Satisfaction of a Virtually Delivered Supervised Exercise Program Specific to Breast Cancer Survivors on Endocrine Therapy
Bibliographic record
Abstract
Background Only 11% of breast cancer survivors currently meet the exercise oncology guidelines, and the restrictions to gyms and time outside of home related to the COVID-19 pandemic may have aggravated this situation. To address this, we are testing the efficacy of a twice-weekly, 8-week, supervised, synchronous exercise program delivered virtually for participants diagnosed with breast cancer, called the BE-FIT program. Objective The aim of this paper is to examine the preliminary participant's satisfaction in participating in the BE-FIT program. Methods Participants are asked to complete a “Participant Satisfaction Questionnaire” using a range of 1-5 for each question (1 represents “very difficult,” 2 “difficult,” 3 “neutral,” 4 “easy,” and 5 “very easy”). The questions were related to the following: level of difficulty to access classes; level of clarity of information received during classes; level of capacity to continue practicing exercises independently after finishing the exercise program; and level of how likely one would recommend the program to a friend. Results For the ongoing efficacy trial, we collected responses from 40 participants. The participants reported that it was “very easy” and “easy” to access and participate in the virtual exercise session (63% and 37%, respectively). When asked if the information received from the exercise training was clear and easy to understand during virtual exercise sessions, 93% reported “very easy,” and the remainder reported “easy.” Regarding continuing the exercise independently with the content learned in the program, 87% of the participants reported “very easy” or “easy” (31% and 56%, respectively), and 13% reported “neutral.” Lastly, 80% of participants reported “very easy” to recommend the BE-FIT program to a friend, 18% reported “easy,” and 2% reported “neutral.” Conclusions A virtually delivered supervised program seems to be an excellent alternative to in-person supervised exercise programs to provide easy access and clear information during the classes with potential influence on the future practice of exercises. Conflicts of Interest None declared. Trial Registration ClinicalTrials.gov NCT04824339; https://clinicaltrials.gov/ct2/show/NCT04824339
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".