Objectives: We conducted an implementation science mental health treatment study in western Kenya, testing strategies for scale up of evidence-based mental health services for common adult disorders using a non-specialist workforce, integrated with existing primary care (Sequential Multiple, Assignment Randomized Trial of non-specialist-delivered psychotherapy (Interpersonal Psychotherapy) and/or medication (fluoxetine) for major depression and post-traumatic stress disorder (PTSD) (SMART DAPPER)). Because study launch coincided with the COVID-19 pandemic, participants were allowed to attend treatment visits via mHealth (audio-only mobile phone) or in-person. We conducted a secondary data analysis of the parent study to evaluate preference for mHealth or in-person treatment among our study participants, including rationale for choosing in-person or mHealth treatment modality, and comparison of baseline demographic and clinical characteristics.
Design, setting, participants and interventions: Participants were public sector primary care patients at Kisumu County Hospital in western Kenya with major depression and/or PTSD and were individually randomised to non-specialist delivery of evidence-based psychotherapy or medication (n=2162).
Outcomes: Treatment modality preference and rationale were ascertained before randomised assignment to treatment arm (psychotherapy or medication). The parent SMART DAPPER study baseline assessment included core demographic (age, gender, relationship status, income, clinic transport time and cost) and clinical data (eg, depression and PTSD symptoms, trauma exposures, medical comorbidities and history of mental healthcare). Given that this evaluation of mHealth treatment preference sought to identify the demographic and clinical characteristics of participants who chose in-person or mHealth treatment modality, we included most SMART DAPPER core measurement domains (not all subcategories).
Results: 649 (30.3%) SMART DAPPER participants preferred treatment via mHealth, rather than in person. The most cited rationales for choosing mHealth were affordability (18.5%) (eg, no transportation cost) and convenience (12.9%). On multivariate analysis, compared with those who preferred in-person treatment, participants who chose mHealth were younger and had higher constraints on receiving in-person treatment, including transport time 1.004 (1.00, 1.007) and finances 0.757 (0.612, 0.936). Higher PTSD symptoms 0.527 (0.395, 0.702) and higher disability 0.741 (0.559, 0.982) were associated with preference for in-person treatment.
Conclusions: To our knowledge, this is the first study of public sector mental healthcare delivered by non-specialists via mHealth for major depression and/or PTSD in Sub-Saharan Africa. Our finding that mHealth treatment is preferred by approximately one-third of participants, particularly younger individuals with barriers to in-person care, may inform future mHealth research to (1) address knowledge gaps in mental health service implementation and (2) improve mental healthcare access to evidence-based treatment.
