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Record W2325617135 · doi:10.1515/ijamh-2013-0323

Gender differences in early trauma and high-risk behaviors among street-entrenched youth in British Columbia

2014· article· en· W2325617135 on OpenAlexaffabout
Sahoo Saddichha, Iris Torchalla, Michael Krausz

Bibliographic record

VenueInternational Journal of Adolescent Medicine and Health · 2014
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsCentre for Advancing Health OutcomesUniversity of British Columbia
Fundersnot available
KeywordsCannabisPsychiatryMental healthSubstance abusePopulationMedicinePsychologyAddictionClinical psychologyDemographyEnvironmental health

Abstract

fetched live from OpenAlex

OBJECTIVE: This work aimed to evaluate gender differences among the street-entrenched youth in British Columbia in terms of their demographics, experiences of childhood maltreatment, mental health issues, and substance use behaviors. MATERIALS AND METHODS: Data were derived from the BC Health of the Homeless Study (BCHOHS), carried out in three cities in British Columbia, Canada. Measures included socio-demographic information, the Maudsley Addiction Profile (MAP), the Childhood Trauma Questionnaire (CTQ), the Mini International Neuropsychiatric Interview (MINI) Plus and the National Survey of Homeless Assistance Providers and Clients (NSHAPC)-Health Chapter. RESULTS: Youth constituted 16.5% (n=82) of the homeless population. Females (55%) outnumbered males and engaged in survival sex more frequently (17.8%; p=0.03). Males had greater substance abuse of alcohol (81.1%) and cannabis (89.2%). Depression (p=0.02) and psychosis (p=0.05) were more common among females, while panic disorder was more common among males (p=0.04). Rates of childhood trauma were similar across genders. CONCLUSION: Our findings reflect trends among youth where illicit drug use may be similar among genders while males may report increased alcohol and cannabis use, possibly as a means to self medicate their panic-related symptoms. In any case, this population of street entrenched-youth frequently experiences several significant problems ranging from childhood abuse to high rates of substance abuse and mental illnesses.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.179
Threshold uncertainty score0.359

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
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 head0.070
GPT teacher head0.385
Teacher spread0.315 · 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

Citations1
Published2014
Admission routes2
Has abstractyes

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