Evaluation of an Educational Whiteboard Video to Introduce Fertility Preservation to Female Adolescents and Young Adults With Cancer
Bibliographic record
Abstract
PURPOSE: Fertility is an important issue for adolescents and young adults with cancer facing potential infertility. Egg cryopreservation options exist, but information is sometimes overwhelming. We evaluated a fertility preservation educational video and assessed patient and family knowledge and impressions at pre- and post-video timepoints. METHODS: We developed a whiteboard video to explain egg cryopreservation to patients and families. The video was evaluated on the basis of patient education best practices (readability, understandability, actionability). Participants were recruited using convenience sampling in oncology clinics. They completed questionnaires before and after watching to assess knowledge and interest. Inclusion criteria were patients age 13-39 years and minimum 1 month from diagnosis. Descriptive statistics, correlation analyses, and mean comparisons were conducted. RESULTS: The video script read at a grade 8 reading level. Average understandability and actionability scores were below the acceptable standard. We recruited 108 patients (mean age, 27 years) and 39 caregivers/partners. Patients' knowledge about fertility preservation increased after viewing the video. Interest was high before and after, and satisfaction was high for both patients and caregivers. Participants appreciated information on process, procedure, and delivery but desired more information on logistics, including cost. CONCLUSION: A targeted patient education video about fertility preservation options can build knowledge and encourage discussions about infertility. The video can be used as a model for videos on related topics to provide accurate information in a youth-friendly medium; however, following patient education best practices for readability, understandability, and actionability may increase video effectiveness. Future research should assess how audiovisual patient education material affects patient behavior.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".