P3.315 Does Adjusting For Sexual Behaviour Improve the Accuracy of Population-Based Chlamydia Incidence and Screening Rates Among Adolescents in British Columbia, Canada?
Bibliographic record
Abstract
Background Recent studies using setting-specific health insurance or clinical datasets have demonstrated the importance of considering sexual activity when calculating Chlamydia incidence and screening rates, particularly for adolescents. Using data from a provincial adolescent health survey we assessed the impact of adjusting for sexual activity on population-based Chlamydia incidence and screening rates among adolescents in British Columbia (BC), Canada. Methods We estimated the proportion of adolescent males (15–18 years) and females (14–18 years) who had ever had sexual intercourse (i.e., sexually active) using data from a cluster-stratified survey of public school students (Grades 7–12) completed by ∼30,000 BC students in 2003 and 2008. Using provincial Chlamydia surveillance and testing data we compared adolescent Chlamydia screening and incidence rates in BC by age and gender, using total and sexually active populations as denominators. Results During these time periods, an estimated 32% and 33% of males 15–18 years and 28% and 31% of females 14–18 years were sexually active in 2003 and 2008 respectively. Regardless of denominator used, screening and incidence rates increased with age, and were higher among females compared to males. Sexually active incidence and screening rates were consistently higher with a more pronounced impact at younger ages. For example, in 2008 screening rates among 14 year old females were 26.2% vs 2.5% in sexually active and total populations respectively, while the corresponding rates among 18 year old females were 60.2% vs 28.9% (2.1 times higher). Conclusions Using data representing the entire population of BC adolescents we demonstrated that without adjustment for sexual behaviour, adolescent Chlamydia incidence and screening rates are substantially under-estimated, particularly at younger ages. Adjusting for sexual behaviour using population survey data is essential for accurately monitoring the population impact of prevention and screening programmes among adolescents.
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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 | 0.007 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".