Evaluation of GERD Symptoms during Therapy. Part II
Bibliographic record
Abstract
BACKGROUND/AIMS: Evaluation of the response of gastroesophageal reflux disease (GERD) symptoms to treatment would be facilitated by a brief, valid, reliable and responsive, self-assessed GERD-sensitive scale. We therefore developed the Reflux Questionnaire (ReQuest). This publication describes the psychometric evaluation and validation of ReQuest. METHODS: This second phase of development was based on data from a clinical trial of patients with erosive GERD who received pantoprazole 20 or 40 mg daily for 28 days and completed weekly the long, and daily the short version of ReQuest. The psychometric analyses of ReQuest included internal consistency, test-retest reliability and responsiveness. Construct validity was evaluated by comparison with the Gastrointestinal Symptom Rating Scale (GSRS) and the Psychological General Well-Being (PGWB) scale. RESULTS: Validation of ReQuest indicated very high internal consistency (Cronbach's alpha = 0.90) and test-retest reliability (intraclass correlation coefficient 0.94 (long-long) and 0.86 (short-short)). This was also the case for the two subscales ReQuest-GI and ReQuest-WSO with Cronbach's alpha coefficients of 0.84 and 0.81. Responsiveness was high with a responsiveness index of >0.8 at day 28. Construct validity was good. CONCLUSION: ReQuest is a highly reliable, valid and responsive self-assessment tool for evaluating treatment response in patients with erosive GERD, and can be applied daily.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.006 | 0.002 |
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".