Chlamydia Screening Strategies and Outcomes in Educational Settings
Bibliographic record
Abstract
Chlamydia trachomatis (CT) screening programs have been established in educational settings in many countries during the past 2 decades. However, recent evidence suggests that high uptake of screening and management (treatment, partner notification, and retesting for reinfection) improves program effectiveness. We conducted a systematic review to understand the screening strategies, the extent of screening conducted, and uptake of management strategies in educational settings. Screening studies in educational settings were identified through a systematic search of published literature from 2005 to 2011. We identified 27 studies describing 30 screening programs in the United States/Canada (n = 10), Europe (n = 8), Australia/New Zealand (n = 5), and Asia (n = 4). Most studies targeted both male and female students (74%). Classroom-based strategies resulted in 21,117 testes overall (4 programs), followed by opportunistic screening during routine health examination (n = 13,470; 5 programs) and opportunistic screening at school-based health centers (n = 13,006; 5 programs). The overall median CT positivity was 4.7% (range, 1.3%-18.1%). Only 5 programs reported treatment rates (median, 100%; range, 86%-100%), 1 partner notification rate (71%), 1 retesting rate within a year of an initial CT diagnosis (47%), and 2 reported repeat positivity rates (21.1% and 26.3%). In conclusion, this systematic review shows that a variety of strategies have been used to screen large numbers of students in educational settings; however, only a few studies have reported CT management outcomes.
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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 | 0.008 | 0.063 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| 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".