Factors associated with interest in bacterial sexually transmitted infection vaccines at two large sexually transmitted infection clinics in British Columbia, Canada
Bibliographic record
Abstract
OBJECTIVE: To explore sexually transmitted infection (STI) clinic client attitudes and preferences towards STI vaccines and STI vaccine programming in an urban clinic setting. METHODS: A 31-item questionnaire was administered during check-in by clinic clerical staff at two STI clinics in Vancouver, Canada. Demographic characteristics and preferences were summarised descriptively. Multivariable logistic regression models to assess factors associated with STI vaccine interest (reported as ORs) were constructed using a priori clinically relevant variables and factors significant at p≤0.05 in bivariate analysis. RESULTS: 293 surveys were included in analysis. 71.3% of respondents identified as male, 80.5% had college level education or higher and 52.9% identified as white/of European descent. The median age was 33. 86.5% of respondents reported they would be interested in receiving an STI vaccine, with a primary motivator to protect oneself. Bivariate analysis indicated several factors associated with vaccine interest, with differences for each infection. After adjusting for other variables, willingness to pay for an STI vaccine (OR=3.83, 95% CI 1.29 to 11.38, p=0.02) remained a significant factor for syphilis vaccine interest and intent to engage in future positive health behaviours remained a significant factor for chlamydia (OR=5.94, 95% CI 1.56 to 22.60, p=0.01) and gonorrhoea (OR=5.13, 95% CI 1.45 to 18.07, p=0.01) vaccine interest. CONCLUSION: Respondents expressed a strong willingness to receive STI vaccines. These valuable findings will inform for eventual STI vaccine programme planning and implementation.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".