Task sharing and stepped referral model for community mental health promotion in low- and middle-income countries (LMIC): insights from a feasibility study in India

Saju Madavanakadu Devassy1,2,3, Lorane Scaria1,3, Natania Cheguvera3
1Department of Social Work, Rajagiri College of Social Sciences (Autonomous), Cochin, India
2Honorary Principal Fellow, Department of Social Work, Melbourne School of Health Sciences, University of Melbourne, Melbourne, Australia
3Rajagiri International Centre for Consortium Research in Social care (ICRS), Cochin, India

Tóm tắt

Abstract Background This study is a low-cost community mental health task-sharing model driven by university students to strengthen the mental health workforce in poor resource settings. This article presents the feasibility of a stepped referral model using the community health workforce and university students. The primary feasibility objective is to detect and refer people with mental illness from the community using a task-sharing approach. Methods We tested the model using a cross-sectional, one-phase door-knock survey in three geographically defined locations in Kerala, India, between May and July 2019. Students surveyed 549 residents above 18 years of age who consented to participate in the study to detect depressive symptoms and suicidality. The feasibility of the current model was evaluated based on four criteria: (a) identification and deployment of untapped human resources, (b) coordination of community health resources, (c) the acceptability of stepped referral pathways, and (d) identification of implementation challenges. Results The mean age of the participants was 38.8, and more than 62% of the respondents were women. The results showed that 11.29%, 8.38%, and 4.91% of people reported mild, moderate, and severe levels of depression, respectively, and suicidal thoughts were found in 6.9% and suicidal ideation in 1.8%. The odds of depression were higher among females compared to males (OR: 1.64 (0.75–2.52), poor people (OR: 2.01 (1.14–2.88), and people with chronic illnesses (OR: 2.03 (1.24–2.81). The agreement of the findings with professional-administered research validated the strategy’s efficiency. Twenty-seven patients with severe/extreme degrees of depression were sent for high-intensity interventions led by the mental health team, whereas 135 individuals with mild and above depression were referred for low-intensity interventions. Conclusions The newly recruited mental health workforce-driven screenings were acceptable and effective in detecting mental illness in the community population. We tested the care coordination systems and processes in creating referral pathways for the detected patients. Further, task-sharing stepped referral model will be tested in five panchayats (the lowest tier of local self-government) before replicating the model across India through Unnat Bharat Abhiyan (UBA) scheme.

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