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Title: People with serious mental illness living in supported accommodation : a meta-analytic and secondary data analysis study
Author: Harrison, Michele
ISNI:       0000 0004 7966 620X
Awarding Body: Queen Margaret University, Edinburgh
Current Institution: Queen Margaret University
Date of Award: 2019
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People with serious mental illness experience significant difficulties related to social, occupational and cognitive functioning. A key form of intervention for these individuals is supported accommodation, with the aim of providing opportunities to live in the community, develop independence and increase social integration. Supported accommodation ranges from help being available 24 hours a day, to having support provided at home one to two times a week. There has been increasing interest in understanding if this type of intervention not only supports clinical outcomes - that is, symptoms and levels of risk - but also outcomes important to people's recovery, including wellbeing, satisfaction with life, living conditions and social functioning. The aim of the research was to investigate supported accommodation for people with serious mental illness. The first objective was to consider outcomes for individuals, including quality of life issues such as wellbeing, satisfaction with living conditions and social functioning. The second objective was to understand what personal and environmental factors determined the placement of individuals in different types of supported accommodation. This study followed two stages. First, a systematic review and meta-analysis of outcomes for people with serious mental illness living in three types of supported accommodation was conducted to address the first research objective. This identified that outcomes related to wellbeing, satisfaction with living conditions and social functioning improved for people as they moved into accommodation with less support. The second stage used secondary data analysis of two national datasets: the Scottish Morbidity Record - Scottish Mental Health and Inpatient Day Case Section (SMR04); and the Scottish Government Social Care Survey (SGSCS). This phase primarily addressed the second research objective. Logistic regression modelling identified the contextual factors that predict being placed in supported housing and floating outreach accommodation from high support accommodation. For placement in supported housing compared to high support accommodation, predictors were age, a diagnosis of schizophrenia, length of stay and a formal admission to hospital. For placement in floating outreach compared to high support, formal admission to hospital was a predictor. There was limited data available which would address outcomes associated with different placement types. However, predictors of people's needs were identified. A diagnosis of schizophrenia predicted having a healthcare need; length of stay predicted having a social, educational and recreational need; and individuals were more likely to have needs identified if support was provided by the local authority. The results suggested that people with serious mental illness achieved greater wellbeing, satisfaction with living conditions and social functioning in less restrictive accommodation. Predictors of accommodation placement were prolonged involvement with mental health services, a diagnosis of schizophrenia and extended lengths of stay in high support. Irrespective of placement type, social, educational, recreational and healthcare needs are important for this client group. The study highlights that service user perspectives on outcomes in mental health services are not routinely identified in national datasets. For future research, it is recommended that personal and environmental factors are explored within supported accommodation environments to understand how these affect the recovery of people with serious mental illness, and to assess outcomes associated with different supported accommodation types.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Prof.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available