Social capital and common mental disorder: a systematic review
Bibliographic record
Abstract
OBJECTIVE: This study aims to systematically review all published quantitative studies examining the direct association between social capital and common mental disorders (CMD). Social capital has potential value for the promotion and prevention of CMD. The association between different types of social capital (individual cognitive and structural, and ecological cognitive and structural) and CMD must be explored to obtain conclusive evidence regarding the association, and to ascertain a direction of causality. DESIGN: 10 electronic databases were searched to find studies examining the association between social capital and CMD published before July 2014. The effect estimates and sample sizes for each type of social capital were separately analysed for cross-sectional and cohort studies. From 1857 studies retrieved, 39 were selected for inclusion: 31 cross-sectional and 8 cohort studies. 39 effect estimates were found for individual level cognitive, 31 for individual level structural, 9 for ecological level cognitive and 11 for ecological level structural social capital. MAIN RESULTS: This review provides evidence that individual cognitive social capital is protective against developing CMD. Ecological cognitive social capital is also associated with reduced risk of CMD, though the included studies were cross-sectional. For structural social capital there was overall no association at either the individual or ecological levels. Two cross-sectional studies found that in low-income settings, a mother's participation in civic activities is associated with an increased risk of CMD. CONCLUSIONS: There is now sufficient evidence to design and evaluate individual and ecological cognitive social capital interventions to promote mental well-being and prevent CMD.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.047 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.020 | 0.016 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".