HIV Risk Profiles Among HIV-Positive, Methamphetamine-Using Men Who Have Sex with Both Men and Women
Bibliographic record
Abstract
This study examined demographic characteristics, sexual risk behaviors, sexual beliefs, and substance use patterns in HIV-positive, methamphetamine-using men who have sex with both men and women (MSMW) (n = 50) as compared to men who have sex with men only (MSM) (n = 150). Separate logistic regressions were conducted to predict group membership. In the final model, of 12 variables, eight were independently associated with group membership. Factors independently associated with MSMW were acquiring HIV through injection drug use, being an injection drug user, using hallucinogens, using crack, being less likely to have sex at a bathhouse, being less likely to be the receptive partner when high on methamphetamine, having greater intentions to use condoms for oral sex, and having more negative attitudes about HIV disclosure. These results suggest that, among HIV-positive methamphetamine users, MSMW differ significantly from MSM in terms of their HIV risk behaviors. Studies of gay men and HIV often also include bisexual men, grouping them all together as MSM, which may obscure important differences between MSMW and MSM. It is important that future studies consider MSM and MSMW separately in order to expand our knowledge about differential HIV prevention needs for both groups. This study showed that there were important differences in primary and secondary prevention needs of MSM and MSMW. These findings have implications for both primary and secondary HIV prevention among these high-risk populations.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".