The Readability of Online Educational Materials for Femoroacetabular Impingement Syndrome
Bibliographic record
Abstract
Although the readability of online materials has been thoroughly studied across different orthopaedic surgery disorders, inadequacy in information exists regarding the readability of the websites pertaining to femoroacetabular impingement (FAI). Given its high prevalence and the importance of providing appropriate online education materials in its prognosis, the primary aim of this study was to assess the readability of web-based patient education materials regarding this disease. “Femoroacetabular impingement,” “FAI,” and “hip impingement” were used as search queries in this study. Readability was evaluated based on five established algorithms, and the readability of contents was compared by website type and also search query. In this study of 59 unique websites on FAI, using five different validated readability formulas, we demonstrated that none of the top 30 webpages were written at the recommended reading level. They were found through three different search queries on the three most used search engines. Current FAI online education materials accessible to patients are written above the recommended levels, and it seems that to improve equity and accessibility in healthcare, universities, hospitals, and healthcare professional societies have a responsibility to ensure that the online materials are provided at more appropriate levels. Early detection and treatment of FAI play a key role in preventing the progression to hip osteoarthritis. Thus, providing appropriate online education materials is of great importance in this prevention by increasing patients' understanding of the disease and the advantages and disadvantages of the treatment options. Level of Evidence: Level III
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 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 | 0.074 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.007 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".