Why do condoms break? A study of female sex workers in Bangalore, south India
Bibliographic record
Abstract
OBJECTIVES: The purpose of the study was to obtain a better understanding of the relative importance of personal factors, male partner factors and situational factors, in determining condom breakage in a population of female sex workers (FSWs) in Bangalore. METHODS: The authors conducted a cross-sectional study that included a face-to-face interview and condom application test, with 291 randomly selected FSWs in Bangalore, India, in early 2011. RESULTS: Ninety-seven per cent of respondents noted condom use at last sex; 34% reported a condom breakage in the last month. Combining individual, situational and partner aspects of condom breakage into one logistic regression model and also controlling for client load, the authors found that partner and situational factors were dominant since the only significant predictors of condom breakage included being a paying client (adjusted odds ratio 4.61, 95% CI 1.20 to 17.58, p=0.025), the condom being too small for the penis (adjusted odds ratio 2.29, 95% CI 0.97 to 5.40, p=0.056) or too big for the penis (adjusted odds ratio 4.29, 95% CI 1.43 to 12.80, p=0.009) and rough sex (adjusted odds ratio 6.39 CI 3.55 to 11.52, p<0.001). CONCLUSIONS: Condom use among Bangalore FSWs is now very high. However, condom breakage is still a not uncommon event and puts women and their clients at unnecessary risk of infection. It may be difficult to eliminate the problem completely, but every effort should be made to discuss with sex workers the findings of this survey that point to possible personal markers of risk seen in the univariate analysis and to highlight the importance of avoiding rough sex and of ensuring the condom fits the client.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".