A meta-analysis of chronic exercise effects and moderating variables on depression severity and core symptoms in older adults

A meta-analysis of chronic exercise effects and moderating variables on depression severity and core symptoms in older adults | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article A meta-analysis of chronic exercise effects and moderating variables on depression severity and core symptoms in older adults Melanie Mack, Andreea Badache, Arzu Erden, Christoforos Giannaki, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6795147/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Previous meta-analyses have demonstrated the effectiveness of chronic exercise in treating depression in older adults; however, the moderating effects of intervention, population, and protocol characteristics remain unclear. This study aims to investigate the effectiveness of chronic exercise on depression severity and core symptoms of depression in older adults, as well as how intervention, population, and protocol characteristics moderate these effects. We searched Web of Science, Academic Search Complete, MEDLINE, CINAHL, APA PsycInfo, SPORTDiscus, and Cochrane from inception until July 2023 for randomized controlled trials of chronic exercise interventions. The primary outcome was overall depression severity; secondary outcomes were indicators of core symptoms of depression. We used multilevel meta-analysis, subgroup comparisons, and meta-regression for analysis. We identified 143 peer-reviewed articles comprising 182 effect sizes and representing 14,789 participants (exercise group: n = 7,664; control group: n = 7,125). Chronic exercise significantly reduced overall depression severity with a moderate effect size and alleviated indicators of core symptoms of depression, including moderate effects on anxiety and small effects on BMI, executive functions, processing speed, and sleep. Effects were particularly strong for interventions that included exergames, had high training volumes, and high cognitive demand. Additionally, effects decreased with advancing age and lower baseline depression severity. The benefits of high-cognitive-demand exercises increased with declining global cognition levels. Individuals with mild to moderate depression benefited most from high-intensity and high-cognitive-demand exercises. The certainty of evidence for reducing the severity of depression was rated as low according to the GRADE approach. There is evidence of low certainty that chronic exercise is effective in treating depression in older adults, especially when tailored to the specific needs of the target population. Scientific community and society/Social sciences/Psychology/Human behaviour Health sciences/Medical research/Clinical trial design/Randomized controlled trials Health sciences/Health care/Geriatrics aging depressive symptoms meta-regression physical activity exercise intervention Figures Figure 1 Figure 2 Figure 3 Introduction Depression is one of the most common mental health conditions among older adults 1 , 2 .Older adults are particularly vulnerable to depression due to adverse life events, such as losing a spouse, chronic illnesses, and transitions to nursing homes 2 , 3 , which are often associated with increased physical inactivity and reduced functional capacity 4 . Chronic exercise has recently gained attention as a non-pharmacological approach to ameliorate late-life depression 5 , 6 . Data from systematic reviews on older adults with and without a clinical diagnosis of depressive disorder reveal a moderate effect of exercise on reducing depression severity compared to control groups 5 , 7 . However, these effects show a considerable heterogeneity, likely due to differences in exercise protocols and participant characteristics 8 – 12 . Exercise interventions benefit older adults with depression through a variety of psychological and physiological mechanisms. Among the psychological benefits is improved self-esteem 13 , while physiological effects include anti-inflammatory responses and enhanced neuroplasticity 14 . The efficacy of exercise depends on training characteristics such as the FITT principles (Frequency, Intensity, Time, and Type) 15 and is further influenced by individual factors, including depression severity, age, sex, physical fitness, cognitive function, and comorbidities 16 . To produce reliable and clinically relevant evidence on the effects of exercise in late-life depression, it is crucial to consider the question of "what works for whom", a key concept in precision or personalized medicine 17 . However, current research lacks concrete, evidence-based conclusions about the most effective treatments for specific individuals 5 . In this review, we aim to investigate how intervention and population characteristics moderate the effects of chronic exercise on depression severity and core depressive symptoms in older adults. Risks of bias due to methodological quality (RoB2) 18 , 19 , publication bias (e.g., small study effects), and evidence quality (GRADE) 20 were evaluated in order to ensure that the findings are robust and can inform clinical guidelines and policy recommendations. Results Study selection and characteristics A total of 20,700 titles and abstracts were screened, followed by a review of 523 full-text articles for potential inclusion. Of these, 143 RCTs, encompassing 182 effect sizes, were included for data extraction in the meta-analysis (Figure 1). Among the 143 studies reporting on depression severity, 24 also included data on anxiety, 6 on apathy, 13 on BMI, 18 on executive functions, 8 on fatigue, 6 on mood, 14 on sleep quality, and 11 on processing speed. The list of references corresponding to the 143 included studies is available in supplementary material 10. Key characteristics of the included studies are summarized in Table 1 and detailed at the study level in supplementary material 11. The list of excluded studies based on full-text screening is available in supplementary materials 12 and the main reason of exclusion listed in supplementary material 13. --------------------------------------- Insert Figure 1 about here --------------------------------------- --------------------------------------- Insert Table 1 about here --------------------------------------- Depression severity Chronic exercise significantly improved overall depression severity compared to a control group with a moderate effect size ( g = - 0.67, [95% CI , -0.81 to 0.53], P < .0001; Figure 2). Substantial heterogeneity was observed (I² = 96.92 %, Q = 1208.06, P < .0001), warranting further exploration. --------------------------------------- Insert Figure 2 about here --------------------------------------- Egger’s test suggested potential publication bias in the included studies, with smaller studies (larger standard errors) reporting larger effect sizes (Intercept = 0.60, P < .0001; Slope = -4.38, P < 0.0001). This was further supported by an asymmetrical funnel plot (Figure 3). Sensitivity analyses using the trim-and-fill method were conducted to adjust for this bias, resulting in an estimation of 54 missing studies on the right-hand side (see Figure supplementary material 15). The SCMC was reduced but still significant after imputation of the missing studies (SMD = -024 [95% CI , -0.40 to -0.07], P = .005 compared to SMD = 0.24 [95% CI , -0.40 to -0.07], P = .006 without the imputed studies). Methodological quality assessed with RoB2 did not significantly influence chronic exercise effects on depression severity (Table 3). The table of risk of bias for each RCT is presented in supplementary material 14. The GRADE rating indicated a low certainty of evidence. --------------------------------------- Insert Figure 3 about here --------------------------------------- Core symptoms of depression Regarding the secondary outcomes, which reflect core symptoms of depression, chronic exercise significantly decreased anxiety ( g = -0.56 [95% CI , -0.82 to -0.30], P < .0001) and BMI ( g = -0.26 [95% CI , -0.45 to -0.08], P = .005), improved executive functions ( g = -0.33 [95% CI , -0.55 to -0.10], P = .004), sleep quality ( g = -0.47 [95% CI , -0.74 to -0.20], P = .0006), and processing speed ( g = -0.35 [95% CI , -0.64 to -0.07], P = .015). No significant effects were observed for apathy, fatigue, and mood (Table 2, additional forest plots can be found in supplementary material 15, Figures S1 to S8). --------------------------------------- Insert Table 2 about here --------------------------------------- Moderation of intervention characteristics An analysis of the moderation of exercise intervention characteristics showed that the exercise type influenced chronic exercise effects on depression severity (QM(6) = 13.52, P = .035). Exergames were associated with the greatest effects on depression severity ( g = -1.24), followed by resistance exercises ( g = -0.88), mind-body exercises ( g = 0.83), dance ( g = -0.65), multi-component exercises ( g = -0.53), aerobic exercises ( g = -0.52), and coordinative exercises ( g = -0.51). Exergames showed significantly higher effects than aerobic exercises ( Est = 0.71 [95% CI , 0.15 to 1.27], P = .012) and multi-component exercises ( Est = 0.71 [95% CI , 0.14 to 1.28], P = .015). Additionally, mind-body exercises showed significantly higher effects than multi-component exercises ( Est = 0.30 [95% CI , 0.02 to 0.58], P = .037). No other post-hoc comparisons revealed significant differences. Furthermore, interventions with a higher training volume were associated with greater effects of chronic exercise on depression severity – but not those with a longer duration alone (intervention duration: QM(1) = 0.04, Est = -0.001 [95% CI , -0.010 to 0.014], P = .839; training volume: QM(1) = 3.87, Est = -0.0001 [95% CI , -0.0002 to 0.0000], P = .049). Similarly, interventions with higher cognitive demand were linked to a greater effect of chronic exercise on depression severity compared to interventions with a lower cognitive demand (QM(1) = 8.35, Est = 0.352 [95% CI , 0.1 to 0.58], P = .004). By contrast, intensity, session duration, session frequency, social interaction, and autonomy did not significantly influence chronic exercise effects on depression severity. Additional statistics on the moderation results for exercise characteristics are provided in Table 3, with related figures available in supplementary material 15 (Figures S9 to S30). --------------------------------------- Insert Table 3 about here --------------------------------------- Moderation of population characteristics Analysis of the moderation of population characteristics revealed that age significantly moderated chronic exercise effects on depression severity, with older populations experiencing lower reductions in depression severity (QM(1) = 12.75, Est = 0.03 [95% CI , 0.02 to 0.05], P = .0004). Similarly, baseline depression severity was significantly associated with chronic exercise effects on depression severity (QM(2) = 10.95, P = .004), with participants with severe depression showing the largest reduction ( g = -1.06), followed by participants with mild to moderate depression ( g = -0.81) and participants with very mild depression ( g = -0.42). Post-hoc analysis indicated significant differences between very mild and severe depression groups ( Est = -0.64 [95% CI , -1.09 to -0.19], P = .006) and between very mild and mild to moderate groups ( Est = -0.39 [95% CI , -0.65 to -0.12], P = .005). By contrast, other population characteristics, including sex, education, global cognition, handgrip strength, 6-minute walk test performance, and population, did not significantly influence chronic exercise effects on depression severity. Additional statistics on the moderation results for population characteristics are provided in Table 3, with related figures available in supplementary material 15. Moderation of protocol characteristics Analysis of protocol characteristics showed that neither the control group type, type of analysis, nor study design significantly influenced the effects of chronic exercise on depression severity. Additional statistics on the moderation results for exercise characteristics are provided in Table 3, with related figures available in supplementary material 15. Moderation between interactions of intervention and population characteristics When testing interactions between different moderators, the interaction between cognitive demand and depression severity reached significance: QM(5) = 19.84, P = .001. Post-hoc tests showed that high cognitive demanding exercises were more beneficial than low cognitive demanding exercises for mild to moderate depression only (low: g = -0.63, high: g = -1.08; Est = 0.46 [95% CI , 0.10 to 0.82], P = .012; see supplementary material 16, Figure S31). Similarly, the interaction between the cognitive demand of exercise and global cognition at baseline was significant: QM(3) = 9.83, P = .020. While high cognitive demanding exercises were more beneficial for participants with low global cognition at baseline than for those with high global cognition, low cognitive demanding exercises were more beneficial for participants with high global cognition than for those with low global cognition ( Est = -0.08 [95% CI , -0.14 to -0.02], P = .016; see supplementary material 16, Figure S32). In addition, the interaction between exercise intensity and depression severity was significant: QM(8) = 15.88, P = .044. The effect of exercise intensity was significant only for participants with mild to moderate depression severity (supplementary material 16, Figure S33): in this population, vigorous intensity was significantly more beneficial than moderate intensity ( Est = 0.48 [95% CI , 0.02 to 0.95], P = .042) and marginally more beneficial than light intensity ( Est = 0.43[95% CI , -0.04 to 0.91], P = .075). Finally, the interaction between age and cognitive demand of the exercise, the interaction between age and exercise intensity, the interaction between exercise type and exercise intensity, and the interaction between intervention duration and exercise intensity did not reach significance. Further details on the moderation effects of exercise characteristics are provided in Table 3, with related figures in supplementary material 15, Figures S35 to S38. Discussion To the best of our knowledge, this meta-analysis represents the most comprehensive synthesis of the effects of chronic exercise on depression severity and indicators of core symptoms of depression in older adults, both with and without a diagnosed depressive disorder. The analysis revealed that chronic exercise significantly improved overall depression severity, yielding a moderate effect size. However, the certainty of evidence was rated as low. Moderate improvements were also observed for indicators of core symptoms of depression such as anxiety, whereas small effect sizes were identified for BMI, executive functions, sleep, and processing speed. The effects of chronic exercise were particularly large for interventions that included exergames, had a greater training volume, and involved high cognitive demand. The benefits of chronic exercise further decreased with advancing age and increased with increasing baseline depression severity. Furthermore, participants with mild to moderate baseline depression experienced greater benefits from exercises with higher cognitive demands, and vigorous intensity, which was not observed in participants with very light or severe depression. Finally, participants with lower global cognition benefited more from exercises with high cognitive demands compared to those with low cognitive demands. The present findings on the overall effects of chronic exercise on depression severity align with those of an umbrella review on twelve meta-analyses, which reported a statistically significant moderate effect and a high heterogeneity 5 . We extend these findings by systematically examining several potential moderators that may explain this heterogeneity in effect sizes. In addition, the findings on the secondary outcomes including anxiety, executive functions, and processing speed align with prior research highlighting the benefits of exercise for anxiety symptoms 21 and cognitive functioning 22 . Given the frequent co-occurrence of depression, anxiety, and cognitive decline, as well as their high prevalence and its contribution to increased morbidity and mortality 23 , exercise presents a promising intervention for comprehensively addressing those symptoms. Exercise did not significantly improve the depressive symptoms of apathy, fatigue, or mood 24 , 25 . The lack of effects for apathy, fatigue, and mood may partly reflect limited statistical power, as these outcomes were assessed in fewer studies and showed high heterogeneity. Apathy, often seen in neuropsychiatric conditions, was primarily examined in participants with neurodegenerative disorders, making it difficult to determine whether it stemmed from the underlying condition, depression, or both 26 . Similarly, fatigue, known to respond poorly to antidepressant treatment, remains understudied as a primary outcome in exercise-based depression interventions 27 . In terms of the effects of exercise type, the results of this review align with previous meta-analyses that compared aerobic, resistance, and mind-body exercises, finding them similarly effective in reducing depression severity in older adults 9 , 28 , 29 . By including additional exercise types in our analysis, we found that exergames yielded the highest effect sizes, highlighting the value of incorporating cognitively stimulating elements into exercise regimens. This conclusion is further supported by our findings that exercise interventions with higher cognitive demand were more effective than those with lower cognitive demand and that the benefits of high-cognitive-demand exercises appear to increase as global cognition levels decline. In addition to the type of exercise, training volume appears to be another exercise-related characteristic that moderates the effects of the intervention. Specifically, higher intervention volumes were associated with larger effect sizes, indicating a dose–response relationship. Training volume, as operationalized in this meta-analysis, is a composite metric encompassing intervention duration, session duration, and frequency. This aggregation reflects the cumulative exposure of participants to the intervention over time. Interestingly, when these components were analyzed individually, none of them significantly moderated the intervention effects. This finding suggests that it is not any single aspect of the intervention structure that drives efficacy, but rather the synergistic effect of total intervention volume. These results underscore the importance of considering total training load as a more holistic and informative parameter when designing or evaluating exercise interventions, particularly in populations where time commitment and adherence may vary considerably. However, the moderating effect of training volume was relatively small and accompanied by substantial heterogeneity, consistent with the possibility of more complex dose-response relationships, such as U-shaped curves that may vary across different exercise types and intensities (for a more detailed analysis and discussion of dose-response relationships, see previous reviews 30 , 31 ). Exercise intensity interacted with depression severity at baseline, showing that vigorous intensity was more beneficial than light or moderate intensity for individuals with moderate depression but not for those with mild or severe depression. This may be due to moderate depression benefiting from stronger physiological and psychological responses, such as endorphin release and improved self-efficacy 32 . Those with low depression severity at baseline may have limited room for improvement, while severe depression may hinder engagement with high-intensity activity. Results for severe depression should be interpreted cautiously, as only two studies investigated vigorous exercise in this group. Similarly, the cognitive demand of exercise interacted with depression severity at baseline, with high-demand exercises being more beneficial for mild to moderate depression but not for low or severe depression. This may be because mild to moderate depression benefits from cognitive engagement, while low severity offers less room for improvement and severe depression may struggle with the added cognitive challenge 33 , reducing adherence and effectiveness. For the primary outcome, i.e., depression severity, the certainty of evidence was rated as low, mainly due to a high risk of bias (58% of the studies analyzed by the Rob2 tool were identified as having a high risk in at least two domains), publication bias due to small study effects, and the substantial heterogeneity among the results. Conclusion This meta-analysis highlights the significant benefits of chronic exercise not only on depression severity but also on several core symptoms of depression in older adults. The findings indicate that interventions with greater training volume and higher cognitive demands such as for instance exergames are particularly effective. Individuals with mild to moderate depression seem especially sensitive to the positive effects of high-intensity and high-cognitive-demand exercises, which may be physically and cognitively overwhelming for those with severe depression. However, the findings of the meta-analyses must be interpreted with caution due to the low certainty of evidence. To avoid bias in measurement of the outcome, we recommend adopting more blinded assessment methods, such as assessments of depression severity conducted by a blinded experimenter through an interview. In the same way, to avoid bias due to deviation from intended interventions, we recommend to include an active control group engaged in exercise and to control for confounding factors, such as self-efficacy to follow the intervention programs and physical activity practiced beside the intervention programs. Additionally, further research is crucial to understand the effects of exergames and high-intensity interventions on severe depression. Methods Search strategy and selection criteria This systematic and meta-analytic review has been registered in PROSPERO (registration number: CRD42022361418) and the protocol has been described in detail elsewhere 34 . It followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines (supplementary material 1), with any amendments to the protocol documented in supplementary material 2. Web of Science, MEDLINE, CINAHL, APA PsycInfo, SPORTDiscus, and the Cochrane Central Register of Controlled Trials were searched from inception to July 2023, using keywords for 'depression', 'chronic exercise', 'randomized controlled trials' (RCTs), and 'older adults' (supplementary material 3). References sections in selected articles, and published meta-analyses were also reviewed for additional studies. RCTs comparing exercise interventions to active or passive control groups in older adults (mean age minus standard deviation ≥ 50 years) with at least mild depression severity, assessed by validated scales, were included. Studies were limited to exercise-only interventions (with at least one intervention group focused solely on exercise), excluding those that included additional components such as nutrition, cognitive behavioral therapy, or pharmacotherapy. Study selection followed a three-step procedure using Rayyan: (1) duplicate removal, (2) title and abstract screening, and (3) full-text screening. Pairs of investigators (MM, AB, AE, CDG, SH, AK, BA, YN, IP, PS, CVR, MA) independently evaluated studies based on predefined guidelines (supplementary materials 4 and 5). Discrepancies were resolved through consensus or arbitration by a panel of investigators (MM, MA). Search strategy and selection criteria were outlined in detail in the study protocol 34 . The flow chart of the selection process is described in Fig. 1 . Outcomes Primary outcomes were depression severity at baseline and at the intervention endpoint, assessed using validated scales through self-reports and external ratings by clinicians or investigators. A list of the included rating scales is provided in supplementary material 6. Secondary outcomes encompassed indicators of core symptoms of depression, as defined in the DSM-5 (i.e., sleep quality, fatigue, anxiety, mood, apathy, BMI, processing speed, and executive functions) at baseline and at the intervention endpoint. We listed the scales used for each symptom in the supplementary material 7. When studies reported multiple outcomes (e.g., using different scales or intervention arms), all measures were included in the analysis. Additional details on the outcomes can be found in the study protocol 34 . Data extraction and quality assessment Data extraction was performed using REDCap. For each study, the following variables were coded: primary and secondary outcome measures (means and SDs), intervention characteristics (session frequency, exercise intensity, session duration, intervention duration, exercise type, training volume, cognitive demand, social interaction, autonomy), population characteristics (age, sex, population, education, global cognition, handgrip strength, 6-min walk test, depression severity), and protocol characteristics (control group, type of analysis, study design). These variables are operationalized as specified in the study protocol 34 . In cases of missing outcome data, study authors were contacted to obtain the necessary information. If no response was received, outcome data were extracted from published figures where feasible. The risk of bias was assessed using the revised Cochrane Risk-of-Bias Tool for Randomized Trials (RoB2, version 2) 18 , 19 . Pairs of investigators (MM, AB, AE, CDG, SH, AK, BA, YN, IP, PS, CVR, MA) independently extracted data and assessed bias following predefined guidelines (supplementary materials 8 and 9). Discrepancies were resolved through consensus or arbitration by a review panel (MM, MA). Details on data extraction and quality assessment are described in the study protocol 34 . The quality of evidence was assessed for the primary outcome depression severity using the GRADE approach 20 with the software GRADEpro ( https://www.gradepro.org/ ). Two independent investigators (MM, MA) individually completed the GRADE assessments. Discrepancies were resolved through discussion. Subsequently, two additional investigators reviewed and approved the final GRADE ratings (CVR, CDG). Data analysis For studies published multiple times, all articles related to the same RCT were considered. Statistical analyses were performed using Comprehensive Meta-Analysis software (CMA, version 4), and R (version 4.2.2) 35 . Standardized Comparative Mean Change scores (SCMC) were calculated for each primary and secondary outcome using Hedges’ g with 95% CIs, representing the difference in changes from baseline to intervention endpoint between the exercise and control groups. A negative g indicated greater efficacy of exercise interventions relative to controls. Effect sizes were inverted for measures where higher scores reflected higher performance (i.e., sleep quality, executive functions). We first analyzed the effect of exercise compared to a control group on the primary outcome of depression severity. To account for multiple measurements (i.e., multiple effect sizes for depression severity) – arising from the use of different depression scales, exercise interventions, and control groups within one study – we employed multilevel models with outcomes nested within studies. Between-study heterogeneity was assessed using Q statistics and I². Publication bias due to small-study effects was evaluated with a funnel plot, Egger’s regression test, and the trim-and-fill method. Sensitivity analysis for publication bias, based on study quality, was conducted through moderation analysis using the RoB2 results. We then examined the effect of exercise on secondary outcomes using random-effects models, with Q statistics and I² assessing heterogeneity. A moderation analysis was conducted to determine whether intervention characteristics, population characteristics, protocol characteristics, or theoretically meaningful interactions between moderators, moderated the effectiveness of exercise interventions on the primary outcome of depression severity. These interactions were included based on the assumption that certain characteristics may influence one another in determining intervention effectiveness (e.g., more intensive interventions might be particularly beneficial for individuals with higher baseline levels of depression). The Cochrane Q test was used to evaluate the significance of these moderators. For significant moderation effects, further post-hoc comparisons were conducted for categorical moderators and interactions reporting estimates and standard errors by comparing each factor level against the other. The full dataset is freely available through the Open Science Framework (OSF; DOI: 10.17605/OSF.IO/ZNWE8 ). Declarations Author contributions Conceptualisation: Melanie Mack, Christoforos D. Giannaki, Claudia Voelcker-Rehage, Michel Audiffren Data curation: Melanie Mack, Andreea Badache, Arzu Erden, Christoforos D. Giannaki, Sandra Haider, Antonia Kaltsatou, Burcu Kömürcü Akik, Yaël Netz, Iuliia Pavlova, Pinelopi S.Stavrinou, Claudia Voelcker-Rehage, Michel Audiffren Formal analysis: Melanie Mack, Michel Audiffren Funding acquisition: Yaël Netz Investigation: Melanie Mack, Andreea Badache, Arzu Erden, Christoforos D. Giannaki, Sandra Haider, Antonia Kaltsatou, Burcu Kömürcü Akik, Yaël Netz, Iuliia Pavlova, Pinelopi S.Stavrinou, Claudia Voelcker-Rehage, Michel Audiffren Methodology: Melanie Mack, Michel Audiffren Project administration: Melanie Mack, Christoforos D. Giannaki, Claudia Voelcker-Rehage, Michel Audiffren Resources: - Software: Melanie Mack, Michel Audiffren Supervision: Melanie Mack, Christoforos D. Giannaki, Claudia Voelcker-Rehage, Michel Audiffren Validation: Melanie Mack, Christoforos D. Giannaki, Claudia Voelcker-Rehage, Michel Audiffren Visualisation: Melanie Mack, Michel Audiffren Writing – original draft: Melanie Mack, Michel Audiffren Writing – review & editing: Melanie Mack, Andreea Badache, Arzu Erden, Christoforos D. Giannaki, Sandra Haider, Antonia Kaltsatou, Burcu Kömürcü Akik, Yaël Netz, Iuliia Pavlova, Pinelopi S.Stavrinou, Claudia Voelcker-Rehage, Michel Audiffren Conflict of interest disclosure All the authors of this manuscript are members of the COST network PhysAgeNet (CA 20104). The authors have declared that no competing interest exists. Funding / support This publication is based upon work from EU COST Action CA20104 - Network on evidence-based physical activity in old age (PhysAgeNet), Working Group 1 supported by COST (European Cooperation in Science and Technology): https://www.cost.eu/, https://physagenet.eu/. Role of the funder / sponsor The funding sources had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. References Jalali A et al (2024) Global prevalence of depression, anxiety, and stress in the elderly population: a systematic review and meta-analysis. BMC Geriatr 24:809 Zenebe Y, Akele B, Selassie W, M., Necho M (2021) Prevalence and determinants of depression among old age: a systematic review and meta-analysis. Ann Gen Psychiatry 20:55 Chang-Quan H et al (2010) Health status and risk for depression among the elderly: a meta-analysis of published literature. Age Ageing 39:23–30 World Healthh Organisation WHO Guidelines on Physical Activity and Sedentary Behaviour . https://www.who.int/publications/i/item/9789240015128 Bigarella LG et al (2022) Exercise for depression and depressive symptoms in older adults: an umbrella review of systematic reviews and Meta-analyses. Aging Mental Health 26:1503–1513 Niemeijer A et al (2020) Adverse events of exercise therapy in randomised controlled trials: a systematic review and meta-analysis. Br J Sports Med 54:1073–1080 Catalan-Matamoros D, Gomez-Conesa A, Stubbs B, Vancampfort D (2016) Exercise improves depressive symptoms in older adults: An umbrella review of systematic reviews and meta-analyses. Psychiatry Res 244:202–209 Schuch FB, Dunn AL, Kanitz AC, Delevatti RS, Fleck MP (2016) Moderators of response in exercise treatment for depression: A systematic review. J Affect Disord 195:40–49 Miller KJ et al (2020) Comparative effectiveness of three exercise types to treat clinical depression in older adults: A systematic review and network meta-analysis of randomised controlled trials. Ageing Res Rev 58:100999 Bo A, Mao W, Lindsey MA (2017) Effects of mind–body interventions on depressive symptoms among older Chinese adults: a systematic review and meta-analysis. Int J Geriat Psychiatry 32:509–521 Klil-Drori S, Klil-Drori AJ, Pira S, Rej S (2020) Exercise Intervention for Late-Life Depression: A Meta-Analysis. J Clin Psychiatry 81 Dauwan M et al (2021) Physical exercise improves quality of life, depressive symptoms, and cognition across chronic brain disorders: a transdiagnostic systematic review and meta-analysis of randomized controlled trials. J Neurol 268:1222–1246 Park S-H, Han KS, Kang C-B (2014) Effects of exercise programs on depressive symptoms, quality of life, and self-esteem in older people: A systematic review of randomized controlled trials. Appl Nurs Res 27:219–226 De Sousa RAL et al (2021) Molecular mechanisms of physical exercise on depression in the elderly: a systematic review. Mol Biol Rep 48:3853–3862 Medicine AC (2013) of S. ACSM’s Guidelines for Exercise Testing and Prescription . (Lippincott williams & wilkins Alexopoulos GS (2005) Depression in the elderly. Lancet 365:1961–1970 Ahmed A, Van Den Muijsenbergh METC, Vrijhoef HJ (2022) M. Person-centred care in primary care: What works for whom, how and in what circumstances? Health Social Care Comm 30 Higgins JP et al (2016) A revised tool for assessing risk of bias in randomized trials. Cochrane Database Syst Rev 10:29–31 Sterne JAC et al (2019) RoB 2: a revised tool for assessing risk of bias in randomised trials. BMJ l4898 10.1136/bmj.l4898 Guyatt G et al (2011) GRADE guidelines: 1. Introduction—GRADE evidence profiles and summary of findings tables. J Clin Epidemiol 64:383–394 Stonerock GL, Hoffman BM, Smith PJ, Blumenthal JA (2015) Exercise as Treatment for Anxiety: Systematic Review and Analysis. Ann Behav Med 49:542–556 Chen F-T et al (2020) Effects of Exercise Training Interventions on Executive Function in Older Adults: A Systematic Review and Meta-Analysis. Sports Med 50:1451–1467 Lenze EJ (2003) Comorbidity of depression and anxiety in the elderly. Curr Psychiatry Rep 5:62–67 Arent SM, Landers DM, Etnier JL (2000) The Effects of Exercise on Mood in Older Adults: A Meta-Analytic Review. 10.1123/japa.8.4.407 Reed J, Buck S (2009) The effect of regular aerobic exercise on positive-activated affect: A meta-analysis. Psychol Sport Exerc 10:581–594 Steffens DC, Fahed M, Manning KJ, Wang L (2022) The neurobiology of apathy in depression and neurocognitive impairment in older adults: a review of epidemiological, clinical, neuropsychological and biological research. Transl Psychiatry 12:1–16 Demyttenaere K, De Fruyt J, Stahl SM (2005) The many faces of fatigue in major depressive disorder. Int J Neuropsychopharmacol 8:93–105 Miller KJ et al (2021) Aerobic, resistance, and mind-body exercise are equivalent to mitigate symptoms of depression in older adults: A systematic review and network meta-analysis of randomised controlled trials. F1000Res 9, 1325 Rhyner KT, Watts A (2016) Exercise and Depressive Symptoms in Older Adults: A Systematic Meta-Analytic Review. 10.1123/japa.2015-0146 Tian S et al (2024) Comparative efficacy of various exercise types and doses for depression in older adults: a systematic review of paired, network and dose–response meta-analyses. Age Ageing 53:afae211 Tang L et al (2024) Optimal dose and type of exercise to improve depressive symptoms in older adults: a systematic review and network meta-analysis. BMC Geriatr 24:505 Mann T, Lamberts RP, Lambert MI (2013) Methods of Prescribing Relative Exercise Intensity: Physiological and Practical Considerations. Sports Med 43:613–625 Horne SJ, Topp TE, Quigley L (2021) Depression and the willingness to expend cognitive and physical effort for rewards: A systematic review. Clin Psychol Rev 88:102065 Mack M et al (2024) Chronic exercise effects on overall depression severity and distinct depressive symptoms in older adults: A protocol of a systematic and meta-analytic review. PLoS ONE 19:e0297348 Team RDC (2010) R: A language and environment for statistical computing. (No Title) Tables Table 1: Summary of the key characteristics of the included studies Variable NO ES N or Mean / SD Number of articles ( N ) 143 Number of ES 182 Number of participants Exercise group ( N ) 182 7664 Control Group ( N ) 182 7125 Age in years ( Mean / SD ) 181 72.60 / 7.07 % female ( Mean / SD ) 168 68.91 / 21.11 Population 192 Asymptomatic 65 Neurodegenerative diseases 28 Depressive disorder 26 Cognitive impairment 17 Other diseases 17 Cardiovascular diseases 15 Other disabilities 14 Education in years ( Mean / SD ) 85 10.06 / 3.88 Handgrip strength in kg ( Mean / SD ) 27 19.63 / 6.17 Six-min walk test in m ( Mean / SD ) 23 358.55 / 115.88 Global cognition ( Mean / SD ) 76 22.60 / 5.44 Depression severity 182 Very light 70 Mild to moderate 99 severe 13 Exercise type 182 Multi-component 64 Mind-body 36 Aerobic 31 Resistance 29 Dance 10 Exergames 8 Coordinative 4 Exercise intensity 178 Light 61 Moderate 88 Vigorous 29 Session duration in min ( Mean / SD ) 172 49.48 / 21.43 Session frequency (NO session per week) 177 3.10 / 1.81 Intervention duration (weeks) 175 14.43 / 10.69 Training volume (in min) 172 1956.63 / 1568.03 Cognitive demand 181 Low 103 High 78 Social interaction 170 Group-based 111 Individual-based 46 Mixed 13 Autonomy 176 Supervised 139 Mixed 21 Home-based 16 Control group 182 Passive 119 Active 63 Type of analysis 182 Complete case 125 Intention-to-treat 43 Per-protocol 14 Study design 182 Parallel-group 165 Cluster 17 Table 2: Summary of effect sizes and heterogeneity across outcomes Outcome k Hedges' g 95% CI z P Q (P) I 2 Depression severity 182 -0.67 -0.81, -0.53 -9.54 < .0001 1208.06 (< .0001) 96.92 % Anxiety 24 -0.56 -0.82, -0.30 -4.21 < .0001 108.54 (< .0001) 78.81 % Apathy 6 -0.57 -1.45, 0.32 -1.25 .210 26.49 (< .0001) 81.13 % BMI 13 -0.26 -0.45, -0.08 -2.83 .005 11.44 (.492) 4.89 % Executive functions 18 -0.33 -0.55, -0.10, 2.85 .004 73.32 (< .0001) 76.81 % Fatigue 8 -0.51 -1.35, 0.33 -1.18 .237 59.60 (< .0001) 88.25 % Mood 6 -0.54 -1.37, 0.28 -1.29 .198 42.86 (< .0001) 88.34 % Sleep 14 -0.47 -0.74, -0.20 3.42 < .001 51.42 (< .0001) 74.72 % Processing speed 11 -0.35 -0.64, -0.07 -2.42 .015 34.39 (.0002) 70.92 % Table 3: Results on moderator analysis for chronic exercise effects on depression severity Moderator k df QM p Q (P) Study quality RoB2 182 3 0.28 .871 1207.15 (< .0001) Exercise characteristics Exercise type 182 6 13.52 .035 1071.52 (< .0001) Exercise intensity 182 2 4.56 .102 1172.79 (< .0001) Session duration (min) 172 1 0.23 .635 1093.65 (< .0001) Session frequency (session / week) 177 1 0.11 .741 1147.59 (< .0001) Intervention duration (weeks) 181 1 0.04 .836 1149.08 (< .0001) Training volume (min) 172 1 3.87 .049 1141.24 (< .0001) Cognitive demand 181 1 8.35 .004 1159.96 (< .0001) Social interaction 170 2 5.19 .075 1032.60 (< .0001) Autonomy 176 2 4.33 .115 1154.82 (< .0001) Population characteristics Age 181 1 12.66 .0004 1119.47 (< .0001) Sex 168 1 0.98 .321 1137.87 (< .0001) Population 182 6 6.70 .349 1179.85 (< .0001) Education 85 1 0.07 .797 506.85 (< .0001) Global cognition 76 1 1.07 .301 355.38 (< .0001) Handgrip strength 27 1 0.61 .433 248.77 (< .0001) 6-min walk test 23 1 0.10 .763 267.69 (< .0001) Depression severity at baseline 182 2 10.95 .004 1129.07 (< 0.0001) Protocol characteristics Control group 182 1 1.08 .300 1203.80 (< .0001) Type of analysis 182 2 3.75 .153 1147.47 (< .0001) Study design 182 1 0.93 .336 1195.98 (< .0001) Interaction between moderators Exercise type x Exercise intensity 60 5 2.27 .810 365.74 (< .0001) Cognitive demand x Depression severity at baseline 181 5 19.84 .001 1087.32 (< .0001) Cognitive demand x global cognition 76 3 9.83 .020 294.64 (< .0001) Age x Cognitive demand 180 3 20.70 < .0001 1069.75 (< .0001) Age x Exercise intensity 178 5 17.54 .004 1073.17 (< .0001) Intervention duration x Exercise intensity 177 5 7.90 .162 1107.45 (< .0001) Exercise intensity x Depression severity at baseline 178 8 15.88 .044 1095.65 (< .0001) Supplementary Material Supplementary files 1-16 are not available with this version. Additional Declarations There is NO Competing Interest. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6795147","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":474198970,"identity":"ec5b939b-d8ed-40ed-8b00-57985da2d105","order_by":0,"name":"Melanie Mack","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7UlEQVRIiWNgGAWjYFAC5gYGBgMIi+EDAwMPhIUXMCK0MM4gXgvUPmYeGAufBt32xsbPBQU2QMbhx8a2bXdk5N0bGD8X4NFiduZgs/QMgzQgI804ObftGY/hmQPM0jPwabmR2CDNY3CYwexADvPh3LbDPIYzEtjgLsSq5f7D5t88Bv8ZzM6/YT5sCdIy/wEBLTcY24C2HAAycpiTGYFa5CUYCGg5k9hmzWOQzGN245mxYc+5wzwGPInN0ni1HD98+DbPHzs5s/PJjyV+lB22l28/fPAzPi0wgFBjcAARU0QCeVI1jIJRMApGwbAHAFBHSG1k+OByAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0002-5512-0339","institution":"University of Geneva","correspondingAuthor":true,"prefix":"","firstName":"Melanie","middleName":"","lastName":"Mack","suffix":""},{"id":474198971,"identity":"c0129421-1bf8-4b39-bd59-a062e04f64ea","order_by":1,"name":"Andreea Badache","email":"","orcid":"","institution":"Örebro University","correspondingAuthor":false,"prefix":"","firstName":"Andreea","middleName":"","lastName":"Badache","suffix":""},{"id":474198972,"identity":"c870f9fd-706a-42ae-a12b-0d09c7e01ea8","order_by":2,"name":"Arzu Erden","email":"","orcid":"","institution":"Karadeniz Technical University","correspondingAuthor":false,"prefix":"","firstName":"Arzu","middleName":"","lastName":"Erden","suffix":""},{"id":474198973,"identity":"466e0c13-b1bf-4dce-9adf-b1717a4d6f65","order_by":3,"name":"Christoforos Giannaki","email":"","orcid":"","institution":"University of Nicosia","correspondingAuthor":false,"prefix":"","firstName":"Christoforos","middleName":"","lastName":"Giannaki","suffix":""},{"id":474198974,"identity":"9bf94728-0637-474b-812a-da0a2f3f01c0","order_by":4,"name":"Sandra Haider","email":"","orcid":"","institution":"Medical University of Vienna,","correspondingAuthor":false,"prefix":"","firstName":"Sandra","middleName":"","lastName":"Haider","suffix":""},{"id":474198975,"identity":"5edc2e48-209f-4103-aa14-7fe0acb26d9b","order_by":5,"name":"Antonia Kaltsatou","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Antonia","middleName":"","lastName":"Kaltsatou","suffix":""},{"id":474198976,"identity":"73d4ac3f-2f99-41e9-a232-7754724a9184","order_by":6,"name":"Burcu Kömürcü Akik","email":"","orcid":"","institution":"Ankara University","correspondingAuthor":false,"prefix":"","firstName":"Burcu","middleName":"Kömürcü","lastName":"Akik","suffix":""},{"id":474198977,"identity":"36c30b6b-05f3-4a1f-ba17-4c15c4af7917","order_by":7,"name":"Yael Netz","email":"","orcid":"","institution":"The Levinsky-Wingate Academic College","correspondingAuthor":false,"prefix":"","firstName":"Yael","middleName":"","lastName":"Netz","suffix":""},{"id":474198978,"identity":"cc317932-7c7c-4378-ad77-0a3427d2dc43","order_by":8,"name":"Iulia Pavlova","email":"","orcid":"https://orcid.org/0000-0002-8111-4469","institution":"Lviv State University of Physical Culture","correspondingAuthor":false,"prefix":"","firstName":"Iulia","middleName":"","lastName":"Pavlova","suffix":""},{"id":474198979,"identity":"0d69884d-f185-4469-ac18-b230d57aa672","order_by":9,"name":"Pinelopi Stavrinou","email":"","orcid":"","institution":"University of Nicosia","correspondingAuthor":false,"prefix":"","firstName":"Pinelopi","middleName":"","lastName":"Stavrinou","suffix":""},{"id":474198980,"identity":"bdd980f3-199f-4a23-89f4-4c2437c69c5f","order_by":10,"name":"Claudia Voelcker-Rehage","email":"","orcid":"https://orcid.org/0000-0001-5398-4099","institution":"University of Münster","correspondingAuthor":false,"prefix":"","firstName":"Claudia","middleName":"","lastName":"Voelcker-Rehage","suffix":""},{"id":474198981,"identity":"afb7c6d4-cab1-4388-9263-b4de78dba5ae","order_by":11,"name":"Michel Audiffren","email":"","orcid":"","institution":"University of Poitiers","correspondingAuthor":false,"prefix":"","firstName":"Michel","middleName":"","lastName":"Audiffren","suffix":""}],"badges":[],"createdAt":"2025-06-01 10:25:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6795147/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6795147/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":87382763,"identity":"f004c723-e99c-4293-b918-ab4a981bde36","added_by":"auto","created_at":"2025-07-23 08:39:17","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":143867,"visible":true,"origin":"","legend":"\u003cp\u003eFlow chart of the study selection process. RCT = randomized controlled trials.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6795147/v1/89055746a09608d726c6a62d.png"},{"id":87386150,"identity":"dbd0c204-70c9-46d8-9a0c-c0754f7fcda6","added_by":"auto","created_at":"2025-07-23 08:55:17","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":35795,"visible":true,"origin":"","legend":"\u003cp\u003eForest plot of the 182 effect sizes of the meta-analysis.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6795147/v1/10689611ef7c3404033925b2.png"},{"id":87382766,"identity":"6fed23c4-2699-4015-9610-90ded384d970","added_by":"auto","created_at":"2025-07-23 08:39:17","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":68954,"visible":true,"origin":"","legend":"\u003cp\u003eFunnel plot of the effect sizes. Filled points represent the original studies, while unfilled points indicate studies imputed using the trim-and-fill method.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6795147/v1/a6a9e3bc0befcdfb7ce1680a.png"},{"id":87386917,"identity":"641691c8-451e-44da-af39-f61545aa53d7","added_by":"auto","created_at":"2025-07-23 09:03:18","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1274142,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6795147/v1/e052b0d8-b633-4541-a6c3-e8139f4fb08d.pdf"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"A meta-analysis of chronic exercise effects and moderating variables on depression severity and core symptoms in older adults","fulltext":[{"header":"Introduction","content":"\u003cp\u003eDepression is one of the most common mental health conditions among older adults\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e.Older adults are particularly vulnerable to depression due to adverse life events, such as losing a spouse, chronic illnesses, and transitions to nursing homes\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e, which are often associated with increased physical inactivity and reduced functional capacity\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. Chronic exercise has recently gained attention as a non-pharmacological approach to ameliorate late-life depression\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. Data from systematic reviews on older adults with and without a clinical diagnosis of depressive disorder reveal a moderate effect of exercise on reducing depression severity compared to control groups\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. However, these effects show a considerable heterogeneity, likely due to differences in exercise protocols and participant characteristics\u003csup\u003e\u003cspan additionalcitationids=\"CR9 CR10 CR11\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eExercise interventions benefit older adults with depression through a variety of psychological and physiological mechanisms. Among the psychological benefits is improved self-esteem\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e, while physiological effects include anti-inflammatory responses and enhanced neuroplasticity\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. The efficacy of exercise depends on training characteristics such as the FITT principles (Frequency, Intensity, Time, and Type)\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e and is further influenced by individual factors, including depression severity, age, sex, physical fitness, cognitive function, and comorbidities\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eTo produce reliable and clinically relevant evidence on the effects of exercise in late-life depression, it is crucial to consider the question of \"what works for whom\", a key concept in precision or personalized medicine\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. However, current research lacks concrete, evidence-based conclusions about the most effective treatments for specific individuals\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. In this review, we aim to investigate how intervention and population characteristics moderate the effects of chronic exercise on depression severity and core depressive symptoms in older adults. Risks of bias due to methodological quality (RoB2)\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e,\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e, publication bias (e.g., small study effects), and evidence quality (GRADE)\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e were evaluated in order to ensure that the findings are robust and can inform clinical guidelines and policy recommendations.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eStudy selection and characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 20,700 titles and abstracts were screened, followed by a review of 523 full-text articles for potential inclusion. Of these, 143 RCTs, encompassing 182 effect sizes, were included for data extraction in the meta-analysis (Figure 1). Among the 143 studies reporting on depression severity, 24 also included data on anxiety, 6 on apathy, 13 on BMI, 18 on executive functions, 8 on fatigue, 6 on mood, 14 on sleep quality, and 11 on processing speed. The list of references corresponding to the 143 included studies is available in supplementary material 10. Key characteristics of the included studies are summarized in Table 1 and detailed at the study level in supplementary material 11. The list of excluded studies based on full-text screening is available in supplementary materials 12 and the main reason of exclusion listed in supplementary material 13.\u003c/p\u003e\n\u003cp\u003e---------------------------------------\u003c/p\u003e\n\u003cp\u003eInsert Figure 1 about here\u003c/p\u003e\n\u003cp\u003e---------------------------------------\u003c/p\u003e\n\u003cp\u003e---------------------------------------\u003c/p\u003e\n\u003cp\u003eInsert Table 1 about here\u003c/p\u003e\n\u003cp\u003e---------------------------------------\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDepression severity\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eChronic exercise significantly improved overall depression severity compared to a control group with a moderate effect size (\u003cem\u003eg\u0026nbsp;\u003c/em\u003e= - 0.67, [95% \u003cem\u003eCI\u003c/em\u003e, -0.81 to 0.53], \u003cem\u003eP\u0026nbsp;\u003c/em\u003e\u0026lt; .0001; Figure 2). Substantial heterogeneity was observed (I\u0026sup2; = 96.92 %, Q = 1208.06, \u003cem\u003eP\u0026nbsp;\u003c/em\u003e\u0026lt; .0001), warranting further exploration.\u003c/p\u003e\n\u003cp\u003e---------------------------------------\u003c/p\u003e\n\u003cp\u003eInsert Figure 2 about here\u003c/p\u003e\n\u003cp\u003e---------------------------------------\u003c/p\u003e\n\u003cp\u003eEgger\u0026rsquo;s test suggested potential publication bias in the included studies, with smaller studies (larger standard errors) reporting larger effect sizes (Intercept = 0.60, \u003cem\u003eP\u0026nbsp;\u003c/em\u003e\u0026lt; .0001; Slope = -4.38, \u003cem\u003eP\u0026nbsp;\u003c/em\u003e\u0026lt; 0.0001). This was further supported by an asymmetrical funnel plot (Figure 3). Sensitivity analyses using the trim-and-fill method were conducted to adjust for this bias, resulting in an estimation of 54 missing studies on the right-hand side (see Figure supplementary material 15). The SCMC was reduced but still significant after imputation of the missing studies (SMD = -024 [95% \u003cem\u003eCI\u003c/em\u003e, -0.40 to -0.07], \u003cem\u003eP\u0026nbsp;\u003c/em\u003e= .005 compared to SMD = 0.24 [95% \u003cem\u003eCI\u003c/em\u003e, -0.40 to -0.07], \u003cem\u003eP\u0026nbsp;\u003c/em\u003e= .006 without the imputed studies). Methodological quality assessed with RoB2 did not significantly influence chronic exercise effects on depression severity (Table 3). The table of risk of bias for each RCT is presented in supplementary material 14. The GRADE rating indicated a low certainty of evidence.\u003c/p\u003e\n\u003cp\u003e---------------------------------------\u003c/p\u003e\n\u003cp\u003eInsert Figure 3 about here\u003c/p\u003e\n\u003cp\u003e---------------------------------------\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCore symptoms of depression\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRegarding the secondary outcomes, which reflect core symptoms of depression, chronic exercise significantly decreased anxiety (\u003cem\u003eg\u0026nbsp;\u003c/em\u003e= -0.56 [95% \u003cem\u003eCI\u003c/em\u003e, -0.82 to -0.30], \u003cem\u003eP\u0026nbsp;\u003c/em\u003e\u0026lt; .0001) and BMI (\u003cem\u003eg\u0026nbsp;\u003c/em\u003e= -0.26 [95% \u003cem\u003eCI\u003c/em\u003e, -0.45 to -0.08], \u003cem\u003eP\u0026nbsp;\u003c/em\u003e= .005), improved executive functions (\u003cem\u003eg\u0026nbsp;\u003c/em\u003e= -0.33 [95% \u003cem\u003eCI\u003c/em\u003e, -0.55 to -0.10], \u003cem\u003eP\u0026nbsp;\u003c/em\u003e= .004), sleep quality (\u003cem\u003eg\u0026nbsp;\u003c/em\u003e= -0.47 [95% \u003cem\u003eCI\u003c/em\u003e, -0.74 to -0.20], \u003cem\u003eP\u0026nbsp;\u003c/em\u003e= .0006), and processing speed (\u003cem\u003eg\u0026nbsp;\u003c/em\u003e= -0.35 [95% \u003cem\u003eCI\u003c/em\u003e, -0.64 to -0.07], \u003cem\u003eP\u0026nbsp;\u003c/em\u003e= .015). No significant effects were observed for apathy, fatigue, and mood (Table 2, additional forest plots can be found in supplementary material 15, Figures S1 to S8).\u003c/p\u003e\n\u003cp\u003e---------------------------------------\u003c/p\u003e\n\u003cp\u003eInsert Table 2 about here\u003c/p\u003e\n\u003cp\u003e---------------------------------------\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eModeration of intervention characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAn analysis of the moderation of exercise intervention characteristics showed that the exercise type influenced chronic exercise effects on depression severity (QM(6) = 13.52, \u003cem\u003eP\u0026nbsp;\u003c/em\u003e= .035). Exergames were associated with the greatest effects on depression severity (\u003cem\u003eg\u0026nbsp;\u003c/em\u003e= -1.24), followed by resistance exercises (\u003cem\u003eg\u0026nbsp;\u003c/em\u003e= -0.88), mind-body exercises (\u003cem\u003eg\u0026nbsp;\u003c/em\u003e= 0.83), dance (\u003cem\u003eg\u0026nbsp;\u003c/em\u003e= -0.65), multi-component exercises (\u003cem\u003eg\u0026nbsp;\u003c/em\u003e= -0.53), aerobic exercises (\u003cem\u003eg\u0026nbsp;\u003c/em\u003e= -0.52), and coordinative exercises (\u003cem\u003eg\u0026nbsp;\u003c/em\u003e= -0.51). Exergames showed significantly higher effects than aerobic exercises (\u003cem\u003eEst\u0026nbsp;\u003c/em\u003e= 0.71 [95% \u003cem\u003eCI\u003c/em\u003e, 0.15 to 1.27], \u003cem\u003eP\u0026nbsp;\u003c/em\u003e= .012) and multi-component exercises (\u003cem\u003eEst\u0026nbsp;\u003c/em\u003e= 0.71 [95% \u003cem\u003eCI\u003c/em\u003e, 0.14 to 1.28], \u003cem\u003eP\u0026nbsp;\u003c/em\u003e= .015). Additionally, mind-body exercises showed significantly higher effects than multi-component exercises (\u003cem\u003eEst\u0026nbsp;\u003c/em\u003e= 0.30 [95% \u003cem\u003eCI\u003c/em\u003e, 0.02 to 0.58], \u003cem\u003eP\u0026nbsp;\u003c/em\u003e= .037). No other post-hoc comparisons revealed significant differences. Furthermore, interventions with a higher training volume were associated with greater effects of chronic exercise on depression severity \u0026ndash; but not those with a longer duration alone (intervention duration: QM(1) = 0.04, \u003cem\u003eEst\u0026nbsp;\u003c/em\u003e= -0.001 [95% \u003cem\u003eCI\u003c/em\u003e, -0.010 to 0.014], \u003cem\u003eP\u0026nbsp;\u003c/em\u003e= .839; training volume: QM(1) = 3.87, \u003cem\u003eEst\u0026nbsp;\u003c/em\u003e= -0.0001 [95% \u003cem\u003eCI\u003c/em\u003e, -0.0002 to 0.0000], \u003cem\u003eP\u0026nbsp;\u003c/em\u003e= .049). Similarly, interventions with higher cognitive demand were linked to a greater effect of chronic exercise on depression severity compared to interventions with a lower cognitive demand (QM(1) = 8.35, \u003cem\u003eEst\u0026nbsp;\u003c/em\u003e= 0.352 [95% \u003cem\u003eCI\u003c/em\u003e, 0.1 to 0.58], \u003cem\u003eP\u0026nbsp;\u003c/em\u003e= .004). By contrast, intensity, session duration, session frequency, social interaction, and autonomy did not significantly influence chronic exercise effects on depression severity. Additional statistics on the moderation results for exercise characteristics are provided in Table 3, with related figures available in supplementary material 15 (Figures S9 to S30).\u003c/p\u003e\n\u003cp\u003e---------------------------------------\u003c/p\u003e\n\u003cp\u003eInsert Table 3 about here\u003c/p\u003e\n\u003cp\u003e---------------------------------------\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eModeration of population characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAnalysis of the moderation of population characteristics revealed that age significantly moderated chronic exercise effects on depression severity, with older populations experiencing lower reductions in depression severity (QM(1) = 12.75, \u003cem\u003eEst\u0026nbsp;\u003c/em\u003e= 0.03 [95% \u003cem\u003eCI\u003c/em\u003e, 0.02 to 0.05], \u003cem\u003eP\u0026nbsp;\u003c/em\u003e= .0004). Similarly, baseline depression severity was significantly associated with chronic exercise effects on depression severity (QM(2) = 10.95, \u003cem\u003eP\u0026nbsp;\u003c/em\u003e= .004), with participants with severe depression showing the largest reduction (\u003cem\u003eg\u0026nbsp;\u003c/em\u003e= -1.06), followed by participants with mild to moderate depression (\u003cem\u003eg\u0026nbsp;\u003c/em\u003e= -0.81) and participants with very mild depression (\u003cem\u003eg\u0026nbsp;\u003c/em\u003e= -0.42). Post-hoc analysis indicated significant differences between very mild and severe depression groups (\u003cem\u003eEst\u0026nbsp;\u003c/em\u003e= -0.64 [95% \u003cem\u003eCI\u003c/em\u003e, -1.09 to -0.19], \u003cem\u003eP\u0026nbsp;\u003c/em\u003e= .006) and between very mild and mild to moderate groups (\u003cem\u003eEst\u0026nbsp;\u003c/em\u003e= -0.39 [95% \u003cem\u003eCI\u003c/em\u003e, -0.65 to -0.12], \u003cem\u003eP\u0026nbsp;\u003c/em\u003e= .005). By contrast, other population characteristics, including sex, education, global cognition, handgrip strength, 6-minute walk test performance, and population, did not significantly influence chronic exercise effects on depression severity. Additional statistics on the moderation results for population characteristics are provided in Table 3, with related figures available in supplementary material 15.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eModeration of protocol characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAnalysis of protocol characteristics showed that neither the control group type, type of analysis, nor study design significantly influenced the effects of chronic exercise on depression severity. Additional statistics on the moderation results for exercise characteristics are provided in Table 3, with related figures available in supplementary material 15.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eModeration between interactions of intervention and population characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWhen testing interactions between different moderators, the interaction between cognitive demand and depression severity reached significance: QM(5) = 19.84, \u003cem\u003eP\u0026nbsp;\u003c/em\u003e= .001. Post-hoc tests showed that high cognitive demanding exercises were more beneficial than low cognitive demanding exercises for mild to moderate depression only (low: \u003cem\u003eg\u0026nbsp;\u003c/em\u003e= -0.63, high: \u003cem\u003eg\u0026nbsp;\u003c/em\u003e= -1.08; \u003cem\u003eEst\u0026nbsp;\u003c/em\u003e= 0.46 [95% \u003cem\u003eCI\u003c/em\u003e, 0.10 to 0.82], \u003cem\u003eP\u0026nbsp;\u003c/em\u003e= .012; see supplementary material 16, Figure S31).\u003c/p\u003e\n\u003cp\u003eSimilarly, the interaction between the cognitive demand of exercise and global cognition at baseline was significant: QM(3) = 9.83, \u003cem\u003eP\u0026nbsp;\u003c/em\u003e= .020. While high cognitive demanding exercises were more beneficial for participants with low global cognition at baseline than for those with high global cognition, low cognitive demanding exercises were more beneficial for participants with high global cognition than for those with low global cognition (\u003cem\u003eEst\u0026nbsp;\u003c/em\u003e= -0.08 [95% \u003cem\u003eCI\u003c/em\u003e, -0.14 to -0.02], \u003cem\u003eP\u0026nbsp;\u003c/em\u003e= .016; see supplementary material 16, Figure S32).\u003c/p\u003e\n\u003cp\u003eIn addition, the interaction between exercise intensity and depression severity was significant: QM(8) = 15.88, \u003cem\u003eP\u0026nbsp;\u003c/em\u003e= .044. The effect of exercise intensity was significant only for participants with mild to moderate depression severity (supplementary material 16, Figure S33): in this population, vigorous intensity was significantly more beneficial than moderate intensity (\u003cem\u003eEst\u0026nbsp;\u003c/em\u003e= 0.48 [95% \u003cem\u003eCI\u003c/em\u003e, 0.02 to 0.95], \u003cem\u003eP\u0026nbsp;\u003c/em\u003e= .042) and marginally more beneficial than light intensity (\u003cem\u003eEst\u0026nbsp;\u003c/em\u003e= 0.43[95% \u003cem\u003eCI\u003c/em\u003e, -0.04 to 0.91], \u003cem\u003eP\u0026nbsp;\u003c/em\u003e= .075).\u003c/p\u003e\n\u003cp\u003eFinally, the interaction between age and cognitive demand of the exercise, the interaction between age and exercise intensity, the interaction between exercise type and exercise intensity, and the interaction between intervention duration and exercise intensity did not reach significance. Further details on the moderation effects of exercise characteristics are provided in Table 3, with related figures in supplementary material 15, Figures S35 to S38.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eTo the best of our knowledge, this meta-analysis represents the most comprehensive synthesis of the effects of chronic exercise on depression severity and indicators of core symptoms of depression in older adults, both with and without a diagnosed depressive disorder.\u003c/p\u003e \u003cp\u003eThe analysis revealed that chronic exercise significantly improved overall depression severity, yielding a moderate effect size. However, the certainty of evidence was rated as low. Moderate improvements were also observed for indicators of core symptoms of depression such as anxiety, whereas small effect sizes were identified for BMI, executive functions, sleep, and processing speed. The effects of chronic exercise were particularly large for interventions that included exergames, had a greater training volume, and involved high cognitive demand. The benefits of chronic exercise further decreased with advancing age and increased with increasing baseline depression severity. Furthermore, participants with mild to moderate baseline depression experienced greater benefits from exercises with higher cognitive demands, and vigorous intensity, which was not observed in participants with very light or severe depression. Finally, participants with lower global cognition benefited more from exercises with high cognitive demands compared to those with low cognitive demands.\u003c/p\u003e \u003cp\u003eThe present findings on the overall effects of chronic exercise on depression severity align with those of an umbrella review on twelve meta-analyses, which reported a statistically significant moderate effect and a high heterogeneity\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. We extend these findings by systematically examining several potential moderators that may explain this heterogeneity in effect sizes. In addition, the findings on the secondary outcomes including anxiety, executive functions, and processing speed align with prior research highlighting the benefits of exercise for anxiety symptoms\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e and cognitive functioning\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. Given the frequent co-occurrence of depression, anxiety, and cognitive decline, as well as their high prevalence and its contribution to increased morbidity and mortality\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e, exercise presents a promising intervention for comprehensively addressing those symptoms.\u003c/p\u003e \u003cp\u003eExercise did not significantly improve the depressive symptoms of apathy, fatigue, or mood\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e,\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. The lack of effects for apathy, fatigue, and mood may partly reflect limited statistical power, as these outcomes were assessed in fewer studies and showed high heterogeneity. Apathy, often seen in neuropsychiatric conditions, was primarily examined in participants with neurodegenerative disorders, making it difficult to determine whether it stemmed from the underlying condition, depression, or both\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. Similarly, fatigue, known to respond poorly to antidepressant treatment, remains understudied as a primary outcome in exercise-based depression interventions\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn terms of the effects of exercise type, the results of this review align with previous meta-analyses that compared aerobic, resistance, and mind-body exercises, finding them similarly effective in reducing depression severity in older adults\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e,\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. By including additional exercise types in our analysis, we found that exergames yielded the highest effect sizes, highlighting the value of incorporating cognitively stimulating elements into exercise regimens. This conclusion is further supported by our findings that exercise interventions with higher cognitive demand were more effective than those with lower cognitive demand and that the benefits of high-cognitive-demand exercises appear to increase as global cognition levels decline.\u003c/p\u003e \u003cp\u003eIn addition to the type of exercise, training volume appears to be another exercise-related characteristic that moderates the effects of the intervention. Specifically, higher intervention volumes were associated with larger effect sizes, indicating a dose\u0026ndash;response relationship. Training volume, as operationalized in this meta-analysis, is a composite metric encompassing intervention duration, session duration, and frequency. This aggregation reflects the cumulative exposure of participants to the intervention over time. Interestingly, when these components were analyzed individually, none of them significantly moderated the intervention effects. This finding suggests that it is not any single aspect of the intervention structure that drives efficacy, but rather the synergistic effect of total intervention volume. These results underscore the importance of considering total training load as a more holistic and informative parameter when designing or evaluating exercise interventions, particularly in populations where time commitment and adherence may vary considerably. However, the moderating effect of training volume was relatively small and accompanied by substantial heterogeneity, consistent with the possibility of more complex dose-response relationships, such as U-shaped curves that may vary across different exercise types and intensities (for a more detailed analysis and discussion of dose-response relationships, see previous reviews\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e,\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e).\u003c/p\u003e \u003cp\u003eExercise intensity interacted with depression severity at baseline, showing that vigorous intensity was more beneficial than light or moderate intensity for individuals with moderate depression but not for those with mild or severe depression. This may be due to moderate depression benefiting from stronger physiological and psychological responses, such as endorphin release and improved self-efficacy\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. Those with low depression severity at baseline may have limited room for improvement, while severe depression may hinder engagement with high-intensity activity. Results for severe depression should be interpreted cautiously, as only two studies investigated vigorous exercise in this group. Similarly, the cognitive demand of exercise interacted with depression severity at baseline, with high-demand exercises being more beneficial for mild to moderate depression but not for low or severe depression. This may be because mild to moderate depression benefits from cognitive engagement, while low severity offers less room for improvement and severe depression may struggle with the added cognitive challenge\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e, reducing adherence and effectiveness.\u003c/p\u003e \u003cp\u003eFor the primary outcome, i.e., depression severity, the certainty of evidence was rated as low, mainly due to a high risk of bias (58% of the studies analyzed by the Rob2 tool were identified as having a high risk in at least two domains), publication bias due to small study effects, and the substantial heterogeneity among the results.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis meta-analysis highlights the significant benefits of chronic exercise not only on depression severity but also on several core symptoms of depression in older adults. The findings indicate that interventions with greater training volume and higher cognitive demands such as for instance exergames are particularly effective. Individuals with mild to moderate depression seem especially sensitive to the positive effects of high-intensity and high-cognitive-demand exercises, which may be physically and cognitively overwhelming for those with severe depression. However, the findings of the meta-analyses must be interpreted with caution due to the low certainty of evidence. To avoid bias in measurement of the outcome, we recommend adopting more blinded assessment methods, such as assessments of depression severity conducted by a blinded experimenter through an interview. In the same way, to avoid bias due to deviation from intended interventions, we recommend to include an active control group engaged in exercise and to control for confounding factors, such as self-efficacy to follow the intervention programs and physical activity practiced beside the intervention programs. Additionally, further research is crucial to understand the effects of exergames and high-intensity interventions on severe depression.\u003c/p\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003cdiv id=\"Sec13\" class=\"Section3\"\u003e \u003c/div\u003e \u003c/div\u003e "},{"header":"Methods","content":"\u003ch2\u003eSearch strategy and selection criteria\u003c/h2\u003e\u003cp\u003eThis systematic and meta-analytic review has been registered in PROSPERO (registration number: CRD42022361418) and the protocol has been described in detail elsewhere\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. It followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines (supplementary material 1), with any amendments to the protocol documented in supplementary material 2. Web of Science, MEDLINE, CINAHL, APA PsycInfo, SPORTDiscus, and the Cochrane Central Register of Controlled Trials were searched from inception to July 2023, using keywords for 'depression', 'chronic exercise', 'randomized controlled trials' (RCTs), and 'older adults' (supplementary material 3). References sections in selected articles, and published meta-analyses were also reviewed for additional studies.\u003c/p\u003e\u003cp\u003eRCTs comparing exercise interventions to active or passive control groups in older adults (mean age minus standard deviation ≥ 50 years) with at least mild depression severity, assessed by validated scales, were included. Studies were limited to exercise-only interventions (with at least one intervention group focused solely on exercise), excluding those that included additional components such as nutrition, cognitive behavioral therapy, or pharmacotherapy. Study selection followed a three-step procedure using Rayyan: (1) duplicate removal, (2) title and abstract screening, and (3) full-text screening. Pairs of investigators (MM, AB, AE, CDG, SH, AK, BA, YN, IP, PS, CVR, MA) independently evaluated studies based on predefined guidelines (supplementary materials 4 and 5). Discrepancies were resolved through consensus or arbitration by a panel of investigators (MM, MA). Search strategy and selection criteria were outlined in detail in the study protocol\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. The flow chart of the selection process is described in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003ch2\u003eOutcomes\u003c/h2\u003e\u003cp\u003ePrimary outcomes were depression severity at baseline and at the intervention endpoint, assessed using validated scales through self-reports and external ratings by clinicians or investigators. A list of the included rating scales is provided in supplementary material 6. Secondary outcomes encompassed indicators of core symptoms of depression, as defined in the DSM-5 (i.e., sleep quality, fatigue, anxiety, mood, apathy, BMI, processing speed, and executive functions) at baseline and at the intervention endpoint. We listed the scales used for each symptom in the supplementary material 7. When studies reported multiple outcomes (e.g., using different scales or intervention arms), all measures were included in the analysis. Additional details on the outcomes can be found in the study protocol\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003ch2\u003eData extraction and quality assessment\u003c/h2\u003e\u003cp\u003eData extraction was performed using REDCap. For each study, the following variables were coded: primary and secondary outcome measures (means and SDs), intervention characteristics (session frequency, exercise intensity, session duration, intervention duration, exercise type, training volume, cognitive demand, social interaction, autonomy), population characteristics (age, sex, population, education, global cognition, handgrip strength, 6-min walk test, depression severity), and protocol characteristics (control group, type of analysis, study design). These variables are operationalized as specified in the study protocol\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. In cases of missing outcome data, study authors were contacted to obtain the necessary information. If no response was received, outcome data were extracted from published figures where feasible. The risk of bias was assessed using the revised Cochrane Risk-of-Bias Tool for Randomized Trials (RoB2, version 2)\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e,\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. Pairs of investigators (MM, AB, AE, CDG, SH, AK, BA, YN, IP, PS, CVR, MA) independently extracted data and assessed bias following predefined guidelines (supplementary materials 8 and 9). Discrepancies were resolved through consensus or arbitration by a review panel (MM, MA). Details on data extraction and quality assessment are described in the study protocol\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. The quality of evidence was assessed for the primary outcome depression severity using the GRADE approach\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e with the software GRADEpro (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.gradepro.org/\u003c/span\u003e\u003cspan address=\"https://www.gradepro.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Two independent investigators (MM, MA) individually completed the GRADE assessments. Discrepancies were resolved through discussion. Subsequently, two additional investigators reviewed and approved the final GRADE ratings (CVR, CDG).\u003c/p\u003e\u003ch2\u003eData analysis\u003c/h2\u003e\u003cp\u003eFor studies published multiple times, all articles related to the same RCT were considered. Statistical analyses were performed using Comprehensive Meta-Analysis software (CMA, version 4), and R (version 4.2.2)\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. Standardized Comparative Mean Change scores (SCMC) were calculated for each primary and secondary outcome using Hedges’ \u003cem\u003eg\u003c/em\u003e with 95% CIs, representing the difference in changes from baseline to intervention endpoint between the exercise and control groups. A negative \u003cem\u003eg\u003c/em\u003e indicated greater efficacy of exercise interventions relative to controls. Effect sizes were inverted for measures where higher scores reflected higher performance (i.e., sleep quality, executive functions).\u003c/p\u003e\u003cp\u003eWe first analyzed the effect of exercise compared to a control group on the primary outcome of depression severity. To account for multiple measurements (i.e., multiple effect sizes for depression severity) – arising from the use of different depression scales, exercise interventions, and control groups within one study – we employed multilevel models with outcomes nested within studies. Between-study heterogeneity was assessed using Q statistics and I². Publication bias due to small-study effects was evaluated with a funnel plot, Egger’s regression test, and the trim-and-fill method. Sensitivity analysis for publication bias, based on study quality, was conducted through moderation analysis using the RoB2 results. We then examined the effect of exercise on secondary outcomes using random-effects models, with Q statistics and I² assessing heterogeneity.\u003c/p\u003e\u003cp\u003eA moderation analysis was conducted to determine whether intervention characteristics, population characteristics, protocol characteristics, or theoretically meaningful interactions between moderators, moderated the effectiveness of exercise interventions on the primary outcome of depression severity. These interactions were included based on the assumption that certain characteristics may influence one another in determining intervention effectiveness (e.g., more intensive interventions might be particularly beneficial for individuals with higher baseline levels of depression). The Cochrane Q test was used to evaluate the significance of these moderators. For significant moderation effects, further post-hoc comparisons were conducted for categorical moderators and interactions reporting estimates and standard errors by comparing each factor level against the other. The full dataset is freely available through the Open Science Framework (OSF; DOI: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.17605/OSF.IO/ZNWE8\u003c/span\u003e\u003cspan address=\"10.17605/OSF.IO/ZNWE8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualisation: Melanie Mack, Christoforos D. Giannaki, Claudia Voelcker-Rehage, Michel Audiffren\u003c/p\u003e\n\u003cp\u003eData curation: Melanie Mack, Andreea Badache, Arzu Erden, Christoforos D. Giannaki, Sandra Haider, Antonia Kaltsatou, Burcu K\u0026ouml;m\u0026uuml;rc\u0026uuml; Akik, Ya\u0026euml;l Netz, Iuliia Pavlova, Pinelopi S.Stavrinou, Claudia Voelcker-Rehage, Michel Audiffren\u003c/p\u003e\n\u003cp\u003eFormal analysis: Melanie Mack, Michel Audiffren\u003c/p\u003e\n\u003cp\u003eFunding acquisition: Ya\u0026euml;l Netz\u003c/p\u003e\n\u003cp\u003eInvestigation: Melanie Mack, Andreea Badache, Arzu Erden, Christoforos D. Giannaki, Sandra Haider, Antonia Kaltsatou, Burcu K\u0026ouml;m\u0026uuml;rc\u0026uuml; Akik, Ya\u0026euml;l Netz, Iuliia Pavlova, Pinelopi S.Stavrinou, Claudia Voelcker-Rehage, Michel Audiffren\u003c/p\u003e\n\u003cp\u003eMethodology: Melanie Mack, Michel Audiffren\u003c/p\u003e\n\u003cp\u003eProject administration: \u0026nbsp;Melanie Mack, Christoforos D. Giannaki, Claudia Voelcker-Rehage, Michel Audiffren\u003c/p\u003e\n\u003cp\u003eResources: -\u003c/p\u003e\n\u003cp\u003eSoftware: Melanie Mack, Michel Audiffren\u003c/p\u003e\n\u003cp\u003eSupervision: Melanie Mack, Christoforos D. Giannaki, Claudia Voelcker-Rehage, Michel Audiffren\u003c/p\u003e\n\u003cp\u003eValidation: Melanie Mack, Christoforos D. Giannaki, Claudia Voelcker-Rehage, Michel Audiffren\u003c/p\u003e\n\u003cp\u003eVisualisation: Melanie Mack, Michel Audiffren\u003c/p\u003e\n\u003cp\u003eWriting \u0026ndash; original draft: Melanie Mack, Michel Audiffren\u003c/p\u003e\n\u003cp\u003eWriting \u0026ndash; review \u0026amp; editing: Melanie Mack, Andreea Badache, Arzu Erden, Christoforos D. Giannaki, Sandra Haider, Antonia Kaltsatou, Burcu K\u0026ouml;m\u0026uuml;rc\u0026uuml; Akik, Ya\u0026euml;l Netz, Iuliia Pavlova, Pinelopi S.Stavrinou, Claudia Voelcker-Rehage, Michel Audiffren\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest disclosure\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll the authors of this manuscript are members of the COST network PhysAgeNet (CA 20104). The authors have declared that no competing interest exists.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding / support\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis publication is based upon work from EU COST Action CA20104 - Network on evidence-based physical activity in old age (PhysAgeNet), Working Group 1 supported by COST (European Cooperation in Science and Technology): https://www.cost.eu/, https://physagenet.eu/.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRole of the funder / sponsor\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe funding sources had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.\u003c/p\u003e"},{"header":"References ","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eJalali A et al (2024) Global prevalence of depression, anxiety, and stress in the elderly population: a systematic review and meta-analysis. BMC Geriatr 24:809\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZenebe Y, Akele B, Selassie W, M., Necho M (2021) Prevalence and determinants of depression among old age: a systematic review and meta-analysis. Ann Gen Psychiatry 20:55\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChang-Quan H et al (2010) Health status and risk for depression among the elderly: a meta-analysis of published literature. Age Ageing 39:23\u0026ndash;30\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWorld Healthh Organisation \u003cem\u003eWHO Guidelines on Physical Activity and Sedentary Behaviour\u003c/em\u003e. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.who.int/publications/i/item/9789240015128\u003c/span\u003e\u003cspan address=\"https://www.who.int/publications/i/item/9789240015128\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBigarella LG et al (2022) Exercise for depression and depressive symptoms in older adults: an umbrella review of systematic reviews and Meta-analyses. Aging Mental Health 26:1503\u0026ndash;1513\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNiemeijer A et al (2020) Adverse events of exercise therapy in randomised controlled trials: a systematic review and meta-analysis. Br J Sports Med 54:1073\u0026ndash;1080\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCatalan-Matamoros D, Gomez-Conesa A, Stubbs B, Vancampfort D (2016) Exercise improves depressive symptoms in older adults: An umbrella review of systematic reviews and meta-analyses. Psychiatry Res 244:202\u0026ndash;209\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchuch FB, Dunn AL, Kanitz AC, Delevatti RS, Fleck MP (2016) Moderators of response in exercise treatment for depression: A systematic review. J Affect Disord 195:40\u0026ndash;49\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMiller KJ et al (2020) Comparative effectiveness of three exercise types to treat clinical depression in older adults: A systematic review and network meta-analysis of randomised controlled trials. Ageing Res Rev 58:100999\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBo A, Mao W, Lindsey MA (2017) Effects of mind\u0026ndash;body interventions on depressive symptoms among older Chinese adults: a systematic review and meta-analysis. Int J Geriat Psychiatry 32:509\u0026ndash;521\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKlil-Drori S, Klil-Drori AJ, Pira S, Rej S (2020) Exercise Intervention for Late-Life Depression: A Meta-Analysis. J Clin Psychiatry 81\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDauwan M et al (2021) Physical exercise improves quality of life, depressive symptoms, and cognition across chronic brain disorders: a transdiagnostic systematic review and meta-analysis of randomized controlled trials. J Neurol 268:1222\u0026ndash;1246\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePark S-H, Han KS, Kang C-B (2014) Effects of exercise programs on depressive symptoms, quality of life, and self-esteem in older people: A systematic review of randomized controlled trials. Appl Nurs Res 27:219\u0026ndash;226\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDe Sousa RAL et al (2021) Molecular mechanisms of physical exercise on depression in the elderly: a systematic review. Mol Biol Rep 48:3853\u0026ndash;3862\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMedicine AC (2013) of S. \u003cem\u003eACSM\u0026rsquo;s Guidelines for Exercise Testing and Prescription\u003c/em\u003e. (Lippincott williams \u0026amp; wilkins\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlexopoulos GS (2005) Depression in the elderly. Lancet 365:1961\u0026ndash;1970\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAhmed A, Van Den Muijsenbergh METC, Vrijhoef HJ (2022) M. Person-centred care in primary care: What works for whom, how and in what circumstances? Health Social Care Comm 30\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHiggins JP et al (2016) A revised tool for assessing risk of bias in randomized trials. Cochrane Database Syst Rev 10:29\u0026ndash;31\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSterne JAC et al (2019) RoB 2: a revised tool for assessing risk of bias in randomised trials. \u003cem\u003eBMJ\u003c/em\u003e l4898 \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1136/bmj.l4898\u003c/span\u003e\u003cspan address=\"10.1136/bmj.l4898\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGuyatt G et al (2011) GRADE guidelines: 1. Introduction\u0026mdash;GRADE evidence profiles and summary of findings tables. J Clin Epidemiol 64:383\u0026ndash;394\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStonerock GL, Hoffman BM, Smith PJ, Blumenthal JA (2015) Exercise as Treatment for Anxiety: Systematic Review and Analysis. Ann Behav Med 49:542\u0026ndash;556\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen F-T et al (2020) Effects of Exercise Training Interventions on Executive Function in Older Adults: A Systematic Review and Meta-Analysis. Sports Med 50:1451\u0026ndash;1467\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLenze EJ (2003) Comorbidity of depression and anxiety in the elderly. Curr Psychiatry Rep 5:62\u0026ndash;67\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eArent SM, Landers DM, Etnier JL (2000) The Effects of Exercise on Mood in Older Adults: A Meta-Analytic Review. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1123/japa.8.4.407\u003c/span\u003e\u003cspan address=\"10.1123/japa.8.4.407\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eReed J, Buck S (2009) The effect of regular aerobic exercise on positive-activated affect: A meta-analysis. Psychol Sport Exerc 10:581\u0026ndash;594\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSteffens DC, Fahed M, Manning KJ, Wang L (2022) The neurobiology of apathy in depression and neurocognitive impairment in older adults: a review of epidemiological, clinical, neuropsychological and biological research. Transl Psychiatry 12:1\u0026ndash;16\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDemyttenaere K, De Fruyt J, Stahl SM (2005) The many faces of fatigue in major depressive disorder. Int J Neuropsychopharmacol 8:93\u0026ndash;105\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMiller KJ et al (2021) Aerobic, resistance, and mind-body exercise are equivalent to mitigate symptoms of depression in older adults: A systematic review and network meta-analysis of randomised controlled trials. \u003cem\u003eF1000Res\u003c/em\u003e 9, 1325\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRhyner KT, Watts A (2016) Exercise and Depressive Symptoms in Older Adults: A Systematic Meta-Analytic Review. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1123/japa.2015-0146\u003c/span\u003e\u003cspan address=\"10.1123/japa.2015-0146\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTian S et al (2024) Comparative efficacy of various exercise types and doses for depression in older adults: a systematic review of paired, network and dose\u0026ndash;response meta-analyses. Age Ageing 53:afae211\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTang L et al (2024) Optimal dose and type of exercise to improve depressive symptoms in older adults: a systematic review and network meta-analysis. BMC Geriatr 24:505\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMann T, Lamberts RP, Lambert MI (2013) Methods of Prescribing Relative Exercise Intensity: Physiological and Practical Considerations. Sports Med 43:613\u0026ndash;625\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHorne SJ, Topp TE, Quigley L (2021) Depression and the willingness to expend cognitive and physical effort for rewards: A systematic review. Clin Psychol Rev 88:102065\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMack M et al (2024) Chronic exercise effects on overall depression severity and distinct depressive symptoms in older adults: A protocol of a systematic and meta-analytic review. PLoS ONE 19:e0297348\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTeam RDC (2010) R: A language and environment for statistical computing. (No Title)\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1:\u0026nbsp;\u003c/strong\u003eSummary of the key characteristics of the included studies\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.6998%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7343%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNO ES\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.5659%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eN\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;or \u003cem\u003eMean / SD\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.6998%;\"\u003e\n \u003cp\u003eNumber of articles (\u003cem\u003eN\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7343%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.5659%;\"\u003e\n \u003cp\u003e143\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.6998%;\"\u003e\n \u003cp\u003eNumber of ES\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7343%;\"\u003e\n \u003cp\u003e182\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.5659%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.6998%;\"\u003e\n \u003cp\u003eNumber of participants\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7343%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.5659%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.6998%;\"\u003e\n \u003cp\u003eExercise group (\u003cem\u003eN\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7343%;\"\u003e\n \u003cp\u003e182\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.5659%;\"\u003e\n \u003cp\u003e7664\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.6998%;\"\u003e\n \u003cp\u003eControl Group (\u003cem\u003eN\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7343%;\"\u003e\n \u003cp\u003e182\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.5659%;\"\u003e\n \u003cp\u003e7125\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.6998%;\"\u003e\n \u003cp\u003eAge in years (\u003cem\u003eMean / SD\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7343%;\"\u003e\n \u003cp\u003e181\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.5659%;\"\u003e\n \u003cp\u003e72.60 / 7.07\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.6998%;\"\u003e\n \u003cp\u003e% female (\u003cem\u003eMean / SD\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7343%;\"\u003e\n \u003cp\u003e168\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.5659%;\"\u003e\n \u003cp\u003e68.91 / 21.11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.6998%;\"\u003e\n \u003cp\u003ePopulation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7343%;\"\u003e\n \u003cp\u003e192\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.5659%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.6998%;\"\u003e\n \u003cp\u003eAsymptomatic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7343%;\"\u003e\n \u003cp\u003e65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.5659%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.6998%;\"\u003e\n \u003cp\u003eNeurodegenerative diseases\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7343%;\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.5659%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.6998%;\"\u003e\n \u003cp\u003eDepressive disorder\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7343%;\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.5659%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.6998%;\"\u003e\n \u003cp\u003eCognitive impairment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7343%;\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.5659%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.6998%;\"\u003e\n \u003cp\u003eOther diseases\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7343%;\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.5659%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.6998%;\"\u003e\n \u003cp\u003eCardiovascular diseases\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7343%;\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.5659%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.6998%;\"\u003e\n \u003cp\u003eOther disabilities\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7343%;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.5659%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.6998%;\"\u003e\n \u003cp\u003eEducation in years (\u003cem\u003eMean / SD\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7343%;\"\u003e\n \u003cp\u003e85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.5659%;\"\u003e\n \u003cp\u003e10.06 / 3.88\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.6998%;\"\u003e\n \u003cp\u003eHandgrip strength in kg (\u003cem\u003eMean / SD\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7343%;\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.5659%;\"\u003e\n \u003cp\u003e19.63 / 6.17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.6998%;\"\u003e\n \u003cp\u003eSix-min walk test in m (\u003cem\u003eMean / SD\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7343%;\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.5659%;\"\u003e\n \u003cp\u003e358.55 / 115.88\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.6998%;\"\u003e\n \u003cp\u003eGlobal cognition (\u003cem\u003eMean / SD\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7343%;\"\u003e\n \u003cp\u003e76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.5659%;\"\u003e\n \u003cp\u003e22.60 / 5.44\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.6998%;\"\u003e\n \u003cp\u003eDepression severity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7343%;\"\u003e\n \u003cp\u003e182\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.5659%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.6998%;\"\u003e\n \u003cp\u003eVery light\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7343%;\"\u003e\n \u003cp\u003e70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.5659%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.6998%;\"\u003e\n \u003cp\u003eMild to moderate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7343%;\"\u003e\n \u003cp\u003e99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.5659%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.6998%;\"\u003e\n \u003cp\u003esevere\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7343%;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.5659%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.6998%;\"\u003e\n \u003cp\u003eExercise type\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7343%;\"\u003e\n \u003cp\u003e182\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.5659%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.6998%;\"\u003e\n \u003cp\u003eMulti-component\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7343%;\"\u003e\n \u003cp\u003e64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.5659%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.6998%;\"\u003e\n \u003cp\u003eMind-body\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7343%;\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.5659%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.6998%;\"\u003e\n \u003cp\u003eAerobic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7343%;\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.5659%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.6998%;\"\u003e\n \u003cp\u003eResistance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7343%;\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.5659%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.6998%;\"\u003e\n \u003cp\u003eDance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7343%;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.5659%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.6998%;\"\u003e\n \u003cp\u003eExergames\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7343%;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.5659%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.6998%;\"\u003e\n \u003cp\u003eCoordinative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7343%;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.5659%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.6998%;\"\u003e\n \u003cp\u003eExercise intensity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7343%;\"\u003e\n \u003cp\u003e178\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.5659%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.6998%;\"\u003e\n \u003cp\u003eLight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7343%;\"\u003e\n \u003cp\u003e61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.5659%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.6998%;\"\u003e\n \u003cp\u003eModerate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7343%;\"\u003e\n \u003cp\u003e88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.5659%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.6998%;\"\u003e\n \u003cp\u003eVigorous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7343%;\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.5659%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.6998%;\"\u003e\n \u003cp\u003eSession duration in min (\u003cem\u003eMean / SD\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7343%;\"\u003e\n \u003cp\u003e172\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.5659%;\"\u003e\n \u003cp\u003e49.48 / 21.43\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.6998%;\"\u003e\n \u003cp\u003eSession frequency (NO session per week)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7343%;\"\u003e\n \u003cp\u003e177\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.5659%;\"\u003e\n \u003cp\u003e3.10 / 1.81\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.6998%;\"\u003e\n \u003cp\u003eIntervention duration (weeks)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7343%;\"\u003e\n \u003cp\u003e175\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.5659%;\"\u003e\n \u003cp\u003e14.43 / 10.69\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.6998%;\"\u003e\n \u003cp\u003eTraining volume (in min)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7343%;\"\u003e\n \u003cp\u003e172\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.5659%;\"\u003e\n \u003cp\u003e1956.63 / 1568.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.6998%;\"\u003e\n \u003cp\u003eCognitive demand\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7343%;\"\u003e\n \u003cp\u003e181\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.5659%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.6998%;\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7343%;\"\u003e\n \u003cp\u003e103\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.5659%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.6998%;\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7343%;\"\u003e\n \u003cp\u003e78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.5659%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.6998%;\"\u003e\n \u003cp\u003eSocial interaction\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7343%;\"\u003e\n \u003cp\u003e170\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.5659%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.6998%;\"\u003e\n \u003cp\u003eGroup-based\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7343%;\"\u003e\n \u003cp\u003e111\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.5659%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.6998%;\"\u003e\n \u003cp\u003eIndividual-based\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7343%;\"\u003e\n \u003cp\u003e46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.5659%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.6998%;\"\u003e\n \u003cp\u003eMixed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7343%;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.5659%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.6998%;\"\u003e\n \u003cp\u003eAutonomy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7343%;\"\u003e\n \u003cp\u003e176\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.5659%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.6998%;\"\u003e\n \u003cp\u003eSupervised\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7343%;\"\u003e\n \u003cp\u003e139\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.5659%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.6998%;\"\u003e\n \u003cp\u003eMixed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7343%;\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.5659%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.6998%;\"\u003e\n \u003cp\u003eHome-based\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7343%;\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.5659%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.6998%;\"\u003e\n \u003cp\u003eControl group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7343%;\"\u003e\n \u003cp\u003e182\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.5659%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.6998%;\"\u003e\n \u003cp\u003ePassive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7343%;\"\u003e\n \u003cp\u003e119\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.5659%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.6998%;\"\u003e\n \u003cp\u003eActive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7343%;\"\u003e\n \u003cp\u003e63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.5659%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.6998%;\"\u003e\n \u003cp\u003eType of analysis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7343%;\"\u003e\n \u003cp\u003e182\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.5659%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.6998%;\"\u003e\n \u003cp\u003eComplete case\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7343%;\"\u003e\n \u003cp\u003e125\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.5659%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.6998%;\"\u003e\n \u003cp\u003eIntention-to-treat\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7343%;\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.5659%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.6998%;\"\u003e\n \u003cp\u003ePer-protocol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7343%;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.5659%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.6998%;\"\u003e\n \u003cp\u003eStudy design\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7343%;\"\u003e\n \u003cp\u003e182\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.5659%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.6998%;\"\u003e\n \u003cp\u003eParallel-group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7343%;\"\u003e\n \u003cp\u003e165\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.5659%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 52.6998%;\"\u003e\n \u003cp\u003eCluster\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7343%;\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.5659%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2:\u0026nbsp;\u003c/strong\u003eSummary of effect sizes and heterogeneity across outcomes\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"643\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13.1988%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOutcome\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.74534%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ek\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.0435%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eHedges\u0026apos; g\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.7516%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e95% CI\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.2484%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ez\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.1118%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.0994%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eQ (P)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8012%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eI\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13.1988%;\"\u003e\n \u003cp\u003eDepression severity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5.74534%;\"\u003e\n \u003cp\u003e182\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.0435%;\"\u003e\n \u003cp\u003e-0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.7516%;\"\u003e\n \u003cp\u003e-0.81, -0.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.2484%;\"\u003e\n \u003cp\u003e-9.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.1118%;\"\u003e\n \u003cp\u003e\u0026lt; .0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.0994%;\"\u003e\n \u003cp\u003e1208.06 (\u0026lt; .0001)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.8012%;\"\u003e\n \u003cp\u003e96.92 %\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13.1988%;\"\u003e\n \u003cp\u003eAnxiety\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5.74534%;\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.0435%;\"\u003e\n \u003cp\u003e-0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.7516%;\"\u003e\n \u003cp\u003e-0.82, -0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.2484%;\"\u003e\n \u003cp\u003e-4.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.1118%;\"\u003e\n \u003cp\u003e\u0026lt; .0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.0994%;\"\u003e\n \u003cp\u003e108.54 (\u0026lt; .0001)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.8012%;\"\u003e\n \u003cp\u003e78.81 %\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13.1988%;\"\u003e\n \u003cp\u003eApathy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5.74534%;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.0435%;\"\u003e\n \u003cp\u003e-0.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.7516%;\"\u003e\n \u003cp\u003e-1.45, 0.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.2484%;\"\u003e\n \u003cp\u003e-1.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.1118%;\"\u003e\n \u003cp\u003e.210\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.0994%;\"\u003e\n \u003cp\u003e26.49 (\u0026lt; .0001)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.8012%;\"\u003e\n \u003cp\u003e81.13 %\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13.1988%;\"\u003e\n \u003cp\u003eBMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5.74534%;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.0435%;\"\u003e\n \u003cp\u003e-0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.7516%;\"\u003e\n \u003cp\u003e-0.45, -0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.2484%;\"\u003e\n \u003cp\u003e-2.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.1118%;\"\u003e\n \u003cp\u003e.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.0994%;\"\u003e\n \u003cp\u003e11.44 (.492)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.8012%;\"\u003e\n \u003cp\u003e4.89 %\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13.1988%;\"\u003e\n \u003cp\u003eExecutive functions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5.74534%;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.0435%;\"\u003e\n \u003cp\u003e-0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.7516%;\"\u003e\n \u003cp\u003e-0.55, -0.10,\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.2484%;\"\u003e\n \u003cp\u003e2.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.1118%;\"\u003e\n \u003cp\u003e.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.0994%;\"\u003e\n \u003cp\u003e73.32 (\u0026lt; .0001)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.8012%;\"\u003e\n \u003cp\u003e76.81 %\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13.1988%;\"\u003e\n \u003cp\u003eFatigue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5.74534%;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.0435%;\"\u003e\n \u003cp\u003e-0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.7516%;\"\u003e\n \u003cp\u003e-1.35, 0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.2484%;\"\u003e\n \u003cp\u003e-1.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.1118%;\"\u003e\n \u003cp\u003e.237\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.0994%;\"\u003e\n \u003cp\u003e59.60 (\u0026lt; .0001)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.8012%;\"\u003e\n \u003cp\u003e88.25 %\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13.1988%;\"\u003e\n \u003cp\u003eMood\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5.74534%;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.0435%;\"\u003e\n \u003cp\u003e-0.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.7516%;\"\u003e\n \u003cp\u003e-1.37, 0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.2484%;\"\u003e\n \u003cp\u003e-1.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.1118%;\"\u003e\n \u003cp\u003e.198\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.0994%;\"\u003e\n \u003cp\u003e42.86 (\u0026lt; .0001)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.8012%;\"\u003e\n \u003cp\u003e88.34 %\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13.1988%;\"\u003e\n \u003cp\u003eSleep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5.74534%;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.0435%;\"\u003e\n \u003cp\u003e-0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.7516%;\"\u003e\n \u003cp\u003e-0.74, -0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.2484%;\"\u003e\n \u003cp\u003e3.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.1118%;\"\u003e\n \u003cp\u003e\u0026lt; .001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.0994%;\"\u003e\n \u003cp\u003e51.42 (\u0026lt; .0001)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.8012%;\"\u003e\n \u003cp\u003e74.72 %\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13.1988%;\"\u003e\n \u003cp\u003eProcessing speed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5.74534%;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.0435%;\"\u003e\n \u003cp\u003e-0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.7516%;\"\u003e\n \u003cp\u003e-0.64, -0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.2484%;\"\u003e\n \u003cp\u003e-2.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.1118%;\"\u003e\n \u003cp\u003e.015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.0994%;\"\u003e\n \u003cp\u003e34.39 (.0002)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.8012%;\"\u003e\n \u003cp\u003e70.92 %\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3:\u0026nbsp;\u003c/strong\u003eResults on moderator analysis for chronic exercise effects on depression severity\u003c/p\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"642\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 264px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModerator\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ek\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003edf\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eQM\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ep\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eQ (P)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 642px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStudy quality\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eRoB2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e182\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e.871\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e1207.15 (\u0026lt; .0001)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 642px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eExercise characteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eExercise type\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e182\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e13.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e.035\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e1071.52 (\u0026lt; .0001)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eExercise intensity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e182\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e4.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e.102\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e1172.79 (\u0026lt; .0001)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eSession duration (min)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e172\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e.635\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e1093.65 (\u0026lt; .0001)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eSession frequency (session / week)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e177\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e.741\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e1147.59 (\u0026lt; .0001)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eIntervention duration (weeks)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e181\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e.836\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e1149.08 (\u0026lt; .0001)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eTraining volume (min)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e172\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e3.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e.049\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e1141.24 (\u0026lt; .0001)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eCognitive demand\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e181\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e8.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e1159.96 (\u0026lt; .0001)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eSocial interaction\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e170\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e5.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e.075\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e1032.60 (\u0026lt; .0001)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eAutonomy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e176\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e4.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e.115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e1154.82 (\u0026lt; .0001)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 642px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePopulation characteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e181\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e12.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e.0004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e1119.47 (\u0026lt; .0001)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e168\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e.321\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e1137.87 (\u0026lt; .0001)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003ePopulation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e182\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e6.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e.349\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e1179.85 (\u0026lt; .0001)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eEducation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e.797\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e506.85 (\u0026lt; .0001)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eGlobal cognition\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e.301\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e355.38 (\u0026lt; .0001)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eHandgrip strength\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e.433\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e248.77 (\u0026lt; .0001)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003e6-min walk test\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e.763\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e267.69 (\u0026lt; .0001)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eDepression severity at baseline\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e182\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e10.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e1129.07 (\u0026lt; 0.0001)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 642px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eProtocol characteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eControl group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e182\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e.300\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e1203.80 (\u0026lt; .0001)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eType of analysis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e182\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e3.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e.153\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e1147.47 (\u0026lt; .0001)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eStudy design\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e182\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e.336\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e1195.98 (\u0026lt; .0001)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 642px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eInteraction between moderators\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eExercise type x Exercise intensity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e2.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e.810\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e365.74 (\u0026lt; .0001)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eCognitive demand x Depression severity at baseline\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e181\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e19.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e1087.32 (\u0026lt; .0001)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eCognitive demand x global cognition\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e9.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e.020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e294.64 (\u0026lt; .0001)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eAge x Cognitive demand\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e180\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e20.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026lt; .0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e1069.75 (\u0026lt; .0001)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eAge x Exercise intensity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e178\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e17.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e1073.17 (\u0026lt; .0001)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eIntervention duration x Exercise intensity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e177\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e7.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e.162\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e1107.45 (\u0026lt; .0001)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eExercise intensity x Depression severity at baseline\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e178\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e15.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e.044\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e1095.65 (\u0026lt; .0001)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e"},{"header":"Supplementary Material","content":"\u003cp\u003eSupplementary files 1-16 are not available with this version.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"aging, depressive symptoms, meta-regression, physical activity, exercise intervention","lastPublishedDoi":"10.21203/rs.3.rs-6795147/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6795147/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003ePrevious meta-analyses have demonstrated the effectiveness of chronic exercise in treating depression in older adults; however, the moderating effects of intervention, population, and protocol characteristics remain unclear. This study aims to investigate the effectiveness of chronic exercise on depression severity and core symptoms of depression in older adults, as well as how intervention, population, and protocol characteristics moderate these effects. We searched Web of Science, Academic Search Complete, MEDLINE, CINAHL, APA PsycInfo, SPORTDiscus, and Cochrane from inception until July 2023 for randomized controlled trials of chronic exercise interventions. The primary outcome was overall depression severity; secondary outcomes were indicators of core symptoms of depression. We used multilevel meta-analysis, subgroup comparisons, and meta-regression for analysis. We identified 143 peer-reviewed articles comprising 182 effect sizes and representing 14,789 participants (exercise group: n = 7,664; control group: n = 7,125). Chronic exercise significantly reduced overall depression severity with a moderate effect size and alleviated indicators of core symptoms of depression, including moderate effects on anxiety and small effects on BMI, executive functions, processing speed, and sleep. Effects were particularly strong for interventions that included exergames, had high training volumes, and high cognitive demand. Additionally, effects decreased with advancing age and lower baseline depression severity. The benefits of high-cognitive-demand exercises increased with declining global cognition levels. Individuals with mild to moderate depression benefited most from high-intensity and high-cognitive-demand exercises. The certainty of evidence for reducing the severity of depression was rated as low according to the GRADE approach. There is evidence of low certainty that chronic exercise is effective in treating depression in older adults, especially when tailored to the specific needs of the target population.\u003c/p\u003e","manuscriptTitle":"A meta-analysis of chronic exercise effects and moderating variables on depression severity and core symptoms in older adults","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-23 08:39:12","doi":"10.21203/rs.3.rs-6795147/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"73b26a44-2998-4a46-a921-c9d3ddd5be9f","owner":[],"postedDate":"July 23rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":50362328,"name":"Scientific community and society/Social sciences/Psychology/Human behaviour"},{"id":50362329,"name":"Health sciences/Medical research/Clinical trial design/Randomized controlled trials"},{"id":50362330,"name":"Health sciences/Health care/Geriatrics"}],"tags":[],"updatedAt":"2025-07-23T08:39:12+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-23 08:39:12","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6795147","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6795147","identity":"rs-6795147","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}