A Survey-Based Study on Physical Activity Promotion for Individuals with a Current or Past Diagnosis of Cancer in Canada
Bibliographic record
Abstract
Purpose: To determine the prevalence and content of discussions regarding physical activity (PA) promotion between individuals with a current or past diagnosis of cancer and their oncology care team. Methods: Design and Procedure: A cross-sectional survey on PA discussion between individuals with a current or past diagnosis of cancer and their oncology care team was conducted at a single timepoint. Participants: Eligible participants were adults with a current or past diagnosis of cancer at any time point in their cancer treatment who had a pre-scheduled appointment with their oncology care team. Results: A total of 100 participants completed the survey. PA-related discussions happened in 41% of the patient-provider interactions and 66% of respondents reported PA discussions at some point during care. No significant association occurred between cancer type, stage, or treatment status and PA discussions at any timepoint (all p’s > 0.05). Most respondents were satisfied with the education provided on PA (54%); however, only 37% were sufficiently active. Those receiving education from their medical oncologist were more likely to be ‘sufficiently active’ (p = 0.020) according to the Godin Leisure Time Exercise Questionnaire. Conclusions: Most respondents discuss PA with an oncology care provider at some point during their cancer treatment; however, few are sufficiently active. Future research is needed to determine strategies to facilitate PA promotion and close the gap between discussions and actual physical activity behavior.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".