Two heads are better than one: the association between condom decision-making and condom use errors and problems
Bibliographic record
Abstract
OBJECTIVES: This exploratory study compared the frequency of condom use errors and problems between men reporting that condom use for penile-vaginal sex was a mutual decision compared with men making the decision unilaterally. METHODS: Nearly 2000 people completed a web-based questionnaire. A sub-sample of 660 men reporting that they last used a condom for penile-vaginal sex (within the past three months) was analysed. Nine condom use errors/problems were assessed. Multivariate analyses controlled for men's age, marital status, and level of experience using condoms. RESULTS: Men's unilateral decision-making was associated with increased odds of removing condoms before sex ended (adjusted odds ratio (AOR) 2.51, p = 0.002), breakage (AOR 3.90, p = 0.037), and slippage during withdrawal (AOR 2.04, p = 0.019). Men's self-reported level of experience using condoms was significantly associated with seven out of nine errors/problems, with those indicating less experience consistently reporting more errors/problems. CONCLUSIONS: Findings suggest that female involvement in the decision to use condoms for penile-vaginal sex may be partly protective against some condom errors/problems. Men's self-reported level of experience using condoms may be a useful indicator of the need for education designed to promote the correct use of condoms. Education programmes may benefit men by urging them to involve their female partner in condom use decisions.
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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 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".