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Females Experiencing Sexual and Drug Vulnerabilities Are at Elevated Risk for HIV Infection Among Youth Who Use Injection Drugs

2002· article· en· W2332903548 on OpenAlexaffabout
Cari L. Miller, Patricia M. Spittal, Nancy Laliberté, Kathy Li, Mark Tyndall, Michael V. O’Shaughnessy, Martin T. Schechter

Bibliographic record

VenueJAIDS Journal of Acquired Immune Deficiency Syndromes · 2002
Typearticle
Languageen
FieldMedicine
TopicHIV, Drug Use, Sexual Risk
Canadian institutionsAIDS Vancouver
Fundersnot available
KeywordsHuman immunodeficiency virus (HIV)DrugMedicineInjection drug useInfection riskInternal medicineImmunologyPharmacologyDrug injectionIntensive care medicine

Abstract

fetched live from OpenAlex

OBJECTIVES: To compare sociodemographic, drug-related, and sexual risk variables between young (13-24 years of age) and older (> or =25 years of age) injection drug users (IDUs); and to determine HIV prevalence and associated risk factors for HIV infection among young IDUs. METHODS: Data were collected through the Vancouver Injection Drug Users Study (VIDUS). To date, over 1400 Vancouver area IDUs have been enrolled and observed during follow-up. Sociodemographic, drug-related, and sexual risk variables were compared between younger and older IDUs using nonparametric methods. Mantel-Haenszel and logistic regression methods were used to compare HIV-positive and HIV-negative female youth. RESULTS: Younger injectors (N = 232) were more likely to be female; work in the sex trade; report condom use; inject heroin daily; smoke crack cocaine daily; and need help injecting. HIV prevalence at baseline among the youth was 10%. HIV prevalence was associated with female gender; history of sexual abuse; engaging in survival sex; injecting heroin daily; injecting speedballs (a mixture of heroin and cocaine) daily; and having numerous lifetime sexual partners. CONCLUSION: Our data show that HIV positivity among young IDUs is concentrated among females engaged in dual sexual and drug-related risk exposure categories. Over half the HIV-positive youth were Aboriginal (a classification used by the federal government in Canada to include native peoples of all ethnic groups). Targeted interventions that take into account sexual and drug risk for young female and Aboriginal peoples are urgently needed.

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)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.161
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.049
GPT teacher head0.291
Teacher spread0.242 · 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 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

Citations72
Published2002
Admission routes2
Has abstractyes

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