Associations between Drug Use and Sexual Risk Behaviours among Men Who Have Sex with Men in Japan: Results from the Cross-Sectional LASH Study
Bibliographic record
Abstract
This study assessed drug use patterns among men who have sex with men (MSM) in Japan, and evaluated their potential associations with sexual risk behaviours. Between September and October 2016, study subjects were recruited through a cross-sectional survey (LASH: Love Life and Sexual Health) using a geosocial networking application for MSM. Of the participants, 25.4% (1756/6921) reported ever having used drugs, and 11.3% (780/6921) reported having done so in the past six months. Those who used drugs were more likely to have greater knowledge of HIV/sexually transmitted infections (STIs). Drug use in the past six months was independently associated with each of the following sexual risk behaviours in the same period: (i) six or more sexual partners (adjusted odds ratio [aOR] = 2.70, 95% confidence interval [CI]: 2.30-3.17); (ii) condomless anal intercourse (aOR = 2.88, 95% CI: 2.43-3.42); (iii) group sex (aOR = 2.60, 95% CI: 2.22-3.05); and (iv) sex work (aOR = 2.30, 95% CI: 1.67-3.16). These results suggest that MSM in Japan who use drugs are more likely to report sexual risk behaviours, while also having greater knowledge of HIV/STIs. Supporting MSM to minimise the harm from drug use may be helpful in reducing HIV transmission among this priority population.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".