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An App-Based WHO Mental Health Guide for Depression Detection: A Cluster Randomized Clinical Trial.

Brandon A Kohrt1, Akin Ojagbemi2, Nagendra P Luitel3

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An app version of the World Health Organization Mental Health Gap Action Programme-Intervention Guide (mhGAP-IG) improved depression detection by primary care workers in Nigeria and Nepal. The e-mhGAP-IG showed varied use and cost-effectiveness across settings.

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Area of Science:

  • Global Health
  • Digital Health Interventions
  • Primary Care

Background:

  • Depression detection is limited in low- and middle-income countries.
  • The World Health Organization Mental Health Gap Action Programme-Intervention Guide (mhGAP-IG) is increasingly used.
  • There is a need to improve depression detection in primary care settings.

Purpose of the Study:

  • To test an app version of the mhGAP-IG (e-mhGAP-IG) in Nepal and Nigeria.
  • To assess the feasibility and effectiveness of the e-mhGAP-IG in improving depression detection.
  • To evaluate the cost-effectiveness of the e-mhGAP-IG.

Main Methods:

  • A feasibility cluster randomized clinical trial was conducted in Nepal and Nigeria.
  • Primary care facilities were randomized to standard mhGAP-IG training or e-mhGAP-IG training.
  • Depression detection rates by primary care workers (PCWs) were measured before and after training.

Main Results:

  • In Nepal, depression detection increased by 16% in the standard arm and 24% in the e-mhGAP-IG arm.
  • In Nigeria, depression detection increased by 19% in the standard arm and 71% in the e-mhGAP-IG arm.
  • The e-mhGAP-IG app was used in 10% of assessments in Nepal and 82% in Nigeria.

Conclusions:

  • The e-mhGAP-IG demonstrated potential for improving depression detection.
  • The use, cost, and clinical benefit of the e-mhGAP-IG varied significantly by setting.
  • Multisite feasibility studies are crucial for evaluating digital health innovations globally.