Agreement between gay, bisexual and other men who have sex with men’s period prevalence and event-level recall of sexual behaviour: an observational respondent-driven sampling study
Bibliographic record
Abstract
Background Agreement between sexual behaviour recall measures among gay, bisexual and other men who have sex with men (GBM) in Vancouver, Canada was examined. METHODS: Study participants were sexually active GBM aged ≥16 years recruited via respondent-driving sampling (RDS). Participants completed a computer-assisted self-interview survey, including individual-level period prevalence (last 6 months) and sexual event-level (last sex with each of the five most recent partners) measures. RDS-weighted kappa statistics assessed the agreement between these types of data across five different sexual risk outcomes, stratified by self-identified HIV status and other demographic factors (age, education, race/ethnicity). RESULTS: Of 719 participants, 195 (RDS-weighted 23.4%) were HIV-positive. For HIV-negative GBM (n=524, RDS-weighted 76.6%), there were moderate agreements between period prevalence and event-level data for any anal intercourse (AI), any condomless AI and any fisting, but weak agreement for any discordant/unknown AI and any sex toy use. For HIV-positive GBM, there was moderate agreement for any AI, any condomless AI, any discordant/unknown AI and any fisting; there was weak agreement for any sex toy use. Agreement between measurement types was generally higher for GBM who were living with HIV, who were older and who completed secondary school; there was little difference in agreement levels by race/ethnicity. CONCLUSIONS: We observed moderate agreement between sexual behaviour recall through event-level and period prevalence questions. Each method had differential advantages and ideal circumstances for use, which should be guided by one's research question and outcome measure of interest.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".