Atmiyata, a community champion led psychosocial intervention for common mental disorders: A stepped wedge cluster randomized controlled trial in rural Gujarat, India
Bibliographic record
Abstract
BACKGROUND: While effective lay-health worker models for mental health care have been demonstrated through efficacy trials, there is limited evidence of the effectiveness of these models implemented in rural LMIC settings. AIM: To evaluate the impact of a volunteer community-led intervention on reduction in depression and anxiety symptoms and improvement in functioning, and social participation among people living in rural Gujarat, India. METHODS: Stepped-wedge cluster randomized controlled trial was used to assess the effectiveness of delivery of psychosocial intervention across 645 villages in Mehsana district of Gujarat, India between April 2017 and August 2019. The primary outcome was an improvement in depression and/or anxiety symptoms assessed using GHQ-12 at 3-month follow-up. Secondary outcomes were improvement in (a) depression and anxiety (Patient Health Questionnaire, (PHQ-9), Generalized Anxiety Disorder (GAD-7) & Self-Reporting Questionnaire-20 (SRQ-20); b) quality of life (EQ- 5D); c) functioning (WHO-DAS-12), and social participation (Social Participation Scale SPS). Generalized linear mixed-effects models were used to assess the independent effect of the intervention. RESULTS: Out of a total of 1191 trial participants (608- intervention & 583-control), 1014 (85%) completed 3-month follow-up. In an adjusted analysis, 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). Intervention participants had improved scores on the PHQ-9 (Adjusted mean difference (AMD) -1.8; 95%CI -3.0 to -0.6), and SRQ-20 (AMD -1.7; 95%CI -2.7 to -0.6), at 3-months and PHQ-9, GAD-7, SRQ-20, EQ-5D and WHO-DAS at 8 months follow-up. CONCLUSION: Findings suggest that Atmiyata had a significant effect on recovery from symptoms of depression and anxiety with sustained effects at 8-month follow-up. TRIAL REGISTRATION: Trial registration details. The 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) | 0.002 | 0.002 |
| 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) | 0.006 | 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".