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Public Health Interventions to Address Housing and Mental Health amongst Migrants from Culturally and Linguistically Diverse Backgrounds Living in High-Income Countries: A Scoping Review.

Gemma CrawfordElizabeth ConnorKahlia McCauslandKarina ReevesKrysten Blackford
Published in: International journal of environmental research and public health (2022)
Migrants from culturally and linguistically diverse (CaLD) backgrounds experience factors that may increase health inequities related to a range of determinants of health including housing and mental health. However, the intersection between mental health and housing for migrants is poorly understood. A scoping review searched four academic databases for concepts related to cultural and linguistic diversity, housing conditions, and public health interventions to address homelessness. A total of 49 articles were included and seven key themes identified: housing provision; mental health intersections and interventions; complexity and needs beyond housing; substance use; service provider and policy issues; the role of cultural and linguistic diversity; and consumer experience. The intersection of ethnicity with other social determinants of health and housing was highlighted though there were limited interventions tailored for migrants. Studies generally pointed to the positive impacts of Housing First. Other sub-themes emerged: social connection and community; shame, stigma, and discrimination; health and support requirements; and employment, financial assistance, and income. Consumer choice was identified as vital, along with the need for systemic anti-racism work and interventions. To support secure housing for migrants and mitigate mental health impacts, closer attention is required towards migration factors along with broader, tailored services complementing housing provision.
Keyphrases
  • mental health
  • mental illness
  • public health
  • physical activity
  • healthcare
  • health information
  • primary care
  • machine learning
  • palliative care
  • deep learning