Hybrid Tele and In-Clinic Occupation Based Intervention to Improve Women’s Daily Participation after Breast Cancer: A Pilot Randomized Controlled Trial
Bibliographic record
Abstract
Background: Women after breast cancer (BC) cope with decreased daily participation and quality of life (QOL) due to physical, cognitive, and emotional symptoms. This study examined a hybrid occupation-based intervention, Managing Participation with Breast Cancer (MaP-BC), to improve daily participation in their meaningful activities. Methods: Thirty-five women after BC phase were randomly allocated to the MaP-BC intervention (n = 18) or control (n = 17) group (standard care only). Assessments were administered at baseline (T1), 6-week (T2), and 12-week (T3) post-T1. Main outcome: perceived performance and performance-satisfaction with meaningful activities according to the Canadian Occupational Performance Measure. Secondary outcomes: retained activity levels (Activity Card Sort), QOL (Functional Assessment of Cancer Therapy-Breast), cognitive abilities (Montreal Cognitive Assessment and Behavior Rating Inventory of Executive Function), and upper-extremity functioning (Disability of Arm, Shoulder, Hand). Results showed significant interaction (group x time) effects for the primary outcome in performance, F(2,66) = 29.54, p = 0.001, ɳP2 = 0.472, and satisfaction, F(2,66) = 37.15, p = 0.000, ɳP2 = 0.530. The intervention group improved more in performance, t = 5.51, p = 0.0001, d = 1.298, and satisfaction, t = −5.32, p = 0.0001, d = 1.254, than the control group between T1 and T2. Secondary outcomes demonstrated within-group improvements. Conclusion: MaP-BC, a comprehensive occupation-based hybrid intervention tailored to women’s functional daily needs after BC, improved participation in meaningful activities within a short period.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".