The quality of websites addressing fibromyalgia: an assessment of quality and readability using standardised tools
Bibliographic record
Abstract
Background Patients living with fibromyalgia strongly prefer to access health information on the web. However, the majority of subjects in previous studies strongly expressed their concerns about the quality of online information resources. Objectives The purpose of this study was to evaluate existing online fibromyalgia information resources for content, quality and readability by using standardised quality and readability tools. Methods The first 25 websites were identified using Google and the search keyword 'fibromyalgia'. Pairs of raters independently evaluated website quality using two structured tools (DISCERN and a quality checklist). Readability was assessed using the Flesch Reading Ease score maps. Results Ranking of the websites' quality varied by the tool used, although there was general agreement about the top three websites (Fibromyalgia Information, Fibromyalgia Information Foundation and National Institute of Arthritis and Musculoskeletal and Skin Diseases). Content analysis indicated that 72% of websites provided information on treatment options, 68% on symptoms, 60% on diagnosis and 40% on coping and resources. DISCERN ratings classified 32% websites as 'very good', 32% as 'good and 36% as 'marginal'. The mean overall DISCERN score was 36.88 (good). Only 16% of websites met the recommended literacy level grade of 6-8 (range 7-15). Conclusion Higher quality websites tended to be less readable. Online fibromyalgia information resources do not provide comprehensive information about fibromyalgia, and have low quality and poor readability. While information is very important for those living with fibromyalgia, current resources are unlikely to provide necessary or accurate information, and may not be usable for most people.
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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 | 0.035 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".