Patient-Oriented Methotrexate Information Sites on the Internet: A Review of Completeness, Accuracy, Format, Reliability, Credibility, and Readability
Bibliographic record
Abstract
OBJECTIVE: With continuing use of the Internet, rheumatologists are referring patients to various websites to gain information about medications and diseases. Our goal was to develop and evaluate a Medication Website Assessment Tool (MWAT) for use by health professionals, and to explore the overall quality of methotrexate information presented on common English-language websites. METHODS: Identification of websites was performed using a search strategy on the search engine Google. The first 250 hits were screened. Inclusion criteria included those English-language websites from authoritative sources, trusted medical, physicians', and common health-related websites. Websites from pharmaceutical companies, online pharmacies, and where the purpose seemed to be primarily advertisements were also included. Product monographs or technical-based web pages and web pages where the information was clearly directed at patients with cancer were excluded. Two reviewers independently scored each included web page for completeness and accuracy, format, readability, reliability, and credibility. An overall ranking was provided for each methotrexate information page. RESULTS: Twenty-eight web pages were included in the analysis. The average score for completeness and accuracy was 15.48+/-3.70 (maximum 24) with 10 out of 28 pages scoring 18 (75%) or higher. The average format score was 6.00+/-1.46 (maximum 8). The Flesch-Kincaid Grade Level revealed an average grade level of 10.07+/-1.84, with 5 out of 28 websites written at a reading level less than grade 8; however, no web page scored at a grade 5 to 6 level. An overall ranking was calculated identifying 8 web pages as appropriate sources of accurate and reliable methotrexate information. CONCLUSION: With the enormous amount of information available on the Internet, it is important to direct patients to web pages that are complete, accurate, readable, and credible sources of information. We identified web pages that may serve the interests of both rheumatologists and patients.
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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 | 0.051 | 0.197 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.023 | 0.021 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".