Quality and accuracy of publicly accessible cancer‐related physical activity information on the Internet: a cross‐sectional assessment
Bibliographic record
Abstract
In this study, we assessed the quality of publicly available cancer-related physical activity (PA) information appearing on reputable sites from Canada and other English-speaking countries. A cross-sectional Internet search was conducted on select countries (Canada, USA, Australia, New Zealand, UK) using Google to generate top 50 results per country for the keywords "'physical activity' AND 'cancer'". Top results were assessed for quality of PA information based on a coding frame. Additional searches were performed for Canadian-based sites to produce an exhaustive list. Results found that many sites offered cancer-related PA information (94.5%), but rarely defined PA (25.2%). Top 50 results from each country did not differ on any indicator examined. The exhaustive list of Canadian sites found that many sites gave information about PA for survivorship (78.3%) and prevention (70.0%), but rarely defined (6.7%) or referenced PA guidelines (28.3%). Cancer-related PA information is plentiful on the Internet but the quality needs improvement. Sites should do more than mention PA; they should provide definitions, examples and guidelines. With improvements, these websites would enable healthcare providers to effectively educate their patients about PA, and serve as a valuable resource to the general public who may be seeking cancer-related PA information.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".