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Record W2338042987 · doi:10.1177/070674371506001101

Putting Housing First: The Evidence and Impact

2015· editorial· en· W2338042987 on OpenAlexaffvenueabout
Paula Goering, David L. Streiner

Bibliographic record

VenueThe Canadian Journal of Psychiatry · 2015
Typeeditorial
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsMcMaster UniversityUniversity of TorontoCentre for Addiction and Mental Health
FundersMental Health Commission
KeywordsPsychologyMedicine

Abstract

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Until recently, there was little empirical evidence regarding the most effective intervention for a very vulnerable population, adults who are homeless with a mental illness. Many programs existed, but they were supported mainly by descriptive studies or nonexperimental designs. This began to change about 15 years ago, following the introduction of a novel and somewhat controversial program, Pathways to HF.1 Unlike more traditional housing approaches that first require clients to engage in treatment and stop abusing drugs and alcohol, the HF approach, true to its name, offers people who are homeless their own scattered-site apartments, without any preconditions. Since that time, there have been numerous RCTs demonstrating its effectiveness and cost-effectiveness. The latest, and by far the largest, trial was the AH–CS study, funded by Health Canada through the Mental Health Commission of Canada.2 This study involved 2148 people in 5 cities across Canada, randomized to receive either HF plus either assertive community treatment (for those with high needs) or intensive case management (for those with moderate needs), rather than TAU. In this issue of the journal, 2 articles3,4 review the literature regarding the HF approach. The first paper, by Aubry et al,3 defines the original program model and summarizes the findings about implementation and effectiveness, with an emphasis on those from the AH–CS project. Despite dire warnings by an external reviewer at the start of that study that very large projects rarely tap the richness of their data or publish enough papers to justify their expense, AH–CS has already resulted in 80 papers (and counting). Consequently, it is useful to have one article summarizing the major findings. The second paper, by Ly and Latimer,4 is both narrower in scope, focusing only on the economic findings, and broader, in that it marshals the results from other studies of the more generic HF approach. There are numerous lessons to be learned from these reviews. The first, and most important, is that HF is very successful, most especially regarding the primary outcome of enabling people with a mental illness who are homeless to find and maintain stable housing for an extended period of time. The second conclusion is the necessity to use an RCT design in evaluating efficacy and effectiveness of complex interventions. Ly and Latimer’s review found that studies that used a pre–post design reported an overall decrease in costs with HF, whereas RCTs showed a net increase in costs, except for people who were the highest users of services. Other papers coming out of the HF–CS study have shown that, while those in the intervention group demonstrated improvements, in areas such as mental health symptoms and substance abuse problems, this was paralleled by equivalent gains in the TAU group.5,6 Not having a control group would have exaggerated the extent to which HF has a beneficial result. A third conclusion is that the impact of evidence on policy is enhanced by using rigorous designs that include economic results and are combined with participatory approaches to knowledge translation. The remarkable receptiveness of the Canadian government to the findings of the AH–CS study that are described in the Aubry et al3 review were achieved through a combination of good science and an extensive communication strategy that addressed the cost offsets, a central preoccupation of decision makers. A final lesson relates to the impact of evidence on practice, which is enhanced by a multi-site, mixed methods approach that included rich qualitative data about the experience of the providers and participants in various settings. The technical assistance and training efforts that are under way across Canada rely heavily on the credibility and expertise of people who were actively involved in the demonstration project. The impact of evidence about implementation and outcomes on policy and practice always involves myriad factors beyond the results themselves.7 Still, the quality and quantity of the research matters. These review articles3,4 provide a helpful summary of the existing evidence to inform decisions about how best to support homeless adults with a mental illness to find a home.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.737
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0000.000

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 head0.063
GPT teacher head0.423
Teacher spread0.360 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEditorial

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

Citations19
Published2015
Admission routes3
Has abstractyes

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