The prevalence of physical activity information for breast cancer stakeholders on Canadian cancer websites
Bibliographic record
Abstract
An increasing number of individuals have become reliant on the internet to obtain health/ disease related information. Online breast cancer center websites may be a useful tool for distributing information on the benefits of physical activity in relation to breast cancer, and can serve to assist breast cancer patients to make positive changes to physical activity behaviour. To date, the physical activity information on accessible websites affiliated with prominent cancer centers in Canada has not been evaluated. The aim of this study is to describe and evaluate the physical activity content and information provided on cancer center websites, which were selected if a radiology department was present. The websites (n=24) were evaluated by two raters based on the eEurope 2002: Quality Criteria for Health related websites and CALO-RE taxonomy of behaviour change techniques (BCTs). Inter-rater reliability for evaluation of websites was 87%. Cancer center websites contained an average of 6.88 BCTs. Overall, the majority of cancer center websites (n= 21) offered some form of physical activity information. The most frequently published BCTs included; provide information about consequences in general (92%), goal setting (50%) and set graded tasks (50%). Based on these findings, Canadian cancer center websites should be improved for information content to help breast cancer patients and clinicians understand the well-known benefits of physical activity and offer strategies for improving healthy participation. These results provide preliminary evidence that knowledge translation efforts should be emphasized to help the nearly 90% of breast cancer survivors who are currently inactive.
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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 | 0.005 | 0.045 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".