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The efficacy of exercise in reducing depressive symptoms among cancer survivors: a meta-analysis.

ABSTRACT: INTRODUCTION: The purpose of this meta-analysis was to examine the efficacy of exercise to reduce depressive symptoms among cancer survivors. In addition, we examined the extent to which exercise dose and clinical characteristics of cancer survivors influence the relationship between exercise and reductions in depressive symptoms. METHODS: We conducted a systematic search identifying randomized controlled trials of exercise interventions among adult cancer survivors, examining depressive symptoms as an outcome. We calculated effect sizes for each study and performed weighted multiple regression moderator analysis. RESULTS: We identified 40 exercise interventions including 2,929 cancer survivors. Diverse groups of cancer survivors were examined in seven exercise interventions; breast cancer survivors were examined in 26; prostate cancer, leukemia, and lymphoma were examined in two; and colorectal cancer in one. Cancer survivors who completed an exercise intervention reduced depression more than controls, d(+)?=?-0.13 (95% CI: -0.26, -0.01). Increases in weekly volume of aerobic exercise reduced depressive symptoms in dose-response fashion (??=?-0.24, p?=?0.03), a pattern evident only in higher quality trials. Exercise reduced depressive symptoms most when exercise sessions were supervised (??=?-0.26, p?=?0.01) and when cancer survivors were between 47-62 yr (??=?0.27, p?=?0.01). CONCLUSION: Exercise training provides a small overall reduction in depressive symptoms among cancer survivors but one that increased in dose-response fashion with weekly volume of aerobic exercise in high quality trials. Depressive symptoms were reduced to the greatest degree among breast cancer survivors, among cancer survivors aged between 47-62 yr, or when exercise sessions were supervised.

SUBMITTER: Brown JC

PROVIDER: S-EPMC3267760 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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The efficacy of exercise in reducing depressive symptoms among cancer survivors: a meta-analysis.

Brown Justin C JC Huedo-Medina Tania B TB Pescatello Linda S LS Ryan Stacey M SM Pescatello Shannon M SM Moker Emily E LaCroix Jessica M JM Ferrer Rebecca A RA Johnson Blair T BT

PloS one 20120127 1

<h4>Introduction</h4>The purpose of this meta-analysis was to examine the efficacy of exercise to reduce depressive symptoms among cancer survivors. In addition, we examined the extent to which exercise dose and clinical characteristics of cancer survivors influence the relationship between exercise and reductions in depressive symptoms.<h4>Methods</h4>We conducted a systematic search identifying randomized controlled trials of exercise interventions among adult cancer survivors, examining depre ...[more]

PMID: 22303474

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Project description:Importance:The physical benefits of resistance exercise training (RET) are well documented, but less is known regarding the association of RET with mental health outcomes. To date, no quantitative synthesis of the antidepressant effects of RET has been conducted. Objectives:To estimate the association of efficacy of RET with depressive symptoms and determine the extent to which logical, theoretical, and/or prior empirical variables are associated with depressive symptoms and whether the association of efficacy of RET with depressive symptoms accounts for variability in the overall effect size. Data Sources:Articles published before August 2017, located using Google Scholar, MEDLINE, PsycINFO, PubMed, and Web of Science. Study Selection:Randomized clinical trials included randomization to RET (n = 947) or a nonactive control condition (n = 930). Data Extraction and Synthesis:Hedges d effect sizes were computed and random-effects models were used for all analyses. Meta-regression was conducted to quantify the potential moderating influence of participant and trial characteristics. Main Outcomes and Measures:Randomized clinical trials used validated measures of depressive symptoms assessed at baseline and midintervention and/or postintervention. Four primary moderators were selected a priori to provide focused research hypotheses about variation in effect size: total volume of prescribed RET, whether participants were healthy or physically or mentally ill, whether or not allocation and/or assessment were blinded, and whether or not the RET intervention resulted in a significant improvement in strength. Results:Fifty-four effects were derived from 33 randomized clinical trials involving 1877 participants. Resistance exercise training was associated with a significant reduction in depressive symptoms with a moderate-sized mean effect ∆ of 0.66 (95% CI, 0.48-0.83; z = 7.35; P < .001). Significant heterogeneity was indicated (total Q = 216.92, df = 53; P < .001; I2 = 76.0% [95% CI, 72.7%-79.0%]), and sampling error accounted for 32.9% of observed variance. The number needed to treat was 4. Total volume of prescribed RET, participant health status, and strength improvements were not significantly associated with the antidepressant effect of RET. However, smaller reductions in depressive symptoms were derived from randomized clinical trials with blinded allocation and/or assessment. Conclusions and Relevance:Resistance exercise training significantly reduced depressive symptoms among adults regardless of health status, total prescribed volume of RET, or significant improvements in strength. Better-quality randomized clinical trials blinding both allocation and assessment and comparing RET with other empirically supported treatments for depressive symptoms are needed.

Project description:BackgroundDepressive symptoms in patients with cancer are associated with poor quality of life and decreased survival. Although inflammation is reliably associated with depression in otherwise healthy individuals, the association in patients with cancer remains unclear. Given the high prevalence of cancer-related inflammation, the authors aimed to establish the relationship between inflammation and depression in cancer patients based on extant literature.MethodsA systematic review and meta-analysis was performed using Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 guidelines and registered under Prospero ID CRD42021226743. Three databases were searched including PubMed, the Cochrane Library, and PsycINFO using the following criteria for inclusion: 1) measurement of a peripheral inflammatory marker, 2) use of a validated tool/scale to measure depression, and 3) a cancer diagnosis. Risk of publication bias was assessed by Funnel plot and Egger test.ResultsSeventy-three studies were included in the systematic review and 54 studies (n = 5017) were included in meta-analyses. Associations with depressive symptoms were significant for peripheral blood interleukin (IL)-6 (standardized mean difference [SMD] = 0.59; 95% confidence interval [CI], 0.35-0.82), I2 = 57.9%; tumor necrosis factor (TNF) (SMD = 0.73; 95% CI, 0.35-1.11), I2 = 74.1%; and C-reactive protein (CRP) (SMD = 0.57; 95% CI, 0.27-0.87), I2 = 0%. IL-5, IL-13, albumin, and neutrophil-to-lymphocyte ratio were associated with depressive symptoms but based on fewer studies. Most cancer settings were represented; the number of studies per inflammatory marker varied from 1 to 52.ConclusionsAlthough peripheral inflammatory markers were unevenly studied, the most studied markers (IL-6, TNF, and CRP) were associated with depressive symptoms in cancer patients and may be useful for management of depressive symptoms in the cancer setting.Lay summaryPeripheral blood inflammatory markers (IL-6, TNF, and CRP) were associated with depressive symptoms in various cancer settings. Although further studies are warranted, these findings may help identify and manage depressive symptoms in patients with cancer.

Project description:BackgroundThe incidence of depression is increasing worldwide. Depression can lead to poor physical health and even suicide. However, in high-income countries, only about 50% of the people with depression receive appropriate therapy, and the detection rate of depression in low- and middle-income countries is relatively lower. Web-based self-management enables remote treatment and solves the problem of insufficient psychological treatment resources. Many past studies have evaluated the effectiveness of web-based self-management of depression, but there has been no synthesis of evidence. Therefore, this study conducted a meta-analysis of the effectiveness of web-based self-management for depressive symptoms.MethodSix electronic databases (Cochrane Central Register of Controlled Trials, PubMed, Web of Science, Embase, CINAHL, and PsycINFO) were searched in September 2020. All literature referring to the effects of web-based self-management on depression were shortlisted by performing the medical subject headings (MeSH) search combined with a text word search.ResultsA total of 18 eligible randomized controlled trials were identified, and the results from 3055 participants were consolidated. The web-based self-management group exhibited a greater reduction in depressive symptoms than the control group (g = - 0.46; 95% CI: 0.62,0.30), and there was no evidence of publication bias. Subgroup analysis revealed that patients with moderate-to-severe depression benefited from web-based self-management interventions. In terms of interventions, those based on cognitive behavioral therapy (CBT) were highly effective. We noted that the longer the intervention time, the better was the improvement in the status of depression. Furthermore, it was established that participants who communicated with therapists and showed greater adherence to the intervention experienced significant improvement in their symptoms. The results of the intervention group were better than those of the waiting-list, treatment-as-usual, and online psychoeducation groups.ConclusionsWeb-based self-management is a promising therapy for depression. Future research should aim to refine these aspects of the intervention to achieve a beneficial impact.

Project description:BackgroundThe introduction of natural language processing (NLP) technologies has significantly enhanced the potential of self-administered interventions for treating anxiety and depression by improving human-computer interactions. Although these advances, particularly in complex models such as generative artificial intelligence (AI), are highly promising, robust evidence validating the effectiveness of the interventions remains sparse.ObjectiveThe aim of this study was to determine whether self-administered interventions based on NLP models can reduce depressive and anxiety symptoms.MethodsWe conducted a systematic review and meta-analysis. We searched Web of Science, Scopus, MEDLINE, PsycINFO, IEEE Xplore, Embase, and Cochrane Library from inception to November 3, 2023. We included studies with participants of any age diagnosed with depression or anxiety through professional consultation or validated psychometric instruments. Interventions had to be self-administered and based on NLP models, with passive or active comparators. Outcomes measured included depressive and anxiety symptom scores. We included randomized controlled trials and quasi-experimental studies but excluded narrative, systematic, and scoping reviews. Data extraction was performed independently by pairs of authors using a predefined form. Meta-analysis was conducted using standardized mean differences (SMDs) and random effects models to account for heterogeneity.ResultsIn all, 21 articles were selected for review, of which 76% (16/21) were included in the meta-analysis for each outcome. Most of the studies (16/21, 76%) were recent (2020-2023), with interventions being mostly AI-based NLP models (11/21, 52%); most (19/21, 90%) delivered some form of therapy (primarily cognitive behavioral therapy: 16/19, 84%). The overall meta-analysis showed that self-administered interventions based on NLP models were significantly more effective in reducing both depressive (SMD 0.819, 95% CI 0.389-1.250; P<.001) and anxiety (SMD 0.272, 95% CI 0.116-0.428; P=.001) symptoms compared to various control conditions. Subgroup analysis indicated that AI-based NLP models were effective in reducing depressive symptoms (SMD 0.821, 95% CI 0.207-1.436; P<.001) compared to pooled control conditions. Rule-based NLP models showed effectiveness in reducing both depressive (SMD 0.854, 95% CI 0.172-1.537; P=.01) and anxiety (SMD 0.347, 95% CI 0.116-0.578; P=.003) symptoms. The meta-regression showed no significant association between participants' mean age and treatment outcomes (all P>.05). Although the findings were positive, the overall certainty of evidence was very low, mainly due to a high risk of bias, heterogeneity, and potential publication bias.ConclusionsOur findings support the effectiveness of self-administered NLP-based interventions in alleviating depressive and anxiety symptoms, highlighting their potential to increase accessibility to, and reduce costs in, mental health care. Although the results were encouraging, the certainty of evidence was low, underscoring the need for further high-quality randomized controlled trials and studies examining implementation and usability. These interventions could become valuable components of public health strategies to address mental health issues.Trial registrationPROSPERO International Prospective Register of Systematic Reviews CRD42023472120; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023472120.

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The efficacy of exercise in reducing depressive symptoms among cancer survivors: a meta-analysis.

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The efficacy of exercise in reducing depressive symptoms among cancer survivors: a meta-analysis.

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