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Feasibility and acceptability of a novel community-based mental health intervention delivered by community volunteers in Maharashtra, India: the Atmiyata programme

  • Joag, Kaustubh1
  • Shields-Zeeman, Laura2
  • Kapadia-Kundu, Nandita3
  • Kawade, Rama1
  • Balaji, Madhumitha1, 4
  • Pathare, Soumitra1
  • 1 Centre for Mental Health Law and Policy, Indian Law Society, Pune, 411004, India , Pune (India)
  • 2 Trimbos Institute (Netherlands Institute for Mental Health and Addiction), Da Costakade 45, Utrecht, VS, 3521, the Netherlands , Utrecht (Netherlands)
  • 3 John Hopkins Bloomberg School of Public Health, Baltimore, MD, 21202, USA , Baltimore (United States)
  • 4 Sangath, South Goa, Goa, 403720, India , South Goa (India)
Published Article
BMC Psychiatry
Springer (Biomed Central Ltd.)
Publication Date
Feb 07, 2020
DOI: 10.1186/s12888-020-2466-z
Springer Nature


BackgroundMany 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.MethodsA 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.ResultsOf 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.ConclusionsThis 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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