An App-Based WHO Mental Health Guide for Depression Detection
Authors: Brandon A. Kohrt, Akin Ojagbemi, Nagendra P. Luitel, Ioannis Bakolis, Toyin Bello, Paul McCrone, Tatiana Taylor Salisbury, Mark J. D. Jordans, Nicole Votruba, Kenneth Carswell, Eric Green, Evdoxia Gkaintatzi, Bishnu Lamichhane, Olufisayo Elugbadebo, Lola Kola, Heidi Lempp, Neerja Chowdhary, Tarun Dua, Oye Gureje, Graham Thornicroft
Journal: JAMA Network Open (2025)

Importance Depression detection in primary care remains limited in low- and middle-income countries despite increasing use of the World Health Organization Mental Health Gap Action Programme–Intervention Guide (mhGAP-IG). Objective To test an app version of the mhGAP-IG (e-mhGAP-IG) in Nepal and Nigeria to improve depression detection. Design, Setting, and Participants In this feasibility cluster randomized clinical trial conducted from February 14, 2021, to March 25, 2022, primary care facilities (unit of clustering) in Nepal and Nigeria were randomized to the standard mhGAP-IG training arm (control) or to training using the e-mhGAP-IG app (intervention). Primary care workers (PCWs) received training based on the arm assignment of their health care facility. Statistical analysis was conducted from July 20, 2022, through September 27, 2024. Intervention Training using standard mhGAP-IG vs training using the e-mhGAP-IG. Main Outcomes and Measures Analysis was performed on an intention-to-treat basis. The main outcome was accuracy of depression detection rates by PCWs, evaluated prior to mhGAP training and 5 to 8 months after training, measured as the percentage of patients who received a depression diagnosis by their PCWs compared with the number of patients who scored 10 or more on the locally validated 9-item Patient Health Questionnaire. Costs per patient detected were calculated. Results In Nepal, 25 facilities (67 PCWs; mean [SD] age, 35.3 [9.2] years; 52 men [78%]) were randomized: 13 facilities to standard mhGAP-IG training (36 PCWs) and 12 facilities to e-mhGAP-IG (31 PCWs). In Nigeria, 10 facilities (47 PCWs; mean [SD] age, 46.9 [7.5] years; 44 women [94%]) were randomized: 5 facilities to standard mhGAP-IG (25 PCWs) and 5 facilities to e-mhGAP-IG (22 PCWs). In Nepal, depression detection by PCWs in the standard mhGAP-IG arm increased from 0 of 43 patients before training to 15 of 92 patients after training (adjusted mean change [AMC], 16% [95% CI, 5%-28%]), and depression detection in the e-mhGAP-IG arm increased from 0 of 49 before training to 22 of 91 after training (AMC, 24% [95% CI, 12%-36%]). In Nigeria, depression detection in the standard mhGAP-IG arm increased from 5 of 36 patients before training to 25 of 75 patients after training (AMC, 19% [95% CI, 2%-37%]), and depression detection in the e-mhGAP-IG arm increased from 6 of 35 patients before training to 67 of 76 patients after training (AMC, 71% [95% CI, 57%-85%]). In facilities in the e-mhGAP-IG arm, the app was used for 59 of 616 assessments (10% of patients) in Nepal and 883 of 1077 assessments (82% of patients) in Nigeria. Cost per patient with depression detected using the e-mhGAP-IG was Nepali Rupiya (NPR) 1980 (US $14.79) in Nepal and naira (₦) 1462 (US $0.91) in Nigeria. Conclusions and Relevance This feasibility cluster randomized clinical trial demonstrated that the use, cost, and potential clinical benefit of the e-mhGAP-IG varied by setting, highlighting the importance of multisite feasibility studies when evaluating digital innovations intended for health care systems worldwide. Trial Registration ClinicalTrials.gov Identifier: NCT04522453