Development and validation of a condition-specific quality of life instrument for adults with esophageal atresia:the SQEA questionnaire
Bibliographic record
Abstract
The importance of multidisciplinary long-term follow-up for adults born with esophageal atresia (EA) is increasingly recognized. Hence, a valid, condition-specific instrument to measure health-related quality of life (HRQoL) becomes imperative. This study aimed to develop and validate such an instrument for adults with EA. The Specific Quality of life in Esophageal atresia Adults (SQEA) questionnaire was developed through focus group-based item generation, pilot testing, item reduction and a multicenter, nationwide field test to evaluate the feasibility, reliability (internal and retest) and validity (structural, construct, criterion and convergent), in compliance with the consensus-based standards for the selection of health measurement instruments guidelines. After pilot testing (n = 42), items were reduced from 144 to 36 questions. After field testing (n = 447), three items were discarded based on item-response theory results. The final SQEA questionnaire (33 items) forms a unidimensional scale generating an unweighted total score. Feasibility, internal reliability (Cronbach’s alpha 0.94) and test–retest agreement (intra-class coefficient 0.92) were good. Construct validity was discriminative for esophageal replacement (P < 0.001), dysphagia (P < 0.001) and airway obstruction (P = 0.029). Criterion validity showed a good correlation with dysphagia (area under the receiver operating characteristic 0.736). SQEA scores correlated well with other validated disease-specific HRQoL scales such as the GIQLI and SGRQ, but poorly with the more generic RAND-36. Overall, this first condition-specific instrument for EA adults showed satisfactory feasibility, reliability and validity. Additionally, it shows discriminative ability to detect disease burden. Therefore, the SQEA questionnaire is both a valid instrument to assess the HRQoL in EA adults and an interesting signaling tool, enabling clinicians to recognize more severely affected patients.
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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 | 0.012 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".