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Record W2145419585 · doi:10.1186/1471-2458-12-787

Ending homelessness among people with mental illness: the At Home/Chez Soi randomized trial of a Housing First intervention in Toronto

2012· article· en· W2145419585 on OpenAlexafffundabout
Stephen W. Hwang, Vicky Stergiopoulos, Patricia O’Campo, Agnes Gozdzik

Bibliographic record

VenueBMC Public Health · 2012
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsPublic Health OntarioUniversity of TorontoSt. Michael's Hospital
FundersHealth CanadaMental Health Commission
KeywordsMental healthMedicinePsychological interventionAssertive community treatmentRandomized controlled trialHousing FirstReferralMental illnessIntervention (counseling)BiostatisticsOutreachSupportive housingService providerGerontologyPublic healthFamily medicineNursingPsychiatryService (business)

Abstract

fetched live from OpenAlex

BACKGROUND: The At Home/Chez Soi (AH/CS) Project is a randomized controlled trial of a Housing First intervention to meet the needs of homeless individuals with mental illness in five cities across Canada. The objectives of this paper are to examine the approach to participant recruitment and community engagement at the Toronto site of the AH/CS Project, and to describe the baseline demographics of participants in Toronto. METHODS: Homeless individuals (n = 575) with either high needs (n = 197) or moderate needs (n = 378) for mental health support were recruited through service providers in the city of Toronto. Participants were randomized to Housing First interventions or Treatment as Usual (control) groups. Housing First interventions were offered at two different mental health service delivery levels: Assertive Community Treatment for high needs participants and Intensive Case Management for moderate needs participants. Demographic data were collected via quantitative questionnaires at baseline interviews. RESULTS: The effectiveness of the recruitment strategy was influenced by a carefully designed referral system, targeted recruitment of specific groups, and an extensive network of pre-existing services. Community members, potential participants, service providers, and other stakeholders were engaged through active outreach and information sessions. Challenges related to the need for different sectors to work together were resolved through team building strategies. Randomization produced similar demographic, mental health, cognitive and functional impairment characteristics in the intervention and control groups for both the high needs and moderate needs groups. The majority of participants were male (69%), aged >40 years (53%), single/never married (69%), without dependent children (71%), born in Canada (54%), and non-white (64%). Many participants had substance dependence (38%), psychotic disorder (37%), major depressive episode (36%), alcohol dependence (29%), post-traumatic stress disorder (PTSD) (23%), and mood disorder with psychotic features (21%). More than two-thirds of the participants (65%) indicated some level of suicidality. CONCLUSIONS: Recruitment at the Toronto site of AH/CS project produced a sample of participants that reflects the diverse demographics of the target population. This study will provide much needed data on how to best address the issue of homelessness and mental illness in Canada.

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.700
Threshold uncertainty score0.596

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.047
GPT teacher head0.386
Teacher spread0.339 · 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 designRandomized trial
Domainnot available
GenreEmpirical

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

Citations102
Published2012
Admission routes3
Has abstractyes

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