Bibliographic record
Abstract
There is no comprehensive and standardized tool for evaluating the communication quality of web resources for patients. The purpose of this study was to assess prostate cancer websites using the Communication AssessmenT Checklist in Health (CATCH) and to compare the results with those of the Consumer and Patient Health Information Section of the MLA (CAPHIS). CATCH is a theory-based tool consisting of 50 elements nested in 12 concepts. Two raters independently applied it to 35 HON certified websites containing information on prostate cancer treatment. The CATCH summary scores for these websites were then compared to the 2015 list of credible health websites published by CAPHIS. Websites contained a mean 24.1 (SD= 3.6) CATCH items. The concepts Language, Readability, Layout, Typography and Appearance were present in over 80% of sites. Content, Risk Communication, Usefulness, and Scientific Value were present in 50% or less. CATCH provided an overall score of the selected sites that was consistent with CAPHIS ratings. The prostate cancer websites evaluated in this study did not present treatment information in a useful, informative or credible way for patients. The communication quality of these resources could be improved with a clear strategic intent focused on decision-making, using CATCH as a guiding framework. CATCH is a tool that can be used independently or with other health resource evaluation tools to select the most trustworthy web resources for health 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 | 0.005 | 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 | 0.001 |
| Open science | 0.001 | 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".