Feasibility and acceptability of a novel community-based mental health intervention delivered by community volunteers in Maharashtra, India: the Atmiyata programme
Bibliographic record
Abstract
BACKGROUND: Many community-based intervention models for mental health and wellbeing have undergone robust experimental evaluation; however, there are limited accounts of the implementation of these evidence-based interventions in practice. Atmiyata piloted the implementation of a community-led intervention to identify and understand the challenges of delivering such an intervention. The goal of the pilot evaluation is to identify factors important for larger-scale implementation across an entire district in India. This paper presents the results of a feasibility and acceptability study of the Atmiyata intervention piloted in Nashik district, Maharashtra, India between 2013 and 2015. METHODS: A mixed methods approach was used to evaluate the Atmiyata intervention. First, a pre-post survey conducted with 215 cases identified with a GHQ cut-off 6 using a 3-month interval. Cases enrolled into the study in one randomly selected month (May-June 2015). Secondly, a quasi-experimental, pre-post design was used to conduct a population-based survey in the intervention and control areas. A randomly selected sample (panel) of 827 women and 843 men age between 18 to 65 years were interviewed to assess the impact of the Atmiyata intervention on common mental disorders. Finally, using qualitative methods, 16 Champions interviewed to understand an implementation processes, barriers and facilitators. RESULTS: Of the 215 participants identified by the Champions as being distressed or having a common mental disorder (CMD), n = 202 (94.4%) had a GHQ score at either sub-threshold level for CMD or above at baseline. Champions accurately identified people with emotional distress and in need of psychological support. After a 6-session counselling provided by the Champions, the percentage of participants with a case-level GHQ score dropped from 63.8 to 36.8%. The second sub-intervention consisted of showing films on Champions' mobile phones to raise community awareness regarding mental health. Films consisted of short scenario-based depictions of problems commonly experienced in villages (alcohol use and domestic violence). Champions facilitated access to social benefits for people with disability. Retention of Atmiyata Champions was high; 90.7% of the initial selected champions continued to work till the end of the project. Champions stated that they enjoyed their work and found it fulfilling to help others. This made them willing to work voluntarily, without pay. The semi-structured interviews with champions indicated that persons in the community experienced reduced symptoms and improved social, occupational and family functioning for problems such as depression, domestic violence, alcohol use, and severe mental illness. CONCLUSIONS: This study shows that community-led interventions using volunteers from rural neighbourhoods can serve as a locally feasible and acceptable approach to facilitating access social welfare benefits, as well as reducing distress and symptoms of depression and anxiety in a low and middle-income country context. The intervention draws upon social capital in a community to engage and empower community members to address mental health problems. A robust evaluation methodology is needed to test the efficacy of such a model when it is implemented at scale.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".