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Factors associated with homelessness among women: a cross-sectional survey of outpatient mental health service users at The Banyan, India
Author(s) -
Preetha Krishnadas,
Lakshmi Narasimhan,
Tanya N. Joseph,
Joske Bunders,
B.J. Regeer
Publication year - 2021
Publication title -
journal of public health
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.916
H-Index - 82
eISSN - 1741-3850
pISSN - 1741-3842
DOI - 10.1093/pubmed/fdab219
Subject(s) - mental illness , psychological intervention , mental health , medicine , logistic regression , population , cross sectional study , psychiatry , disadvantage , cohort , gerontology , family medicine , demography , environmental health , sociology , pathology , political science , law
Background Homelessness has multifaceted and damaging effects on women with mental illness. This makes it imperative to identify and address the factors leading to homelessness among women with mental illness in order to inform policy on providing relevant services for this vulnerable population. Method A cross-sectional survey was conducted among 346 women in active contact with one of four outpatient clinics at The Banyan, a non-profit organization in the Indian state of Tamil Nadu. A semi-structured instrument and modified version of the List of Threatening Experiences Questionnaire was used for data collection. Multivariate logistic regression analysis was used to examine predictive variables for homelessness among women with mental illness. Result 32.65% of participants reported a history of homelessness. Less than 5 years of schooling (OR = 2.914, 95% CI = 1.027–8.269, P < 0.05) and disrupted relationships (OR = 1.807, 95% CI = 1.23–2.655, P < 0.01) were associated with a greater likelihood of women with mental illness to experience homelessness. Conclusion In the study cohort, this was explained mainly by factors rooted in gender-based disadvantage. Further practice and research are needed to develop interventions that address issues with a sociological basis to mental illness and prevent these predictive factors.

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