Quality and readability of online information on idiopathic subglottic stenosis
Bibliographic record
Abstract
Abstract Objective Idiopathic subglottic stenosis (ISS) is a chronic condition characterized by disease recurrence and multiple surgeries. These frustrated patients may utilize the internet to research their condition. The aim of this study was to determine the quality and readability of online ISS information. Methods “Idiopathic subglottic stenosis” was entered into Google. The first 50 websites that met inclusion criteria were extracted. The DISCERN instrument, Flesch Reading Ease Score (FRES), and Flesch‐Kincaid Grade Level (FKGL) assessed the quality and readability, respectively. Means, SDs, Pearson correlation coefficients, and two‐tailed Student's t ‐test were calculated. Results The 50 websites consisted of 17 patient‐targeted and 33 professional‐targeted websites, plus 30 major and 20 minor websites. The overall DISCERN, FRES, and FKGL scores were 2.81 ± 0.99, 27.75 ± 15.27, and 13.65 ± 2.79, respectively (mean ± SD). Patient‐targeted websites had significantly lower quality (DISCERN [ P < .00]) but were easier to read (lower FKGL [ P < .00], higher FRES [ P < .00]) than professional‐targeted websites. Minor websites had a significantly lower quality (DISCERN [ P < 0.00]) but were easier to read (lower FKGL [ P < .00], higher FRES [ P < .00]) than major websites. There was a positive correlation between overall quality and difficulty in readability. Conclusion The quality of online ISS information was suboptimal. Resources were too difficult to comprehend and readability scores were above AMA and NIH recommendations. Improved online information is required to properly educate this patient population. Level of Evidence Level 4.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".