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Record W2484473026 · doi:10.1192/bjp.bp.115.169094

Social support and protection from depression: systematic review of current findings in Western countries

2016· review· en· W2484473026 on OpenAlexafffund
Geneviève Gariépy, Helena Honkaniemi, Amélie Quesnel‐Vallée

Bibliographic record

VenueThe British Journal of Psychiatry · 2016
Typereview
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsMcGill UniversityMcGill University Health Centre
FundersNational Institute on AgingCanadian Institutes of Health Research
KeywordsSocial supportChecklistPsychologyMeta-analysisCohort studyCohortDepression (economics)Systematic reviewCausality (physics)Critical appraisalClinical psychologyDemographyMedicineGerontologyMEDLINESocial psychologyAlternative medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Numerous studies report an association between social support and protection from depression, but no systematic review or meta-analysis exists on this topic. AIMS: To review systematically the characteristics of social support (types and source) associated with protection from depression across life periods (childhood and adolescence; adulthood; older age) and by study design (cross-sectional v cohort studies). METHOD: A systematic literature search conducted in February 2015 yielded 100 eligible studies. Study quality was assessed using a critical appraisal checklist, followed by meta-analyses. RESULTS: Sources of support varied across life periods, with parental support being most important among children and adolescents, whereas adults and older adults relied more on spouses, followed by family and then friends. Significant heterogeneity in social support measurement was noted. Effects were weaker in both magnitude and significance in cohort studies. CONCLUSIONS: Knowledge gaps remain due to social support measurement heterogeneity and to evidence of reverse causality bias.

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)0.006
metaresearch head score (Gemma)0.024
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 score0.009
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.024
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0060.007
Bibliometrics0.0070.008
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.048
GPT teacher head0.394
Teacher spread0.346 · 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

Citations1,199
Published2016
Admission routes2
Has abstractyes

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