Assessment of HIV-related risky behaviour: a comparative study of face-to-face interviews and polling booth surveys in the general population of Cotonou, Benin
Bibliographic record
Abstract
OBJECTIVES: During the 2008 HIV prevalence survey carried out in the general population of Cotonou, Benin, face-to-face interviews (FTFI) were used to assess risky behaviours for HIV and other sexually transmitted infections (STI). We compared sexual behaviours reported in FTFI with those reported in polling booth surveys (PBS) carried out in parallel in an independent random sample of the same population. METHODS: In PBS, respondents grouped by gender and marital status answered simple questions by putting tokens with question numbers in a green box (affirmative answers) or a red box (negative answers). Both boxes were placed inside a private booth. For each group and question, data were gathered together by type of answer. The structured and gender-specific FTFI guided by trained interviewers included all questions asked during PBS. Pearson χ2 or Fisher's exact test was used to compare FTFI and PBS according to affirmative answers. RESULTS: Overall, respondents reported more stigmatised behaviours in PBS than in FTFI: the proportions of married women and men who reported ever having had commercial sex were 17.4% and 41.6% in PBS versus 1.8% and 19.6% in FTFI, respectively. The corresponding proportions among unmarried women and men were 16.1% and 25.5% in PBS versus 3.9% and 13.0% in FTFI, respectively. The proportion of married women who reported having had extramarital sex since marriage was 23.6% in PBS versus 4.6% in FTFI. CONCLUSIONS: PBS are suitable to monitor reliable HIV/STI risk behaviours. Their use should be expanded in behavioural surveillance.
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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".