Condom use errors and problems: a study of high-risk young Black men residing in three Southern US cities
Bibliographic record
Abstract
The primary aim of this study was to assess self-reported frequencies of selected condom use errors and problems, using a retrospective recall period of 2 months, among young Black men attending sexually transmitted infection clinics. A secondary objective was to determine whether more errors/problems occurred among men reporting sex with multiple partners compared with those reporting one sexual partner. Data were collected in clinics treating patients with sexually transmitted infections in three Southern US cities. Men, 15-23 years of age who identified as Black/African American and reported recent (past 2 months) condom use were eligible (N = 475). Condom use errors and problems were common, with some of the most critical errors occurring for greater than one of every five young Black men, such as late application, early removal, slipping off during sex, and re-using condoms. For 8 (33.3%) of the 24 errors/problems assessed, young Black men reporting more than one sexual partner in the previous 2 months experienced more errors and problems than men reporting only one partner. The disease protective value of condoms may be sub-optimal in this population. A need exists to improve the quality of condom use among young Black men at risk of sexually transmitted infection acquisition or transmission. Intensified clinic-based intervention that helps young Black men improve the quality of their condom use behaviours is warranted.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 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".