Telerehabilitation for Managing Daily Participation among Breast Cancer Survivors during COVID-19: A Feasibility Study
Bibliographic record
Abstract
We aimed to examine the feasibility and impact of a short-term occupation-based telerehabilitation intervention (Managing Participation with Breast Cancer (MaP-BC)) on daily participation, health-related quality-of-life, and breast-cancer-related symptoms and understand women's perspectives regarding strategies to manage daily participation and symptoms during COVID-19 pandemic. A mixed-methods study (single-arm pre-post with a qualitative component) included 14 women after their primary medical treatment for breast cancer. Women received six weeks of occupation-based intervention using a video-communication. Sessions focused on identifying functional goals and training strategies to manage daily participation. The primary outcome was perceived performance and satisfaction with meaningful activities by the Canadian Occupational Performance Measure (COPM). Secondary outcomes were participation in the Activity Card Sort (ACS), upper-extremity functioning of Disability Arm Shoulder Hand, self-reported symptom severity, executive-functioning, health-related quality of life, and a question regarding strategies used to manage daily participation. Women significantly improved their daily participation in meaningful activities in the COPM, most ACS activity domains, self-reported executive functioning, and health-related-quality-of-life. Qualitative findings revealed three main themes: (1) daily life under the threats of breast cancer and COVID-19, (2) women's own strategies to overcome challenges, and (3) contribution of the MaP-BC. Providing telerehabilitation during the COVID-19 pandemic is feasible and successful in improving women's daily participation after breast cancer.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".