Virtually Supervised Exercise For People With Ovarian Cancer: Preliminary Feasibility And Physical Function Results
Bibliographic record
Abstract
People living with or beyond ovarian cancer are at a higher risk of falling, and most do not meet recommended exercise levels. Targeted exercise programs are needed to safely improve balance and physical function to ultimately reduce the risk of falls in this population. PURPOSE: To measure preliminary feasibility and efficacy results from the BE-BALANCED virtually supervised exercise program for people living with ovarian cancer. METHODS: BE-BALANCED is an ongoing prospective single-arm feasibility study. Individuals who completed primary chemotherapy treatment for ovarian cancer in the last year were recruited by oncologist- or self-referral. A 12-week group exercise program was delivered twice weekly for an hour each over Zoom by an exercise physiologist. The program included aerobic, functional strength, balance, and range of motion exercises. Feasibility measures, identified a priori, included accrual, attendance, adherence, and attrition. Feasibility was considered achieved if accrual reached 30 participants, attendance was at least 70% and attrition was less than 30%. Exercise adherence was measured as the percent of classes in which participants met the exercise intensity target range, which increased from 10-12 to 13-15, using the Borg Rating of Perceived Exertion (RPE) scale. Physical function was measured using the 6-minute walk test (6MWT) and balance was measured using gait speed from the Short Physical Performance Battery. RESULTS: Thirty-seven individuals have been screened and 15 enrolled (age 58 ± 9.6 years). Eleven participants completed the program, and 4 (27%) withdrew. Exercise class attendance was 83% and adherence was 93%. Mean 6MWT distance improved by 10.2% (49.0 m ± 55.9) post-intervention. Gait speed while walking 4 meters improved by 22.0% (0.24 m/s ± 0.17). Among participants who did no moderate or vigorous exercise at baseline (n = 4), 6MWT improved by 19.2% (83.2 m ± 71.7), and gait speed improved 31.8% (0.32 m/s ± 0.18). CONCLUSION: Preliminary results suggests that a virtual exercise program for people with ovarian cancer is potentially feasible. Recruitment is ongoing. 6MWT and gait speed results suggest physical function and balance improve after the intervention. FUNDING: Women’s Health Research Institute Catalyst Grant (PI: KL Campbell)
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".