Teen clinics: missing the mark? Comparing pregnancy and sexually transmitted infections rates among enrolled and non-enrolled adolescents
Bibliographic record
Abstract
BACKGROUND: In Manitoba, Canada, school-based clinics providing sexual and reproductive health services for adolescents have been implemented to address high rates of sexually transmitted infections (STIs) and pregnancies. METHODS: The objectives of this population-based study were to compare pregnancy and STI rates between adolescents enrolled in schools with school-based clinics, those in schools without clinics, and those not enrolled in school. Data were from the PATHS Data Resource held in the Population Health Research Data Repository housed at the Manitoba Centre for Health Policy. Adolescents aged 14 to 19 between 2003 and 2009 were included in the study. Annualized rates of pregnancies and positive STI tests were estimated and Poisson regression models were used to test for differences in rates amongst the three groups. RESULTS: As a proportion, pregnancies among non-enrolled female adolescents accounted for 55 % of all pregnancies in this age group during the study period. Pregnancy rates were 2-3 times as high among non-enrolled female adolescents. Compared to adolescents enrolled in schools without school-based clinics, age-adjusted STI rates were 3.5 times (p < .001) higher in non-enrolled males and 2.3 times (p < .001) higher in non-enrolled females. CONCLUSIONS: The highest rates for pregnancies and STIs were observed among non-enrolled adolescents. Although provision of reproductive and health services to in-school adolescents should remain a priority, program planning and design should consider optimal strategies to engage out of school youth.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".