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Published on: February 19, 2021
Characterizing modifications to the mental health gap action programme (mhGAP) intervention guide during
Harikeerthan Raghuram1, Akanksha Jayant Rajguru2, Mythili Menon Pathiyil3
1Sangath, Bhopal, India. harikeerthan.raghuram@sangath.in.
Background:
Low- and middle-income countries (LMICs) allocate a disproportionately small fraction of their healthcare budgets to mental health, leading to a treatment gap exceeding 75%. To address this disparity, the World Health Organization (WHO) introduced the Mental Health Gap Action Programme (mhGAP), aiming to integrate mental healthcare into primary and community care settings. Central to this initiative is task-sharing: empowering non-specialist healthcare providers to detect and treat mental disorders. Adaptation and modification of mhGAP to the national and local contexts is an integral aspect of the guidelines.
Methods:
This systematic review of reviews employs the Framework for Reporting Adaptations and Modifications-Expanded (FRAME) to document and characterize modifications to mhGAP implementation in LMICs. The databases searched included Embase, PubMed, PsycINFO, CINAHL, Google Scholar, Cochrane, and Web of Science. Reviews selected in stage 1 were used to find empirical studies from which relevant data was extracted.
Results:
Narrative synthesis suggests that modifications primarily focus on content, delivery, and training methods, with limited attention to scaling up. Modifications adopt top down, yet consultative and participatory approaches. There is a notable lack of reporting on challenges, processes, and outcomes. Recommendations have been made to expand FRAME, namely, sources of knowledge, financial and temporal resources employed during the process of modification.
Conclusion:
Modifications are essential for adapting interventions to diverse settings, yet they are often researcher-led with limited stakeholder involvement. Better documentation-particularly on challenges and outcomes-is needed. Strengthening frameworks like FRAME can improve reporting, optimize resources, and enhance implementation and scale-up in similar contexts.
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