Does age matter? Sexual event-level analysis of age-disparate sexual partners among gay, bisexual and other men who have sex with men (GBM) in Vancouver, Canada
Bibliographic record
Abstract
BACKGROUND: To determine factors associated with age-disparate sexual partners among Vancouver gay, bisexual and other men who have sex with men (GBM). METHODS: Sexually active GBM aged ≥16 years were recruited from February 2012 to February 2014. Participants self-completed a questionnaire on demographics, attitudes and sexual behaviour and substance use at last sexual event with five most recent partners. Two generalised linear mixed models identified factors associated with: (1) 'same-age' (referent), 'younger' or 'much-younger' and (2) 'same-age' (referent), 'older' or 'much-older' partners. Statistical interactions between age and HIV status were tested. RESULTS: Participants (n=719) were predominantly gay (85.1%), White (75.0%), HIV-negative/unknown status (72.9%) with median age of 33 years (Q1,Q3: 26,47). A minority of sexual events were reported with much-older/much-younger partners (13.7%). In the multivariable models, GBM reporting older partners were more likely to be Asian or Latino, have greater Escape Motivation scores, report their partner used erectile dysfunction drugs (EDDs) and have received something for sex; compared with condom-protected insertive anal sex, participants with older partners were more likely to report condomless insertive anal sex with a serodiscordant or unknown status partner or no insertive anal sex. GBM reporting older partners were less likely to be bisexual-identified, have given something for sex and report event-level alcohol and EDD use. GBM reporting younger partners were more likely to have annual incomes >$30 000 and have met their partner online. As per significant statistical interactions, age-disparate relations were more common for younger HIV-positive and older HIV-negative GBM. CONCLUSIONS: Differences among age-disparate partners highlight important targets for health promotion and future research.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".