Oncologists' attitudes towards recommending exercise to cancer patients: A Canadian national survey
Bibliographic record
Abstract
8138 Background: Preliminary research suggests that exercise may be a beneficial supportive therapy for cancer patients and that oncologists may play an important role in promoting exercise to their patients. In the present study, we examined oncologists' attitudes towards recommending exercise to cancer patients during treatment. Methods: Using a national survey, 659 practicing medical and radiation oncologists in Canada listed in the Canadian Medical Directory and Royal College of Physicians and Surgeons directory (2002–2003) were sent a brief questionnaire. Results: The response rate was 46% (281/610). Overall, the majority of oncologists agreed that exercise was beneficial (62.0%), important (55.8%) and safe (63.1%) for cancer patients during treatment. Moreover, 43.1% reported that they tried to recommend exercise to their patients when appropriate while oncologists' actually reported recommending exercise to 28% of their patients in the past month. Independent predictors of providing an exercise recommendation were oncologists' intention (β=.42; p<.001) and perceived ability to recommend exercise (β=.15; p=.009), and their evaluation of their patients' perceived approval of providing exercise advice (β=.15; p=.024). Analyses also indicated significant differences between oncologists with younger, female, and medical oncologists generally having more favorable attitudes towards exercise for cancer patients. Conclusions: Oncologists have a favorable attitude toward recommending exercise to cancer patients although several important barriers may prevent oncologists' from providing exercise advice to their patients. Further research is required evaluating the effectiveness of interventions and strategies designed to improve oncologist's confidence and ability to advise their patients on exercise during oncology consultations. No significant financial relationships to disclose.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 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".