Adherence to a remote exercise program and quality of life among patients with cancer: The mediating role of symptom burden.
Bibliographic record
Abstract
349 Background: Remote exercise interventions are being increasingly employed in oncology, but real-world adherence and its impact on outcomes remain to be established. Understanding whether adherence is associated with better quality of life (QOL), and how symptom burden mediates this relationship, is critical to optimizing supportive care delivery for patients with cancer. Methods: We conducted a longitudinal, single-arm study of a 12-week remote exercise program among adults with cancer receiving systemic treatment. Eligible participants had ECOG ≤2 and access to a smartphone. The intervention included weekly virtual sessions with an exercise physiologist and personalized prescriptions based on the Borg scale, supported by instructional videos and remote guidance via WhatsApp. Participants were encouraged to complete a 30–45-minute exercise session per day. Assessments were conducted at baseline and 12 weeks using the Functional Assessment of Cancer Therapy–General (FACT-G) for QOL and the Edmonton Symptom Assessment Scale (ESAS) for symptom burden. Adherence was defined as high (≥8 weeks) or low (< 8 weeks). Mediation analysis (PROCESS Model 4 with 5,000 bootstrap) tested whether symptom burden at 12 weeks mediated the effect of adherence on QOL. Analyses controlled for baseline FACT-G and ESAS scores. Results: Among 149 participants (median age: 68 years; range: 32–88), 55.0% were female, 67.8% were white, and 56.3% college educated. The most common cancer types were breast (24.8%), genitourinary (17.4%), and gynecological (14.8%); 67.1% had stage IV disease. Treatments included immunotherapy (46.5%), targeted therapy (21.7%), chemotherapy (16.3%), and combination regimens (15.5%). Patients with high adherence (71.1%) showed significantly greater improvement in QOL from baseline to 12 weeks. Adherence had a significant direct effect on QOL at 12 weeks (B = 10.78, SE = 1.33, p < .001; 95% CI: 8.15 to 13.40) and an indirect effect via symptom burden (B = 2.30, Bootstrapped 95% CI: 0.13 to 5.81), indicating partial mediation. These findings suggest that patients who adhered more to the prescribed exercise program had subsequently better QOL, in part due to reduced symptom burden. Conclusions: High adherence to remote exercise programs may lead to meaningful improvements in QOL, partly through reduced symptom burden. Supporting adherence may enhance the effectiveness and scalability of digital exercise interventions in oncology.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".