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BACKGROUND: Training non-specialist health workers (NSHWs) at scale is a major barrier to increasing the coverage of depression care in India. This trial will test the effectiveness of two forms of digital training compared to conventional face-to-face training in changing the competence of NSHWs to deliver a brief evidence-based psychological treatment for depression. METHODS: This protocol is for a three-arm, parallel group randomized controlled trial comparing three ways of training NSHWs to deliver the Healthy Activity Program (HAP), a brief manualized psychotherapy for depression, in primary care. The arms are: digital training (DGT); digital training combined with individualized coaching support (DGT+); and conventional face-to-face training (F2F). The target sample comprises N = 336 government contracted NSHWs in Madhya Pradesh, India. The primary outcome is change of competence to deliver HAP; secondary outcomes include cost-effectiveness of the training programs, change in participants' mental health knowledge, attitudes and behavior, and satisfaction with the training. Assessors blind to participant allocation status will collect outcomes pre- (baseline) and post- (endpoint) training to ascertain differences in outcomes between arms. Training program costs will be collected to calculate incremental costs of achieving one additional unit on the competency measure in the digital compared to face-to-face training programs. Health worker motivation, job satisfaction, and burnout will be collected as exploratory outcome variables. DISCUSSION: This trial will determine whether digital training is an effective, cost-effective, and scalable approach for building workforce capacity to deliver a brief evidence-based psychological treatment for depression in primary care in a low-resource setting. TRIAL REGISTRATION: Identifier: NCT04157816.

Original publication




Journal article


Contemp Clin Trials

Publication Date



Community health workers, Depression, Digital health, Mental health, Task sharing, Training