Demographics and Health Characteristics Associated With the Likelihood of Participating in Digitally Delivered Exercise Rehabilitation for Improving Heart Health Among Breast Cancer Survivors: Cross-Sectional Survey Study
Bibliographic record
Abstract
Background: Strong evidence supports the benefits of exercise following both cardiovascular disease and cancer diagnoses. However, less than one-third of Australians who are referred to exercise rehabilitation complete a program following a cardiac diagnosis. Technological advances make it increasingly possible to embed real-time supervision, tailored exercise prescription, behavior change, and social support into home-based programs. Objective: This study aimed to explore demographic and health characteristics associated with the likelihood of breast cancer survivors uptaking a digitally delivered cardiac exercise rehabilitation program and to determine whether this differed according to intervention timing (ie, offered generally, before, during, or after treatment). Secondary aims were to explore the knowledge of cardiac-related treatment side-effects, exercise behavior, additional intervention interests (eg, diet, fatigue management), and service fee capabilities. Methods: This cross-sectional study involved a convenience sample of breast cancer survivors recruited via social media. A self-reported questionnaire was used to collect outcomes of interests, including the likelihood of uptaking a digitally delivered cardiac exercise rehabilitation program, and demographic and health characteristics. Descriptive statistics were used to summarize sample characteristics and outcomes. Ordered logistic regression models were used to examine associations between demographic and health characteristics and likelihood of intervention uptake generally, before, during, and after treatment, with odds ratios (ORs) <0.67 or >1.5 defined as clinically meaningful and statistical significance a priori set at P≤.05. Results: A high proportion (194/208, 93%) of the sample (mean age 57, SD 11 years; median BMI=26, IQR 23-31 kg/m2) met recommended physical activity levels at the time of the survey. Living in an outer regional area (compared with living in a major city) was associated with higher odds of uptake in each model (OR 3.86-8.57, 95% CI 1.04-68.47; P=.01-.04). Receiving more cardiotoxic treatments was also associated with higher odds of general uptake (OR 1.42, 95% CI 1.02-1.96; P=.04). There was some evidence that a higher BMI, more comorbid conditions, and lower education (compared with university education) were associated with lower odds of intervention uptake, but findings differed according to intervention timing. Respondents identified the need for better education about the cardiotoxic effects of breast cancer treatment, and the desire for multifaceted rehabilitation interventions that are free or low cost (median Aus $10, IQR 10-15 per session; Aus $1=US $0.69 at time of study). Conclusions: These findings can be used to better inform future research and the development of intervention techniques that are critical to improving the delivery of a digital service model that is effective, equitable, and accessible, specifically, by enhancing digital inclusion, addressing general exercise barriers experienced by chronic disease populations, incorporating multidisciplinary care, and developing affordable delivery models.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".