Physical Activity Preferences Among a Population-Based Sample of Colorectal Cancer Survivors
Bibliographic record
Abstract
PURPOSE/OBJECTIVES: To identify the key physical activity (PA) programming and counseling preferences of colorectal cancer (CRC) survivors. DESIGN: Population-based, cross-sectional mailed survey. SETTING: Alberta, Canada. SAMPLE: 600 CRC survivors. METHODS: CRC survivors randomly identified through the Alberta Cancer Registry in Canada completed a mailed survey (34% response rate). MAIN RESEARCH VARIABLES: Self-reported PA, medical and demographic variables, and PA preferences. FINDINGS: Most CRC survivors indicated that they were interested and able to participate in a PA program. The most common PA preferences of CRC survivors were to receive PA counseling from a fitness expert at a cancer center, receive PA information in the form of print materials, start a PA program after cancer treatment, do PA at home, and walk in both the summer and winter. In addition, oncologists and nurses were identified as preferences from whom CRC survivors would like to receive PA information. Chi-square analyses identified that age, education, annual family income, and current PA were the demographic variables most consistently associated with PA preferences. CONCLUSIONS: The majority of CRC survivors expressed an interest in participating in a PA program and key PA preferences were identified. Those preferences may be useful for developing and implementing successful PA interventions for CRC survivors. IMPLICATIONS FOR NURSING: Oncology nurses are in a unique position to promote PA for CRC survivors. Therefore, understanding CRC survivor PA preferences is essential to assist nurses in making appropriate PA recommendations or referrals. KNOWLEDGE TRANSLATION: Although CRC survivors' PA participation rates are low, they may have an interest in receiving PA programming and counseling. CRC survivors have indicated a preference to receive PA information from individuals within their cancer support team (e.g., fitness specialist at a cancer center, oncologist, nurses). The PA preferences identified by CRC survivors are important for the development of successful PA interventions.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".