Condom use errors and problems: a global view
Bibliographic record
Abstract
BACKGROUND: Significantly more research attention has been devoted to the consistency of condom use, with far fewer studies investigating condom use errors and problems. The purpose of this review was to present the frequency of various condom use errors and problems reported worldwide. METHODS: A systematic literature search was conducted for peer-reviewed articles, published in English-language journals between 1995 and 2011. RESULTS: Fifty articles representing 14 countries met criteria for inclusion. The most common errors included not using condoms throughout sex, not leaving space at the tip, not squeezing air from the tip, putting the condom on upside down, not using water-based lubricants and incorrect withdrawal. Frequent problems included breakage, slippage, leakage, condom-associated erection problems, and difficulties with fit and feel. Prevalence estimates showed great variation across studies. Prevalence varied as a function of the population studied and the period assessed. CONCLUSION: Condom use errors and problems are common worldwide, occurring across a wide spectrum of populations. Although breakage and slippage were most commonly investigated, the prevalence of other condom use errors and problems found in this review were substantially higher. As a framework for understanding the role of condom errors and problems in inadequate protection, we put forward a new model: the Condom Use Experience model. This model can be used to generate testable hypotheses for future research. Addressing condom use errors and problems in research and interventions is crucial to closing the gap between the perfect use and typical use of condoms.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.011 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.013 | 0.013 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".