Preparing for National Implementation of an Evidence-based, Effective HIV Prevention Program among Bahamian Sixth-Grade Students
Bibliographic record
Abstract
Using data from the preparatory phase prior to national implementation of an effective HIV prevention program (Focus on Youth in the Caribbean; FOYC) in all Bahamian government sixth-grade classes, we describe (1) actual FOYC implementation, (2) factors that influenced implementation, and (3) the relationship of implementation with intervention outcome. Six elementary schools (with 17 grade six classrooms) were selected to participate in the preparatory phase. The 17 teachers were invited to attend a training workshop, coordinate administration of questionnaires to the students, teach the 10 sessions of FOYC and complete self-assessment checklists. A total of 395 students submitted baseline and 311 students submitted year-end questionnaires. Thirteen teachers initiated FOYC; five completed all 10 sessions. Implementation of FOYC was not related to teacher FOYC workshop experience but did cluster by school. There were significant positive correlations between improved student knowledge of HIV/AIDS, protective health skills, perceived parental monitoring and reduced risk behaviours with the number of FOYC sessions delivered. Implementation was impeded by logistics issues, structural issues with the measures, and comfort-level issues, most of which can be addressed for national implementation. Degree of FOYC implementation is correlated with positive student 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 | 0.004 | 0.008 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".