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Record W1967676965 · doi:10.1176/appi.ps.201200257

Factors Influencing Service Use Among Homeless Youths With Co-Occurring Disorders

2013· article· en· W1967676965 on OpenAlexafffund
Nicole Kozloff, Amy Cheung, Lori E. Ross, Heather Winer, Diana Ierfino, Heather L. Bullock, Kathryn Bennett

Bibliographic record

VenuePsychiatric Services · 2013
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsCentre for Addiction and Mental Health
FundersCanadian Institutes of Health Research
KeywordsThematic analysisPsychological interventionPsychologySubstance useStigma (botany)Clinical psychologyPopulationEmotional and behavioral disordersHarm reductionService (business)Focus groupHarmMental healthMedicinePsychiatryQualitative researchPublic healthNursingEnvironmental healthSocial psychology

Abstract

fetched live from OpenAlex

OBJECTIVE: Given high rates of co-occurring mental and substance use disorders among homeless youths and poorly understood facilitators of and barriers to service use, this study explored factors influencing service use among homeless youths with co-occurring disorders. METHODS: Focus groups were conducted with 23 youths age 18 to 26 with co-occurring disorders. Group discussion was audio-recorded and transcribed verbatim, and transcripts were examined with thematic content analysis. RESULTS: The factors identified as influencing service use were grouped into three broad categories: individual (motivation, support, and therapeutic relationship), program (flexibility and comprehensiveness of services and availability of harm reduction services), and systemic (stigma and accessibility). CONCLUSIONS: Multilevel factors appear to influence service use among homeless youths with co-occurring disorders. Given the lack of evidence to support specific treatments in this population, these findings may be used to guide the development of thoughtfully designed interventions to engage homeless youths with co-occurring disorders.

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)0.001
metaresearch head score (Gemma)0.005
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.033
GPT teacher head0.343
Teacher spread0.310 · 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
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

Citations50
Published2013
Admission routes2
Has abstractyes

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