Sexually Transmitted Infections: Educational Settings
Bibliographic record
Abstract
Background: Sexually transmitted infections (STIs) are a major public health concern in Canada and worldwide. Nearly two-thirds of STIs are seen among youth. Therefore, it is crucial to provide effective STI interventions to youth. Substance use is an important factor for STI acquisition among youth because of high prevalence and its ability to link proximal sexual risk behaviors and distal contextual factors. STI preventive behavioral interventions remain the gold standard due to the limitations in biomedical interventions. Educational institutions are recognized as ideal settings to target youth. Thus, it is essential to assess whether integrating substance use into STI prevention programs at educational settings is worthwhile as well as whether STI preventive interventions at educational settings are effective and how can they be improved. \nObjectives and Methods: The objectives and methodologies of this thesis include 1) determine the prevalence and association between substance use and STIs among Canadian post-secondary students (descriptive analysis and logistic regression of the ACHA-NCHA II Spring 2016 survey data and 2) assess the efficacy and effectiveness of STI preventive intervention programs at educational settings (a systematic review and meta-analysis). \nResults: Positive association exists between current cannabis use or other drug use and STIs among Canadian post secondary students. STI preventive interventions at educational institutions in developed countries show effectiveness. Interventions are more effective in promoting knowledge compared to enhancing motivational factors, behavioral skills and behaviors, and for female students. No significant difference in effectiveness is seen based on the type of provider (peer-involved and non-peer-involved) and type of intervention (face-to-face and technology-based).\nRecommendations: Based on our findings, it is recommended to integrate substance use preventive interventions into STI preventive interventions at Canadian post-secondary institutions. A potential framework for effective STI preventive interventions at educational settings which can possibly be inferred to the Canadian post-secondary institutions is presented based on our results. This thesis will help inform, evaluate and guide STI preventive interventions at educational settings to effectively reduce the burden of STIs among Canadian youth. Future research with more rigorous methodology should be undertaken to provide conclusive evidence.
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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 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.029 | 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".