Evidence map›Paper›PMID 40112295›Full record

SynthesisJournal of medical Internet research2025

Effectiveness of Digital Lifestyle Interventions on Depression, Anxiety, Stress, and Well-Being: Systematic Review and Meta-Analysis.

Jacinta Brinsley, Edward J O'Connor, Ben Singh, Grace McKeon, Rachel Curtis, Ty Ferguson, Georgia Gosse, Iris Willems, Pieter-Jan Marent, Kimberley Szeto and 2 more

Abstract readSystematic ReviewMeta-Analysis
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in Journal of medical Internet research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 3 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
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  4. Trial
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  7. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Jacinta BrinsleyAlliance for Research in Exercise, Nutrition and Activity, University of South Australia, Adelaide, Australia.ORCID https://orcid.org/0000-0002-2588-9649
Edward J O'ConnorHealth & Biosecurity, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Adelaide, Australia.ORCID https://orcid.org/0000-0003-3770-8355
Ben SinghAlliance for Research in Exercise, Nutrition and Activity, University of South Australia, Adelaide, Australia.ORCID https://orcid.org/0000-0002-7227-2406
Grace McKeonDiscipline of Psychiatry and Mental Health, School of Clinical Medicine, Nutrition, Exercise and Social Equity (NExuS), University of New South Wales, Sydney, Australia.ORCID https://orcid.org/0000-0003-4722-1639
Rachel CurtisAlliance for Research in Exercise, Nutrition and Activity, University of South Australia, Adelaide, Australia.ORCID https://orcid.org/0000-0002-1341-7804
Ty FergusonAlliance for Research in Exercise, Nutrition and Activity, University of South Australia, Adelaide, Australia.ORCID https://orcid.org/0000-0003-0106-7621
Georgia GosseIIMPACT in Health, University of South Australia, Adelaide, Australia.ORCID https://orcid.org/0000-0002-5460-6329
Iris WillemsDepartment of Movement and Sports Sciences, Research Centre for Aging Young, Ghent University, Ghent, Belgium.ORCID https://orcid.org/0000-0003-2654-8931
Pieter-Jan MarentDepartment of Movement and Sports Sciences, Research Centre for Aging Young, Ghent University, Ghent, Belgium.ORCID https://orcid.org/0000-0002-9308-931X
Kimberley SzetoAlliance for Research in Exercise, Nutrition and Activity, University of South Australia, Adelaide, Australia.ORCID https://orcid.org/0000-0001-9469-9139
Joseph FirthDivision of Psychology and Mental Health, Manchester Academic Health Science Centre, The University of Manchester, Manchester, United Kingdom.ORCID https://orcid.org/0000-0002-0618-2752
Carol MaherAlliance for Research in Exercise, Nutrition and Activity, University of South Australia, Adelaide, Australia.ORCID https://orcid.org/0000-0002-8676-0224

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThere is a growing body of robust evidence to show that lifestyle behaviors influence mental health outcomes. Technology offers an accessible and cost-effective implementation method for interventions, yet the study of the effectiveness of interventions to date has been specific to the mode of delivery, population, or behavior.

objectiveThe primary aim of this review was to comprehensively evaluate the effectiveness of digital lifestyle interventions for improving symptoms of depression, anxiety, stress, and well-being as coprimary outcomes in adults. The secondary aim was to explore the technological, methodological, intervention-specific, and population-specific characteristics that were associated with major changes in mental health outcomes.

methodsA systematic search was conducted across the MEDLINE, CINAHL, Embase, Emcare, PsycINFO, and Scopus databases to identify studies published between January 2013 and January 2023. Randomized controlled trials of lifestyle interventions (physical activity, sleep, and diet) that were delivered digitally; reported changes in symptoms of depression, anxiety, stress, or well-being in adults (aged ≥18 years); and were published in English were included. Multiple authors independently extracted data, which was evaluated using the 2011 Levels of Evidence from the Oxford Centre for Evidence-Based Medicine. Inverse-variance random-effects meta-analyses were used for data analysis. The primary outcome was the change in symptoms of depression, anxiety, stress, and well-being as measured by validated self-report of clinician-administered outcomes from pre- to postintervention. Subgroup analyses were conducted to determine whether results differed based on the target lifestyle behavior, delivery method, digital features, design features, or population characteristics.

resultsOf the 14,356 studies identified, 61 (0.42%) were included. Digital lifestyle interventions had a significant small-to-medium effect on depression (standardized mean difference [SMD] -0.37; P<.001), a small effect on anxiety (SMD -0.29; P<.001) and stress (SMD -0.17; P=.04), and no effect on well-being (SMD 0.14; P=.15). Subgroup analyses generally suggested that effects were similar regardless of the delivery method or features used, the duration and frequency of the intervention, the population, or the lifestyle behavior targeted.

conclusionsOverall, these results indicate that delivering lifestyle interventions via a range of digital methods can have significant positive effects on depression (P<.001), anxiety (P<.001), and stress (P=.04) for a broad range of populations, while effects on well-being are inconclusive. Future research should explore how these interventions can be effectively implemented and embedded within health care with a concerted focus on addressing digital health equity.

trial registrationPROSPERO CRD42023428908; https://www.crd.york.ac.uk/PROSPERO/view/CRD42023428908.

Indexed as

AnxietyDepressionLife StyleStress, PsychologicalAdultExerciseHumansanxietydepressiondietdigital healthlifestyle interventionmental healthmobile phonephysical activitysleepstresswell-being

Identifiers

PMID40112295
PMCPMC11969127

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.