Informed and Empowered: A Pre–Post Evaluation of a Whiteboard Video for Sexual Health Education in Female Adolescents and Young Adults with Cancer
Bibliographic record
Abstract
Adolescents and young adults (AYA) assigned female at birth with cancer face significant sexual health challenges, yet accessible, age-appropriate educational tools remain limited. This study evaluated a 13 min whiteboard video designed to improve sexual health knowledge. Female AYA patients aged 15–39 years across Canada completed pre- and post-video surveys assessing knowledge, attitudes, and satisfaction. The video’s understandability and actionability were measured using the Patient Education Materials Assessment Tool for Audiovisual Materials (PEMAT-A/V), and readability was assessed using six standard metrics. Quantitative analyses included paired t-tests and regression modeling; qualitative responses were thematically coded. Ninety participants completed the study. Knowledge scores increased by 19.5% (95% CI, 14–24%; p < 0.001, Cohen’s d = 0.89) following the video. Greater gains were observed among participants with a high school education or less (p = 0.040), while younger participants tended to show larger improvements. The video received average PEMAT-A/V scores of 96% for understandability and 94% for actionability. Most participants (89%) found it helpful for learning about sexual health and would recommend the video to peers, though suggested improvements included shorter length, enhanced visuals, and more age-specific content. Nearly half reported never discussing sexual health with providers. These findings support the feasibility of whiteboard video as an effective, scalable tool to address sexual health in oncology care.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".