Carol E Adair1, David L Streiner2,3, Ryan Barnhart4, Brianna Kopp5, Scott Veldhuizen2, Michelle Patterson6, Tim Aubry7, Jennifer Lavoie8, Jitender Sareen9, Stefanie Renée LeBlanc10, Paula Goering3,4. 1. 1 Departments of Psychiatry and Community Health Sciences, University of Calgary, Calgary, Alberta. 2. 2 Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, Ontario. 3. 3 Department of Psychiatry, University of Toronto, Toronto, Ontario. 4. 4 Centre for Addiction and Mental Health, York University, Toronto, Ontario. 5. 5 Mental Health Commission of Canada, Calgary, Alberta. 6. 6 Faculty of Health Sciences, Simon Fraser University, Vancouver, British Columbia. 7. 7 School of Psychology and Centre for Research on Educational and Community Services, University of Ottawa, Ottawa, Ontario. 8. 8 Department of Criminology, Wilfrid Laurier University, Brantford, Ontario. 9. 9 Departments of Psychiatry, Psychology and Community Health Sciences, University of Manitoba, Winnipeg, Manitoba. 10. 10 Centre de recherche et de développement en éducation, Université de Moncton, Moncton, New Brunswick.
Abstract
PURPOSE:Housing First (HF) has been shown to improve housing stability, on average, for formerly homeless adults with mental illness. However, little is known about patterns of change and characteristics that predict different outcome trajectories over time. This article reports on latent trajectories of housing stability among 2140 participants (84% followed 24 months) of a multisite randomised controlled trial of HF. METHODS: Data were analyzed using generalised growth mixture modeling for the total cohort. Predictor variables were chosen based on the original program logic model and detailed reviews of other qualitative and quantitative findings. Treatment group assignment and level of need at baseline were included in the model. RESULTS: In total, 73% of HF participants and 43% of treatment-as-usual (TAU) participants were in stable housing after 24 months of follow-up. Six trajectories of housing stability were identified for each of the HF and TAU groups. Variables that distinguished different trajectories included gender, age, prior month income, Aboriginal status, total time homeless, previous hospitalizations, overall health, psychiatric symptoms, and comorbidity, while others such as education, diagnosis, and substance use problems did not. CONCLUSION: While the observed patterns and their predictors are of interest for further research and general service planning, no set of variables is yet known that can accurately predict the likelihood of particular individuals benefiting from HF programs at the outset.
RCT Entities:
PURPOSE: Housing First (HF) has been shown to improve housing stability, on average, for formerly homeless adults with mental illness. However, little is known about patterns of change and characteristics that predict different outcome trajectories over time. This article reports on latent trajectories of housing stability among 2140 participants (84% followed 24 months) of a multisite randomised controlled trial of HF. METHODS: Data were analyzed using generalised growth mixture modeling for the total cohort. Predictor variables were chosen based on the original program logic model and detailed reviews of other qualitative and quantitative findings. Treatment group assignment and level of need at baseline were included in the model. RESULTS: In total, 73% of HF participants and 43% of treatment-as-usual (TAU) participants were in stable housing after 24 months of follow-up. Six trajectories of housing stability were identified for each of the HF and TAU groups. Variables that distinguished different trajectories included gender, age, prior month income, Aboriginal status, total time homeless, previous hospitalizations, overall health, psychiatric symptoms, and comorbidity, while others such as education, diagnosis, and substance use problems did not. CONCLUSION: While the observed patterns and their predictors are of interest for further research and general service planning, no set of variables is yet known that can accurately predict the likelihood of particular individuals benefiting from HF programs at the outset.
Authors: Stefan G Kertesz; Mary Jo Larson; Nicholas J Horton; Michael Winter; Richard Saitz; Jeffrey H Samet Journal: Med Care Date: 2005-06 Impact factor: 2.983
Authors: Tim Aubry; Paula Goering; Scott Veldhuizen; Carol E Adair; Jimmy Bourque; Jino Distasio; Eric Latimer; Vicky Stergiopoulos; Julian Somers; David L Streiner; Sam Tsemberis Journal: Psychiatr Serv Date: 2015-12-01 Impact factor: 3.084
Authors: James Lachaud; Cilia Mejia-Lancheros; Michael Liu; Ri Wang; Rosane Nisenbaum; Vicky Stergiopoulos; Stephen W Hwang; Patricia O'Campo Journal: Front Nutr Date: 2021-05-12