Psychometric testing of the ICECAP-A in patients with coeliac disease: a comparative analysis with EQ-5D-5L
Bibliographic record
Abstract
OBJECTIVES: This study aimed to assess the psychometric properties of the ICEpop CAPability measure for Adults (ICECAP-A) in patients with coeliac disease (CD) and compare its performance with EQ-5D-5L. METHODS: An online cross-sectional survey was conducted among 312 adult patients with CD in Hungary, who completed both the ICECAP-A and EQ-5D-5L. Psychometric properties assessed included distributional characteristics, convergent validity with the Gastrointestinal Symptom Rating Scale (GSRS), Satisfaction with Life Scale (SWLS), and known-group validity. RESULTS: Mean age was 35.8 years (range: 18-80), and 70.2% were female. On the ICECAP-A, 51% (attachment) to 81% (stability) of patients reported limitations, while on the EQ-5D-5L, 2% (self-care) to 41% (pain/discomfort) reported problems. Ceiling effect was not observed for the ICECAP-A (6.7%), but reached 38.8% for EQ-5D-5L. The mean index value was 0.85 for the ICECAP-A and 0.92 for the EQ-5D-5L. ICECAP-A correlated strongly with SWLS (r=0.698), moderately with EQ-5D-5L (r=0.551) and weakly with GSRS (r=-0.284). Both the ICECAP-A and EQ-5D-5L were able to differentiate between known groups based on general health status and relevant clinical variables (e.g. symptoms, comorbidities, duration on gluten-free diet and adherence to it); however, the EQ-5D-5L typically showed somewhat larger effect sizes. CONCLUSION: This study is the first to validate ICECAP-A in patients with CD, demonstrating good psychometric performance, including strong convergent and known-group validity. Its ability to capture broader aspects of well-being supports its use as a valuable tool in outcome assessments for this patient population.
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| 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".