Substance-specific readiness to change among sexual and gender minority men who use crystal methamphetamine
Bibliographic record
Abstract
A patient-oriented approach to addressing high levels of polysubstance use among sexual and gender minority men (SGM) who use crystal methamphetamine (CM) requires an understanding of which drugs they would like to change their use of. We examined readiness to change for 24 separate substances. Participants were SGM, aged 18+, living with Canada, who used CM in the past six months that were recruited through advertisements on socio-sexual networking applications. Frequency of use and readiness to change were descriptively analyzed and associations between frequency of use and readiness to change were assessed. Only slightly more than half (53.1%) of CM-using SGM were ready now, soon, or in the future to change substance use. Participants were most ready to change their tobacco, methamphetamine, and barbiturate use. Greater frequency of use was associated with greater readiness to change for all drugs in which daily or almost daily use was common. SGM participants reported high levels of comfort being asked about their substance use from primary care, mental health, and queer-identified health professionals. Interventions addressing multiple and specific substances are needed in health care settings serving SGM who use CM. Screening, brief interventions, and referral to treatment (SBIRT) in these settings may help identify those ready to address their substance use. Harm reduction interventions should offer supports for those not wanting to change their substance use—which includes most SGM for most of the drugs they use.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".