Structural factors associated with an increased risk of HIV and sexually transmitted infection transmission among street-involved youth
Bibliographic record
Abstract
BACKGROUND: The prevalence of HIV and sexually transmitted infections (STIs) among street-involved youth greatly exceed that of the general adolescent population; however, little is known regarding the structural factors that influence disease transmission risk among this population. METHODS: Between September 2005 and October 2006, 529 street-involved youth were enroled in a prospective cohort known as the At Risk Youth Study (ARYS). We examined structural factors associated with number of sex partners using quasi-Poisson regression and consistent condom use using logistic regression. RESULTS: At baseline, 415 (78.4%) were sexually active, of whom 253 (61.0%) reported multiple sex partners and 288 (69.4%) reported inconsistent condom use in the past six months. In multivariate analysis, self-reported barriers to health services were inversely associated with consistent condom use (adjusted odds ratio [aOR] = 0.52, 95%CI: 0.25 - 1.07). Structural factors that were associated with greater numbers of sex partners included homelessness (adjusted incidence rate ratio [aIRR] = 1.54, 95%CI: 1.11 - 2.14) and having an area restriction that affects access to services (aIRR = 2.32, 95%CI: 1.28 - 4.18). Being searched or detained by the police was significant for males (aIRR = 1.36, 95%CI: 1.02 - 1.81). CONCLUSION: Although limited by its cross-sectional design, our study found several structural factors amenable to policy-level interventions independently associated with sexual risk behaviours. These findings imply that the criminalization and displacement of street-involved youth may increase the likelihood that youth will engage in sexual risk behaviours and exacerbate the negative impact of resultant health outcomes. Moreover, our findings indicate that environmental-structural interventions may help to reduce the burden of these diseases among street youth in urban settings.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".