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Record W2112239720 · doi:10.3844/ajidsp.2005.50.54

Factors Associated with Syringe Sharing Among Users of a Medically Supervised Safer Injecting Facility

2005· article· en· W2112239720 on OpenAlexaboutno aff
Evan Wood, Mark Tyndall, Jo‐Anne Stoltz, Will Small, Elisa Lloyd-Smit, Ruth Zhang, Julio Montaner, Thomas Kerr

Bibliographic record

VenueAmerican Journal of Infectious Diseases · 2005
Typearticle
Languageen
FieldMedicine
TopicHIV, Drug Use, Sexual Risk
Canadian institutionsnot available
Fundersnot available
KeywordsSAFERSyringeMedicineEnvironmental scienceComputer scienceComputer security

Abstract

fetched live from OpenAlex

Vancouver, Canada recently opened a medically supervised safer injecting facility (SIF) in an effort to reduce HIV and overdose risk and public injection drug use. We sought to examine factors associated with syringe sharing among SIF users. SIF users were randomly recruited into a prospective cohort of SIF users known as the Scientific Evaluation of Supervised Injecting (SEOSI) cohort. We examined the prevalence and correlates of used syringe borrowing among baseline HIV-negative participants and used syringe lending among baseline HIV-infected participants. Between 22 March 2004 and 22 October 2004, 479 baseline HIV-negative subjects (48 [10%] syringe borrowing events) and 103 baseline HIV-infected participants (17 [16.5%] syringe lending events) were recruited into the cohort. For baseline HIV negative participants, syringe borrowing was positively associated with public drug use (p<0.001) and requiring help injecting (p=0.001), whereas exclusive SIF use was inversely associated with syringe sharing (p=0.019). For baseline HIV-infected participants, syringe lending was positively associated with daily cocaine injection (p=0.022) and shooting gallery use (p=0.007). Although ongoing injection-related HIV risk behavior was reported among some SIF users, rates of syringe sharing were substantially lower than the rate observed previously in this community and it is noteworthy that exclusive SIF use was associated with reduced syringe sharing.

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)0.000
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation 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 score0.017
Threshold uncertainty score0.845

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.030
GPT teacher head0.300
Teacher spread0.269 · 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.

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

Citations47
Published2005
Admission routes1
Has abstractyes

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