Promoting optimal outcomes for STI/HIV prevention skills in youth
Bibliographic record
Abstract
Behaviours common among youth (e.g., inconsistent condom use, substance use) place them at increased risk for sexually transmitted infections (STIs). Despite decades of prevention efforts, STIs in youth continue to be a major public health challenge in Canada. Factors affecting school-based intervention success or failure have yet to be explained; contextual factors external to the individual, yet to be defined; and the involvement of youth in the design and evaluation of curriculum interventions, remains poorly documented.A three-phase exploratory study was conducted in two Prince Edward Island schools to describe: (a) factors youth identify as being important to facilitate their ability to take control of their sexual health behaviour, (b) what these youth perceive their needs to be in terms of sexual health education, (c) how they perceive newly developed curriculum resources, and (d) what can be learned about their participation in a curriculum development process.In Phase I, 15 girls and 13 boys participated in focus groups (n=8) and engaged in participatory activities (e.g., reflective writing, role-play, drawing) in order to identify their sexual health education needs and to contribute to the form and content of educational resources to be developed. In Phase II, curriculum experts assisted with refining the youth-generated materials so that they might become resources for use in schools. Eventually this process led to a set of resources (e.g., vignettes, sexual-risk assessment activities, and games) that promote STI/HIV prevention. In Phase III, 22 of the 28 participants from Phase I participated in focus groups (n=4) to evaluate the curriculum resources refined in Phase II. Inductive analyses of data (thematic and content analysis) from student focus groups were undertaken. Youth described positive and negative influences (factors at the intrapersonal, interpersonal, organizational, and community levels) on their ability to take control of sexual health behaviour. The findings from this study offer insight into the social composition of sexual risk that needs to be considered in future intervention studies. A tailored approach to the development of sexual health curriculum resources for youth may improve school-based intervention success toward preventing STIs in this high-risk group.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".