Patient-reported Barriers to Exercise and Predictors of Exercise Adherence During Adjuvant Chemotherapy for Breast Cancer
Bibliographic record
Abstract
The benefits associated with exercise training during chemotherapy for breast cancer are well known. However, information regarding barriers and adherence to a supervised exercise-training program during cancer treatment is limited. PURPOSE: To describe patient-reported barriers to exercise and identify predictors of adherence to a supervised exercise program during chemotherapy for breast cancer. METHODS: Women with early stage breast cancer were enrolled in the Nutrition and Exercise During Adjuvant Treatment trial, a thrice weekly supervised aerobic and resistance exercise program for ≥50% of the duration of adjuvant chemotherapy (8-24 wks). Patient-reported barriers were collected at baseline using a standard exercise barriers questionnaire and are summarized as % of participants who reported barriers ‘often’ or ‘very often.’ Potential predictors of adherence included demographic, quality of life, fitness and medical variables. Program adherence was defined as % of sessions attended. Univariate linear regression was used to determine significant (p < 0.05) and potential (p < 0.10) predictors of adherence. RESULTS: 68 participants (mean age=51±11 yrs) attended >1 study session, completing a mean of 11 weeks of exercise. The most common patient-reported barriers at baseline were exercise being perceived as boring (31.3%), or not a priority (28%), lack of equipment (21.5%), and fear of injury (21.5%). Intervention adherence to prescribed number of sessions was 64±14%. Marital status (p = 0.04) and having ≥3 comorbidities (β=-24.1, p = 0.01) predicted significantly lower adherence. Income >$80,000 (β=+14.9, p=0.03), university education (β=+17.7, p = 0.04) and higher physical functioning (β = +0.5, p= 0.02) predicted significantly higher adherence. Trends in adherence were also observed in those who had higher baseline physical activity (β = +0.2, p = 0.05), a child as a caregiver (β = -8.3, p = 0.09) and a diagnosis of hypertension (β = -8.0, p = 0.10). CONCLUSIONS: Exercise being perceived as boring or not a priority, access to equipment, and fear of injury are important barriers to address in exercise program design. Furthermore, determining demographic factors linked to adherence may allow for identifying individuals with greater adherence challenges and adapting interventions accordingly.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".