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Record W2979967739 · doi:10.20381/ruor-23839

The Role of Services for Homeless and Housed People with Mental Illness: The Relationship Between Service Use and Housing Stability, Recovery, and Capabilities

2019· dissertation· en· W2979967739 on OpenAlexfundaboutno aff
Nicholas Kerman

Bibliographic record

VenueuO Research (University of Ottawa) · 2019
Typedissertation
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsnot available
FundersMental Health Research Canada
KeywordsMental illnessHousing FirstPsychologyService (business)PsychiatryGerontologyMental healthMedicineBusinessMarketing

Abstract

fetched live from OpenAlex

People with mental illness and histories of homelessness represent a vulnerable and marginalized population for whom a wide range of health, social, and community services have been developed. Despite the array of services, their role in the lives of currently and formerly homeless people with mental illness is not fully understood. Three studies were conducted that addressed two research questions: [1] How do patterns of service use differ during transitions from homelessness to housing compared to those from housing to homelessness among people with mental illness? and [2] What is role of services in enhancing the lives of housed and homeless people with mental illness? The first research question was addressed in Study 1, which involved secondary data analysis from a multisite randomized controlled trial of Housing First in Canada known as the At Home/Chez Soi demonstration project. The study explored how service use patterns over 24 months differed among people who achieved housing stability compared to those who remained unstably housed or re-experienced housing instability during the second year of the study. Findings showed that, as homeless people with mental illness transition into stable housing, their service use patterns change, with less time being spent in psychiatric hospitals, prison, and emergency shelters. Housing First minimally affected the changes in service use patterns, indicating that housing stability is the key factor in producing the changes as people transition out of homelessness. Study 2 also used data from the At Home/Chez Soi demonstration project to examine predictors of recovery among homeless people with mental illness at baseline and 24 months. Findings showed that health and community factors most strongly predicted mental health recovery at baseline. The housing and service use block of predictors was also significantly associated with most components of recovery, though the effect sizes were small. At 24 months, the model, which included receipt of Housing First, did not significantly predict residual changes in recovery from baseline. Study 3 of this dissertation qualitatively explored how currently and formerly homeless people with mental illness view services in their lives using two theoretical frameworks: recovery (Part 1) and the capabilities approach (Part 2). In-depth interviews were conducted with 52 participants living in Ottawa, Ontario. Participants perceived services to have a range of positive and negative impacts of their recovery and capabilities. However, the limits of service helpfulness in helping people to move forward with their lives was also highlighted. Overall, the findings of this dissertation indicate that the health, social, and community services used by homeless people with mental illness change as people become stably housed yet are limited in their impacts on recovery and capabilities. Implications for transformative change, service delivery, and future research are discussed.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.133
Threshold uncertainty score0.264

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.084
GPT teacher head0.373
Teacher spread0.289 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2019
Admission routes2
Has abstractyes

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