To Close the Gap of Survivorship Education: A Series of Breast Cancer Webinars in Collaboration with Wellspring
Bibliographic record
Abstract
Background and Aims: Breast cancer survivors face uncertainties post-treatment, requiring ongoing support and education. Digital media online training courses may be used to disseminate evidence-based cancer information. In this study, we hosted a series of webinars which aimed to empower survivors with evidence-based survivorship information. Materials and Methods: A four-part weekly online webinar series (1 hour each) including expert presentations, survivor insights, and interactive question-and-answer sessions, was held in October 2023 during Breast Cancer Awareness Month, via the Zoom digital platform. Topics covered included surveillance, mental health, adjuvant antihormonal therapy, and sexual health. After the webinar series, participants completed a post-webinar survey electronically. The post-webinar survey assessed participant satisfaction, understanding of topics, and suggestions for improvement. Likert scales were used to measure self-reported changes in understanding of the discussed topics. Results: 99 participants took part in the Breast Survivorship and Surveillance webinar, 97 participated in the Mental Health in Breast Survivorship webinar, 108 participated in the Adjuvant Antihormonal Therapy for Breast Cancer webinar, and 74 participated in the Sexual Health after Breast Cancer webinar. 25 participants completed the post-webinar survey, administered after the final webinar (sexual health). Among the 25 survey participants, 96% (24/25) expressed that the information presented in the series of webinars was very useful or extremely useful. Furthermore, 80% (20/25) noted significant knowledge improvement. Conclusions: This breast cancer webinar series effectively bridges the knowledge gap in survivorship, offering valuable insights, emotional support, and practical guidance. The results emphasize the importance of ongoing education and support for breast cancer survivors.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.005 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".