Feasibility of a co-created yoga program for gynecologic cancer survivors implemented in a regional cancer support centre
Bibliographic record
Abstract
Background: Current yoga programs for cancer survivors do not meet participants’ needs and are rarely implemented in community-based settings, despite reported benefits. Thus, study objectives were to implement a co-created 12-week bi-modal Hatha-based yoga program for gynecologic cancer survivors in the community to assess the feasibility of the program and the evaluative study methods. Methods: Using a multiple baseline single subject research design with an 8-week follow-up phase, participants were recruited from The Ottawa Hospital and self-selected to enroll in a morning or evening program. They were asked to complete survey packages at 9-11 timepoints and complete an interview post-program. Recruitment, retention, adherence, and optional program feature use rates were assessed. Results: Forty-one gynecologic cancer survivors were screened for eligibility; 22 (53.6%) were eligible and 20 (90.9%; 10 per program) consented. One participant withdrew from the evening program due to time constraints; 17 (89.4%; nmorning=9, nevening=8) attended >75% (>18/24) of classes. Eighteen participants (94.7%; nmorning=9, nevening=9) were interviewed and 17 (89.4%; nmorning=9, nevening=8) provided data on the 8-week follow-up survey. For optional features, 6 participants (31.5%; nmorning=4, nevening=2) used >1 pre-recorded video, 15 (89.4%; nmorning=6, nevening=9) completed >3 journal entries, and 43/48 (89.5%; nmorning=24/24, nevening=19/24) group discussions were attended by >50% of participants. Conclusions: Recruitment and retention targets were achieved, supporting the feasibility of a future definitive trial. Yet, adherence and program engagement were lower than expected. Analysis of interview data will help to identify factors to focus on to enhance the feasibility of program features.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".