The Influence of Partner Type and Risk Status on the Sexual Behavior of Young Men Who Have Sex With Men Living With HIV/AIDS
Bibliographic record
Abstract
OBJECTIVES: The influence of partner type and risk status on the unprotected sexual behavior of young men living with HIV (YMLH) who have sex with men is examined. METHODS: Sexual behavior and sexual partner characteristics of 217 YMLH recruited from adolescent care clinics in 4 AIDS epicenters (Los Angeles, San Francisco, New York, and Miami) were assessed. YMLH were categorized by sexual behavior pattern, and sexual partners were classified by type and risk status. Generalized linear modeling employing overdispersed Poisson distribution was used to analyze the effect of partner type and partner risk status on unprotected sex acts. RESULTS: Most YMLH (62%) reported multiple partners, 26% reported 1 sexual partner, and 12% reported abstinence in the past 3 months. Approximately 34% of polygamous and 28% of monogamous youth engaged in unprotected sex. Monogamous youth were most likely to have unprotected sex with HIV-positive partners. Polygamous youth were most likely to have unprotected sex with HIV-positive partners, irrespective of whether the partner was regular or casual. For polygamous YMLH, unprotected sex did not differ among single-time/new partners with different risk levels. CONCLUSIONS: Partner characteristics influence the condom use behavior of YMLH. YMLH make decisions regarding condom use based on perception of their partner's risk. Preventive interventions must include skills for acquiring accurate information about partner risk status and education regarding the health risks of unprotected sex with HIV seroconcordant partners.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".