MétaCan
Menu
← Back to cohort
Record W4223649051 · doi:10.2196/preprints.38049

The Effectiveness of Internet-guided Self-help Interventions to Promote Physical Activity Among Individuals with Depression: Systematic Review (Preprint)

2022· preprint· en· W4223649051 on OpenAlexaboutno aff
Yiling Tang, Madelaine Gierc, Raymond W. Lam, Sam Liu, Guy Faulkner

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsnot available
Fundersnot available
KeywordsPsycINFOPsychological interventioneHealthDepression (economics)Randomized controlled trialMedicineMEDLINESystematic reviewIntervention (counseling)Physical therapyPsychiatryClinical psychologyHealth careInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND Depression is a prevalent and debilitating mental disorder and one of the leading causes of disability in Canada and around the world. Structured exercise interventions have been identified as effective in alleviating depression, and exercise is now recommended as a treatment for mild-to-moderate depression in Canada. It may not always be possible, however, to access supervised and structured exercise interventions for depression. Internet-guided self-help (IGSH) interventions, a type of eHealth intervention, may be an effective alternative in increasing physical activity among people with depression who cannot, or prefer not to, access supervised exercise treatment. OBJECTIVE The objective of this systematic review (PROSPERO 2020 CRD42020221713) is to evaluate the effectiveness of IGSH interventions in increasing physical activity and alleviating depressive symptoms among people with depression (PWD). METHODS Two rounds of systematic literature searches for randomized controlled trials (RCTs) and quasi-experimental studies were conducted in nine electronic databases (e.g., Medline, PsycINFO) in December 2020 and November 2021 from their inception. RESULTS Five RCTs (502 participants) met the inclusion criteria. Four were web-based and one was app-based. Three studies indicated that IGSH interventions have medium to large effects on decreasing depressive symptoms but not on increasing physical activity compared to waitlist/usual care groups. Two studies showed increased self-reported physical activity but no significant change in depressive symptoms in the intervention groups compared to control groups. None of the included studies reported changes in physical activity as a primary outcome. Goal-setting, problem solving, feedback on behaviour, and self-monitoring of behaviour were the four most common behaviour change techniques used in the interventions. Dropout rates in intervention groups were relatively low (0% - 21.9%). CONCLUSIONS Our findings suggest that IGSH physical activity interventions are feasible and moderately effective in improving depressive symptoms among PWD. More well-designed and tailored interventions with different combinations of BCTs, particularly those targeting the emotion domain, are needed to assess the overall effectiveness and feasibility of using IGSH interventions for increasing physical activity among PWD.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.043
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.010
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.043
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0080.008
Bibliometrics0.0050.005
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0060.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.047
GPT teacher head0.376
Teacher spread0.329 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

Explore more

Same topicPhysical Activity and Health→French-language works237,207→