Substance Use Patterns of Gay and Bisexual Men in the Momentum Health Study
Bibliographic record
Abstract
Research with male sexual minorities frequently combines gay and bisexual men as Men Who Have Sex with Men or Gay and Bisexual Men. When analyzed separately, bisexual men consistently feature negative health differentials, exemplified by higher substance use levels. This interpretation is not clear-cut because studies may combine bisexual men and women, use different dimensions of sexual orientation to define bisexuality, and/or not consider number of sexual partners as a possible confounding factor. This study conducted separate bivariate and multivariate analyses comparing gay to bisexual Momentum Study participants based on self-identity, sexual attraction, and sexual behavior, while controlling for number of sexual partners and sociodemographic, psychosocial, and sexual behavior measures. The study hypothesized that, regardless of definition, bisexual men feature higher substance use levels compared to gay men. Bivariate analyses revealed significantly higher ( p < .05) use among bisexual men for multiple substances in all samples. Nonprescription stimulants and heroin were significant in all multivariate logistic regression models. In contrast, all bisexual samples reported lower use of erectile dysfunction drugs and poppers, substances associated with anal sex among gay men. Subsequent analysis linked these results to lower levels of anal sex in all bisexual samples. Bivariate analyses also revealed that bisexual men featured significantly lower educational levels, annual incomes, and Social Support Scales scores and higher Anxiety and Depression Sub-Scale Scores. In summary, findings revealed bisexual men's distinctive substance use, sexual behavior, psychosocial, and sociodemographic profiles, and are important for tailoring specific health programs for bisexual 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 | 0.001 |
| Science and technology studies | 0.001 | 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".