Collaborative care programs for common mental illnesses in low- and middle-income countries: A multi-methods assessment of implementation context in Guatemala

Background : Collaborative care programs are effective at improving common mental illnesses (CMIs) outcomes in many low- and middle-income countries (LMICs). However, their routine implementation within primary care and communities is limited. To enhance implementation outcomes, strategies of evidence-informed interventions should be carefully tailored to context. Here, we conducted a contextual assessment to identify key community and health system factors prior to selecting implementation strategies for the first collaborative care program for Maya Indigenous People living with CMIs in Guatemala. Methods : This multi methods study combined systems thinking and implementation science tools. We used routinely collected administrative data to create behavior-over-time (BOT) graphs showcasing the number of primary care visits for CMIs in 10 municipal health districts (2018-2022). We conducted semi-structured interviews at one municipal health district following the ‘Practical, Robust Implementation and Sustainability Model’ (PRISM) framework. Participants (n=20) were Ministry of Health coordinators and providers, community leaders with CMIs, and traditional Maya providers. We conducted rapid matrix-based thematic analysis. Results : BOT graphs showed fluctuations in CMI visits, which participants linked to health system and community factors. For instance, historical advocacy for mental health and the training of primary care workers in mental health had increased the number of CMI visits, while the COVID-19 pandemic suddenly decreased CMI visits in 2020. Overall, less than 1% of primary care visits addressed CMIs, which participants indicated did not meet the large and increasing need for mental health services. Civil war violence, natural disasters and alcohol use have increased the mental health needs of young adults over time. Participants indicated that a collaborative care program could increase CMI visits, if implementation strategies address health system and community factors, such as ensuring access to psychotropic medications, and engaging Maya traditional providers in mental health services. Conclusions: By combining BOT graphs, a systems thinking tool, with PRISM we identified dynamic health system and community factors that may influence the implementation of a collaborative care program for CMIs. This is an example on how to conduct pragmatic contextual assessments with readily accessible administrative data and rapid qualitative methods prior to selecting implementation strategies of evidence-informed interventions.