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Understanding perceptions of community participation in persons with severe mental illness: A mixed-methods approach
Angela K Day1, Rajiv Lalla, Tyler Frederick
1Department of Geography and Planning, University of Toronto, Toronto, ON; Centre for Addiction and Mental Health, Toronto, ON. angelakday@gmail.com.
Objectives:
This study aims to measure community participation in persons with severe mental illness (SMI) in Toronto, Ontario and outlines a methodological approach for understanding the dimensions of community participation.
Methods:
A mixed methods approach was used to define activity spaces through participatory mapping and a qualitative survey interview for participants (N = 31), selected through a stratified purposeful sampling strategy. Five neighbourhoods in Toronto were sampled in an attempt to obtain an ethnically diverse sample. Participants were interviewed over the study period and asked to draw maps indicating places that constituted their community. A qualitative interview was also administered to understand participants' perceptions of their communities. Point locations from the mapping exercise were used to measure and construct activity spaces using a mean circle approach; outlying locations were simultaneously recorded. Observed spatial patterns were then analyzed alongside the findings of the qualitative interviews.
Results:
There were no observed relationships between the number of locations reported by participants and the resultant activity space or outlier count. There were no quantitative relationships between activity space size and perceptions of community by participants. However, qualitative data revealed that a number of underlying factors (mental health status and associated stigma; relationships with friends and family; cultural background; income; and neighbourhood safety) influenced participants' activity spaces.
Conclusions:
These results highlight the ways that community participation is influenced by an interplay of determinants, all of which have implications for service delivery and population-level interventions. They also point to the importance of mixed methods approaches in spatial analysis.
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