of the molecule REDD1 in the PFC of rodents subjected to prolonged stress. REDD1 is generally induced by a variety of stressors – from energy stress, to hypoxia, to DNA damage – in most tissues and inhibits the kinase mTORC1, thus altering the phosphorylation state and function of its targets. In the brain, the interference of REDD1 with mTORC1 signaling ultimately impinges on neuronal protein synthesis, spine formation and synaptic plasticity. The inhibition of mTORC is pivotal for synaptic impairment and appears to be a central endpoint of molecular pathways turned on by chronic stress. In fact, also the decrease of brain-derived neurotrophic factor levels in response to chronic stress disrupts mTORC1 function.

Proinflammatory cytokines induced by stress are also involved in the development of chronic stress-associated depression [ 12 ]. The acute phase response generally triggered by a harmful factor implies the so-called sickness behavior that includes symptoms similar to those typical of depressive disorders, like social withdrawal, decreased physical activity, fatigue, somnolence, mood and cognitive alterations. This adaptive response is orchestrated by cytokines, and is meant to divert an individual from normal activities in order to save energy, thus facilitating a reaction against the challenge, and subsequent recovery. In the case of chronic inflammation that may set in with prolonged stress, persisting cytokine signaling in the brain prevents the resolution of sickness behavior that consequently can degenerate into depression. The biochemical mechanisms underlying cytokine-induced depression are not well defined, but they may involve alterations of serotonin and glutamatergic transmission, and induction of GC resistance [ 12 ].

One of the pathways that are implicated drives the oxidation of tryptophan (a precursor of serotonin) to Kynurenin (Kyn) and results in the brain production of several neuroactive molecules ( Figure 1 ) [ 12 ]. The enzymes tryptophan 2,3-dioxygenase and indoleamine 2,3-dioxygenase trigger the Kyn pathway in the liver and extrahepatically respectively, and can both be activated by chronic stress: tryptophan 2,3-dioxygenase in fact responds to GCs, while indoleamine 2,3-dioxygenase is induced by proinflammatory cytokines. The Kyn pathway not only affects the brain levels of serotonin and thus serotonergic transmission and its mood and behavioral effects, but it is also responsible for the production of tryptophan metabolites that have neuroinflammatory properties or can affect glutamatergic neurotransmission in the brain either positively or negatively. It follows that a shift in the pathway that favors the production of 3-hydroxykynurenine – an inducer of reactive oxygen species and inflammation – and quinolinic acid – an N- methyl- d -aspartate receptor agonist – over the antioxidant and N- methyl- d -aspartate receptor inhibitor kynurenic acid, may promote depression [ 12 ].

There is evidence that physical exercise can sustain brain health by regulating the production of neurotrophic factors, neurotransmitters, as well as inflammatory molecules. This can translate in a general enhancement of cognitive abilities, a reduced risk of neurodegenerative diseases and a mitigation of depression [ 13 ].

An interesting study has recently demonstrated that a key mechanism by which physical exercise counteracts chronic stress-dependent depression is the modulation of the Kyn pathway of tryptophan degradation [ 14 ]. In this work, Agudelo and colleagues demonstrated that skeletal muscle contraction during protracted training induces locally the interaction of the transcriptional coactivator PGC-1α1 with the transcription factors PPARα/δ, thus increasing in the muscles the expression and activity of a set of kynurenin aminotransferases (KAT). KATs catalyze the peripheral transformation of tryptophan-derived Kyn into kynurenic acid, causing a drop in the levels of circulating Kyn. Since Kyn can cross the blood–brain barrier, its peripheral catabolism has the effect to reduce also its brain concentration and so the production of neurotoxic molecules along the 3-hydroxykynurenine and quinolinic acid branch of the degradation pathway. In mice, under conditions that mimic chronic stress, the overexpression in skeletal muscles of PGC-1α1 prevents neuroinflammation, synapses impairment and depression-like behaviors that are instead observed in control animals. Similarly, the scientists found that exercise training stimulates the PGC-1α1-KAT pathway also in humans, and through this mechanism, potentially regulates those Kyn-dependent toxic effects in the brain that contribute to chronic stress-associated depression.

By identifying new signaling cascades implicated in the regulation of depression caused by chronic stress, Ota's and Agudelo's studies suggest novel areas of investigation for therapy development. Drugs that inhibit REDD1 effects on mTORC1, or that modulate brain levels of Kyn by enhancing its peripheral metabolism could improve the treatment of depression maybe also when it is not stress related. Since depressed individuals are usually reluctant to carry out regular physical exercise, drugs that mimic exercise training and reduce the plasma concentration of Kyn by acting peripherally would be of particular interest.

Biological & social implications of the latest findings in chronic stress research

These studies significantly improve our understanding of the interactions between the nervous systems and peripheral tissues and organs, and how their alterations can cause illness ( Figure 2 ). An important discovery is that if on one hand chronic stress can cause immune dysfunctions, that is, impair a peripheral function, on the other hand proper stimulation of a peripheral tissue like skeletal muscles can relieve stress symptoms and protect the brain, possibly favoring recovery. This suggests that programs of physical exercise should be formally proposed as a preventive measure to people known to be exposed to intense stress (eg., work-related stress), and could be prescribed as a form of therapy in combination with other treatments to ease mood and cognitive deficits caused by chronic stress.

In addition, Heidt's study suggests another intriguing possibility: if chronic stress can stimulate hematopoietic stem and progenitor cells through the activation of the peripheral nervous system, it is plausible that it can activate also other types of stem cells in other tissues by a similar mechanism. Bidirectional communication could in principle exist between the nervous system and every organ and tissue, and represents a general mechanism of nervous control of tissue homeostasis. A few recent studies have provided evidence that supports this hypothesis [ 15–16 ]. One of the resulting and provoking implications is that chronic stress could promote cancer development also by direct induction of uncontrolled cell proliferation.

The recognition that chronic stress can cause serious diseases has intensified research to determine the biochemical perturbations that compromise homeostasis to a degree that prevents spontaneous recovery. The picture is very complex because chronic stress appears to affect organ and system functions at multiple levels. Yet, it is by pinpointing specific biochemical processes affected by chronic stress that it will be possible to envisage solutions to stimulate resilience and control stress-dependent diseases.

It is clear that in the case of illnesses caused by heightened occupational stress, priority should be given to preventive interventions with the purpose of creating and maintaining work conditions respectful of human physiological, emotional and social needs: in other words, the work environment should stimulate growth and productivity while supporting each individual in their challenges. If certain measures could be implemented through official regulations that assure, for example, fair contracts, training, and sensible work schedules in relation to the type and load of responsibilities and the levels of physical and mental engagement implied by the job, others are less manageable because they strictly depend on human factors. Elements like discordant interactions with coworkers and superiors’ demands beyond formal agreements, that are quite common in very competitive work environments, can sharpen tensions and exaggerate the psychosocial strain to the point of causing illness, yet they usually remain overlooked and uncontrolled [ 17 ].

Financial & competing interests disclosure

The author has no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

No writing assistance was utilized in the production of this manuscript.

Open Access

This work is licensed under the Creative Commons Attribution 4.0 License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

Premium Content

Can scientists ‘solve’ stress? They’re trying.

From cardiovascular disease and obesity to a weakened immune system, the side effects of stress can be life-altering. But there may be a way to prevent those outcomes.

As modern-day stress ratchets up to what feels like unbearable levels, researchers are striving to learn more about the precise mechanisms through which it affects our body and mind. The hope is that by unlocking more about how stress works physiologically, we can find ways to prevent it from permanently harming people.

Over the last five decades, scientists have established beyond doubt that persistent stress really can poison our overall health. In addition to increasing the risk of cardiovascular disease , stress plays a role in obesity and diabetes and can weaken the immune system , leaving us more vulnerable to infectious diseases. You can recover swiftly from an episode of acute stress—for example, the alarm one might feel when caught unprepared for a presentation. Chronic stress, on the other hand, is more toxic as it is an unrelenting circumstance that offers little chance for a return to normalcy. Financial strain, having a bully for a boss, and social isolation are all examples.

Today chronic stress seems to be increasing worldwide, as people grapple with rapid socioeconomic and environmental change.   A 2023 national survey by the American Psychological Association found that stress has taken a serious toll since the start of the pandemic , with the incidence of chronic illnesses and mental health problems going up significantly, especially among those ages 35 to 44.

( Do you have chronic stress? Look for these signs. )

So far, one of the major realizations among scientists is that stress harms all of us in different and powerful ways. But is there any way to avoid it—or at least recover more quickly? Some promising avenues of research offer hope for the future.

Preventing chronic stress from harming you in the first place

Groundbreaking studies in orphans showed how stress in early life can leave an indelible mark on the brain.

For Hungry Minds

“Chronic stress in early life has more serious and lasting effects, because that’s when a lot of connections are being laid down in the brain,” says Aniko Korosi, a researcher at the University of Amsterdam who has been conducting experiments on mice to elucidate that link between early-life stress and brain development.

Korosi may have found a surprising link between stress and the resulting nutrient composition in the brain . She and her colleagues noticed that mouse pups that had been exposed to stress in the first week of their lives—having been moved from their mother’s care to a cage—had lower levels of certain fatty acids and amino acids in their brains compared with pups being raised in a stress-free environment.

She wondered if it was possible to normalize a stressed pup’s development by feeding it a diet rich in the specific nutrients its brain would be lacking. To find out, the researchers first fed a supplemented diet to the mothers so it would pass through their milk, then continued to provide it in the pups’ feed for two weeks after they were weaned. A few months later, the researchers tested the now adult mice in learning and memory. Unlike stressed mice that had never received an enriched diet, these mice did not display cognitive impairments.

( How wild animals cope with stress—from overeating to sleepless nights. )

“I was surprised that changing the nutrition could have such a powerful effect, because it’s such an easy intervention,” Korosi says.

If further studies provide more evidence of the nutritional pathway, she says, there would be a strong basis for supplementing the diets of infants born to mothers living in stressful conditions.

Developing an early warning system for stress

Katie McLaughlin, a psychologist at the University of Oregon, is investigating how mental health problems arise in adolescents as they’re going through a particularly vulnerable time in their lives, transitioning to adulthood.

She and her colleagues are still collecting data , but a smaller, precursor study tracking 30 teenagers offers clues about what the researchers might learn—and how it might help them identify stress before it goes too far.  

In that study, McLaughlin found that the extent of stress experienced by a subject in the month before their lab visit changed how their brain responded to emotionally impactful information such as when they were shown a picture of a threatening face. The brain’s prefrontal cortex, which helps regulate emotions, showed less activation when the subject had experienced higher levels of stress.

McLaughlin is optimistic that data from the ongoing study will help pinpoint changes in behavior as well as brain activity that predict the emergence of mental health problems like anxiety and depression. This could enable the development of targeted interventions delivered to teenagers at just the right time, she says. If the identified marker of stress were a sudden decrease in sleep duration or a sharp decline in social interactions, for example, it would be possible to push the intervention out to the individual on their smartphone.

“Like, here’s a reminder about good sleep hygiene, or this might be a good time to check in with your counselor at school about what’s been going on in your life,” McLaughlin explains.

( ‘Hysterical strength’? Fight or flight? This is how your body reacts to extreme stress. )

Learn more about stress and how to manage it

Preventing inflammation caused by chronic stress.

Gaining a deeper understanding of how stress affects the immune system may also help find a way to reverse those effects.

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In the 1980s, psychologist Janice Kiecolt-Glaser and her virologist husband, Ronald Glaser, began exploring the physiological impact of stress on two notably stressed segments of society: medical students and older caregivers. The researchers found the students’ immune systems were less robust when they were taking exams than during non-exam times—and that stress altered the body’s response to vaccines.

Researchers then administered the flu and pneumonia vaccines to individuals responsible for a spouse with dementia. Unlike medical students taking exams, who were likely stressed only in the short term, these people were experiencing unrelenting stress. When tested at set periods after inoculation, they had fewer antibodies compared with a control group —they couldn’t maintain their protective response. “That gave us good evidence that the changes brought on by stress were biologically meaningful,” says Kiecolt-Glaser, now an emeritus professor at the Ohio State University.

Around the same time, researchers led by Sheldon Cohen, now emeritus professor of psychology at Carnegie Mellon University, delivered cold-causing viruses into the nostrils of about 400 adult volunteers in the U.K. “The more stress they reported prior to our exposing them to a virus, the higher the risk was for them to develop a cold,” says Cohen. The duration and type of stress mattered: Chronic economic or interpersonal stress were what really put people at high risk—and the longer it went on, the greater the susceptibility to falling sick.

Cohen and his colleagues also learned that when exposed to viruses, chronically stressed people tended to produce an excess of cytokines—proteins that serve as messengers of the immune system, traveling to sites of infection and injury and activating inflammation and other cellular processes to protect the body. Too many cytokines cause an excess of inflammation.

Researchers still don’t know enough about how stress alters the immune system’s ability to regulate cytokines to devise an intervention to reduce the inflammation, but in one way, these findings signal some hope: There are clear targets for more work to be done.  

Understanding stress on a cellular level

The future of understanding and combating stress may lie in our DNA.

In 2023, Ursula Beattie, then a doctoral student at Tufts University, and her colleagues found possible evidence that stress can overwhelm DNA’s repair mechanisms . In their study, researchers repeatedly tapped on sparrow cages with pens, played the radio loudly, and other actions designed to cause distress but no physical harm. Blood and tissue samples from the sparrows after three weeks of this unpleasant treatment revealed damage to the DNA. “It’s like if you had two pieces of string coiled up, just like DNA, and you took a pair of scissors and cut them,” Beattie says.

While these kinds of double-strand breaks in DNA occur all the time in sparrows and other species, including humans, the damage is typically reversed through self-repair mechanisms. In a chronic-stress setting, “those repair mechanisms get overwhelmed, which is how we see a buildup of DNA damage,” Beattie explains. The damage in the birds appears to be the most severe in cells of the liver, she adds, suggesting that for humans, too, the extent and type of damage inflicted by stress might be different for different tissues of the body.

Separately, Kiecolt-Glaser and psychologist Lisa Christian at OSU are conducting a longitudinal study to determine whether chronic stress ages you more quickly. If results support a smaller, earlier study, it appears that chronically stressed caregivers not only are more likely to get sick and heal more slowly but they also show signs of accelerated aging.

We’re still learning how deep stress goes into our bodies. But these exploratory findings mean we’re getting closer to solving the puzzle that is stress, which promises a future where we can better meet the ongoing demand for change.

( 20 stress-relief gifts for the frazzled friend in your life. )

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