Characterizing the content and quality of internet resources on exercise training in Ehlers-Danlos Syndromes and generalized hypermobility spectrum disorder
Bibliographic record
Abstract
BACKGROUND: Individuals with Ehlers-Danlos Syndromes (EDS) and Generalized Hypermobility Spectrum Disorder (G-HSD) experience musculoskeletal joint instability, cardiopulmonary manifestations, and functional limitations with online exercise resources commonly utilized. This study characterizes and assesses the content, quality, and readability of websites addressing exercise training for individuals with EDS/G-HSD. METHODS: The first 350 English websites were Googled using search terms "Ehlers-Danlos Syndrome and exercise" and "Ehlers-Danlos Syndrome and physical activity," targeting educational/instructional sites on exercise training for adults with EDS/G-HSD. Content was assessed using scientific consensus criteria, quality using Modified DISCERN, Global Quality Scale (GQS), and the Patient Education Materials Assessment Tool (PEMAT), and readability using Flesch-Kincaid Grade Level (FKGL) and Flesh-Reading Ease Scores (FRES). RESULTS: 78/350 unique websites were included, most from industry organizations (37%) and personal commentary (24%). The mean content score was moderate 13.8 ± 4.4/25. The content most discussed included: short/long-term benefits of muscle strength, resistance training, and generalized exercise safety considerations. Median modified DISCERN and GQS scores were 4/5 IQR [3-4] and 3/5[2.3-4], respectively. Mean PEMAT understandability and actionability scores were 85% ± 12% and 69% ± 23%, respectively. Average FKGL was 11.0 ± 2.7 and FRES was 43.6 ± 7.2. Moderate-strong Spearman correlations were observed between total content scores and GQS (rho = 0.76) and DISCERN (rho = 0.52), p < 0.001 for both. CONCLUSION: Website content varied, most addressing general safety recommendations and multiple training modalities. While quality was moderate-to-good, future resources should focus on simplified language, actionable guidance, and visual aids. Incorporating practical examples of daily activities, injury prevention strategies, broader benefits like cardiovascular health, and psychological support can empower safe and confident exercise training.
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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 | 0.003 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".