Assessment of the Readability, Adequacy, and Suitability of Online Patient Education Resources for Benign Vascular Tumours Using the DISCERN Instrument
Bibliographic record
Abstract
OBJECTIVE: This study aims to assess the quality and readability of Internet-based patient resources for vascular tumours in order to understand which areas require improvement. METHODS: A World Wide Web search was performed, in addition to a literature review using PubMed, Ovid MEDLINE, and EMBASE. Any material that contained information on vascular tumours pertaining to patient education was included. We evaluated resources with DISCERN and Flesch Reading Ease scores when applicable. The language of publication was restricted to English and French. This review was registered with PROSPERO (CRD42018087885). RESULTS: A total of 117 online resources were screened, with 73 resources included in the final analysis. The overall DISCERN rating for the patient resources was 1.8 (0.8). The majority of online resources failed to depict the entire spectrum of benign vascular tumours. The mean Flesch score was 36 (19), which translates to a college-level readability. CONCLUSION: The majority of resources were not adequate or comprehensive and were written at a much higher level than the average reader would be expected to comprehend.
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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 | 0.009 | 0.052 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.008 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".