A Mixed Methods Study of the Acceptability and Feasibility of a Community-Based mHealth Motivational Interviewing Tool for Depression (COMMIT-D) (Preprint)

BACKGROUND Motivational interviewing (MI) is a structured, person-centered approach that increases a patient’s likelihood of engaging in healthy behaviors. MI can be delivered by non-specialists, making it promising for low- and middle-income countries (LMICs), where mental health specialists are scarce. Community health workers (CHWs) are well-positioned to deliver MI but often lack structured supervision, leading to skill decay after training. Because CHWs work primarily in communities rather than clinics, direct observation and timely feedback are difficult. Digital mobile health (mHealth) tools can help bridge this supervision gap, yet real-world evidence on their acceptability and feasibility remains limited. OBJECTIVE To assess the acceptability and feasibility of COMMIT-D, an mHealth tool designed to support CHWs in delivering motivational interviewing for depression care and receiving remote supervision in rural Nepal. METHODS We conducted a single-arm, mixed-methods study (2019–2022) to develop and pilot test COMMIT-D, a community-based mHealth tool for CHWs. The study was implemented within a primary care system in Dolakha, Nepal, where CHWs are responsible for coordinating care for noncommunicable diseases, mental health, and maternal health. COMMIT-D provides guided prompts on MI skills, captures patient medication adherence and stages of change, and enables audio recording of consented interactions for asynchronous supervisor feedback. A total of 20 CHWs delivered MI to patients with depression identified as having suboptimal care engagement. Quantitative measures included patient-reported adherence and stages of change, as well as a 9-item survey assessing CHW acceptability and feasibility. Qualitative data were collected in two rounds (January and August 2022) using focus group discussions with CHWs (total 7 FGDs, n=41) and semi-structured interviews with CHWs’ supervisors (n=8) and patients (n=13). RESULTS Of 340 patients with depression in the electronic health record, 71 (20.9%) had limited engagement with care. Of those, 65 (91%) were approached, and 37 (58%) completed three MI visits by CHWs. More than 40% of the CHWs delivered four or more MI sessions. All CHWs knew how to seek MI support, and 64% received supervisory feedback at least once. Perceived acceptability among CHWs was high, with more than 94% reporting that MI improved their ability to understand and respond to patients’ needs, and over 80% agreed that MI is applicable to other noncommunicable diseases beyond depression. Findings from CHW focus groups and interviews with supervisors and patients indicated that, despite initial challenges related to audio recording for supervision and the use of MI skills, all participants found COMMIT-D acceptable and feasible. CONCLUSIONS COMMIT-D was feasible and acceptable to CHWs, supervisors, and patients, demonstrating that an mHealth tool can support MI delivery and remote supervision within routine CHW workflows. By addressing supervision barriers and supporting MI practice, COMMIT-D offers a scalable approach for strengthening patient engagement in depression care in rural LMICs. CLINICALTRIAL This study was registered at ClinicalTrials.gov on August 12, 2020 (Registration Number: NCT04510909; Title: COMMIT Depression Trial Nepal).