Assessing Quality of Life in Patients with Epidermolysis Bullosa in the Saudi Population: Validation of the QOLEB Questionnaire
Bibliographic record
Abstract
Background: Epidermolysis bullosa (EB) is a rare condition where skin easily blisters. Using an Arabic-translated Quality of Life in Epidermolysis bullosa (QOLEB) questionnaire, we evaluated quality of life across persons with EB in Kingdom of Saudi Arabia. Methods: Respondents were selected through nonprobability convenience sampling. Data were collected using a pre-validated questionnaire. We statistically compared response data across the four EB phenotypes using the Kruskal–Wallis test. Validity was assessed through confirmatory factor analysis and Cronbach’s alpha was used to evaluate reliability with results 0.88. Results: The study included 91 participants with Epidermolysis Bullosa (EB), comprising 60.4% of them were males. Adults and adolescents constituted 61.5% of the study sample. Children with EB faced more bathing challenges, with 64.3% always needing assistance compared to 31.4% of adults/adolescents. Writing adaptations varied significantly ( p =0.03), with children exploring alternatives like typing, while adults primarily struggled to hold a pen. Conclusion: Our findings underscore the profound physical, psychological, and social burdens associated with this rare condition, emphasizing the critical need for multidisciplinary care approaches. Addressing gaps in public awareness, improving access to specialized care, and providing psychosocial support for patients and their families are essential steps toward enhancing quality of life. Keywords: epidermolysis bullosa, quality of life, questionnaire, Saudi Arabia
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".