'I thought we would be cherished and safe here': understanding the multi-faceted nature of mental health among Arab immigrants/refugees in Ontario, Canada- the CAN-HEAL study.

PURPOSE:Mental health (MH) is a critical public health issue. Arab immigrants/refugees (AIR) may be at high risk for MH problems owing to various unique stressors, such as post-September/11 demonization. Despite the growing AIR population in Western countries, there is a lack of AIR-MH research in these nations. The CAN-HEAL study examined MH experiences and needs among AIR in Ontario, Canada. METHODS:This study employed a cooperative community-based participatory research and integrated knowledge translation approach. The study used photovoice, qualitative interviews and a questionnaire survey. Sixty socio-demographically diverse AIR adults partook in this study. The research was informed by the "social determinants of health" framework and the "years since immigration effect" (YSIE) theory. RESULTS:The term "mental health" was deemed offensive for participants aged > 30 years. Participants proposed other culturally-appropriate words including "well-being" and "emotional state". The prevalence of poor mental well-being in the sample was alarming (55%). Of first-generation immigrant participants, 86.8% reported negative changes in MH since migration. The negative changes are not straightforward; they are complex and dynamic, and mainly related to micro/macro-aggression, cross-cultural pressures, dissatisfaction with the health and social care system, and poor living conditions. Intersections between different socio-demographic factors (e.g., gender, length of residency, income, parenthood, religion) amplified the negative changes in MH and exacerbated inequities. CONCLUSIONS:MH needs among AIR are distinct and intersectionality aggravated inequities. Culturally and structurally competent healthcare and structural/policy reformation are required to tackle MH inequities. This can be fulfilled through intersectoral cooperation and including AIR in decision-making.