Atmiyata, a community led psychosocial intervention, for common mental disorders: A stepped wedge, cluster randomized controlled trial in rural Gujarat, India
Bibliographic record
Abstract
Abstract This study evaluates the effectiveness of a volunteer community-led psychosocial intervention on depression and anxiety symptoms among people living in rural Gujarat, India. Stepped-wedge cluster randomized controlled trial design implemented in 645 villages in Mehsana district, Gujarat, India. Primary outcome was improvement in depression and/or anxiety symptoms using GHQ-12 at 3-month follow-up. Data was analyzed using generalized linear mixed effects models.Of the 1191 participants (608- intervention & 583-control) recruited, 1014 (85%) completed 3-month follow-up. After adjusting for baseline covariates, period, and cluster effects, participants in the intervention condition showed significant recovery from symptoms of depression or anxiety (OR 2.2; 95% CI 1.2 to 4.6; p < 0.05) at the end of 3-months, with effects sustained at 8-month follow-up (OR 3.0; 95% CI 1.6 to 5.9). The study findings have implications for the broader implementation and scale-up of community-based mental health delivery models in LMICs.Trial registration detailsThe trial was registered prospectively with the Clinical Trial Registry in India (registry number: CTRI/2017/03/008139).
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".