Factors associated with transactional sex among a cohort of gay, bisexual, and other men who have sex with men in Vancouver, Canada
Bibliographic record
Abstract
Background Gay, bisexual, and other men who have sex with men (GBM) who engage in transactional sex (sex in exchange for drugs, money, or goods) experience increased risk of sexually transmitted infections (STI), including HIV. This study explored additional psychosocial and health-related factors associated with transactional sex among GBM. Methods Respondent-driven sampling was used to recruit GBM in Vancouver, Canada, from 2012 to 2015, with follow up every 6months until July2019. We examined factors associated with transactional sex using multivariable three-level mixed-effects modelling. Results Among 698 GBM, 22.1% reported ever receiving drugs, money, or goods for sex. Transactional sex was more likely to be reported by GBM who were younger (<30years) and who had lower incomes, less education, and insecure housing. GBM reporting transactional sex were more likely to report substance use (i.e. crystal methamphetamine, poppers, GHB, and non-steroid injection drugs) and higher risk sexual behaviours (i.e. more sex partners, sex party attendance, and condomless anal sex with serodifferent or unknown HIV status partners); however, they were no more likely to be living with HIV or to report a recent bacterial STI diagnosis. GBM who reported higher loneliness, anxiety, and cognitive escape were also more likely to report transactional sex. Conclusions More than one-fifth of GBM in Vancouver reported transactional sex and those who did were more likely to also experience psychosocial stressors, increased substance use, and higher risk sexual behaviours. Programs which consider the interconnections of personal, social, and structural challenges faced by GBM engaging in transactional sex are necessary to support improved mental, physical, and sexual health for these men.
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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 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".