STI Health Disparities: A Systematic Review and Meta-Analysis of the Effectiveness of Preventive Interventions in Educational Settings
Bibliographic record
Abstract
The purpose of this systematic review and meta-analysis was to address disparities related to sexual health among students by examining the effectiveness of sexually transmitted infection (STI) preventive interventions in educational settings. PubMed, Medline, Cochrane Library, Public Health Database, and EMBASE databases were used to conduct searches. Information relating to studies, programs, participants, and quantitative outcome variables were extracted. Risk of bias was assessed and meta-analysis was conducted. This systematic review included 16 articles. The outcomes were classified into behavioral and psychosocial categories. The behavioral category included sexual partners, sexual activity, condom use, STI/HIV testing, and alcohol/drug use before sex. The psychosocial category consisted of knowledge, motivational factors, and skills. Interventions had a significantly positive impact on both behavioral (OR, 1.28; 95% CI, 1.17⁻1.39) and psychosocial (OR, 1.92; 95% CI, 1.36⁻2.72) outcomes. Among the psychosocial outcomes, the interventions were most effective at promoting knowledge (OR, 3.17; 95% CI, 2.13⁻4.72), followed by enhancing motivational factors (OR, 1.69; 95% CI, 1.04⁻2.75) and increasing behavioral skills (OR, 1.43; 95% CI, 1.13⁻1.81). The results of this systematic review provide empirical evidence for public health professionals and policy makers regarding planning, implementation, evaluation, and modification of STI preventive intervention programs in educational settings.
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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 | 0.022 | 0.063 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.024 | 0.039 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| 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".