Evaluation of the Quality of Delirium Website Content for Patient and Family Education: Cross-Sectional Study
Bibliographic record
Abstract
BACKGROUND: Patients and families who have experienced delirium may seek information about delirium online, but the quality and reliability of online delirium-related websites are unknown. OBJECTIVE: This study aimed to identify and evaluate online delirium-related websites that could be used for patient and family education. METHODS: We searched Microsoft Bing, Google, and Yahoo using the keywords "delirium" and the misspelled "delerium" to identify delirium-related websites created to inform patients, families, and members of the public about delirium. The quality of identified delirium-related website content was evaluated by 2 authors using the validated DISCERN tool and the JAMA (Journal of the American Medical Association) benchmark criteria. Readability was assessed with the Simple Measure of Gobbledygook, the Flesch Reading Ease score, and the Flesch Kincaid grade level. Each piece of website content was assessed for its delirium-related information using a checklist of items co-designed by a working group, which included patients, families, researchers, and clinicians. RESULTS: We identified 106 websites targeted toward patients and families, with most hospital-affiliated (21/106, 20%) from commercial websites (20/106, 19%), government-affiliated organizations (19/106, 18%), or from a foundation or advocacy group (16/106, 15%). The median time since the last content update was 3 (IQR 2-5) years. Most websites' content (101/106, 95%) was written at a reading level higher than the recommended grade 6 level. The median DISCERN total score was 42 (IQR 33-50), with scores ranging from 20 (very poor quality) to 78 (excellent quality). The median delirium-related content score was 8 (IQR 6-9), with scores ranging from 1 to 12. Many websites lacked information on the short- and long-term outcomes of delirium as well as how common it is. The median JAMA benchmark score was 1 (IQR 1-3), indicating the quality of the websites' content had poor transparency. CONCLUSIONS: We identified high-quality websites that could be used to educate patients, families, or the public about delirium. While most delirium-related website content generally meets quality standards based on DISCERN and JAMA benchmark criteria, high scores do not always ensure patient and family-friendliness. Many of the top-rated delirium content were text-heavy and complex in layout, which could be overwhelming for users seeking clear, concise information. Future efforts should prioritize the development of websites with patients and families, considering usability, accessibility, and cultural relevance to ensure they are truly effective for delirium education.
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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 | 0.007 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".