Participatory systems modelling to improve mental health systems in Bogotá, Colombia: stakeholders’ perspectives, experiences and networks
摘要
Participatory Systems Modelling (PSM) offers an opportunity to deliver robust, contextually relevant, and suitable models for informing strategic responses to complex public health challenges. For mental health care systems, PSM benefits from multi-sectoral participants’ social and emotional capital for building consensus on priorities and policy objectives that can influence decision-making.
MethodsIn Bogotá, Colombia, we evaluated a PSM process that developed an interactive decision support tool that can inform policymaking on the selection of programs and services to mitigate social, economic, and health system drivers of youth mental health outcomes including suicidal behaviour. Using the CHaRL Framework, we explored changes in perceptions or beliefs of participants on the functionality of the (mental health) system and its drivers. Multi-sectoral participants including youth with lived experience participated in three workshops to collectively inform the building of the model. Pre-post-tests, a survey and observations of the PSM process were conducted.
ResultsThrough the participatory process, participants increased knowledge and understanding of the mental health care system, its drivers and constraints of performance for youth in Bogotá. Due to active engagement, a credible and comprehensive tool was created, reflective of the complexity of the system, and focused on what participants and evidence show are high priority interventions. Participants’ concerns around trust in the model shifted positively over the course of the workshops. Skepticism in policymakers’ capacity to use the model increased participant recognition of the need to advocate for its use.
ConclusionParticipatory processes help to overcome stakeholder hesitancy by offering an important starting point for building trust and partnership for effecting change in health systems. Consideration of participant bias at the start of the process could strength the validity and use of the results in the longer term.