S675 Development and Validation of a Novel Self-Report Mental Health Scale for Patients With Gastroduodenal Disorders of Gut-Brain Interaction: The Alimetry Gut-Brain Wellbeing Survey
Bibliographic record
Abstract
Introduction: Patients with gastroduodenal disorders of gut-brain interaction (DGBIs) often experience psychological comorbidity, highlighting the bidirectional relationship between psychological factors and gastrointestinal symptoms. Consequently, it is recommended that clinicians routinely evaluate the mental wellbeing of these patients as part of standard care. However, no mental wellbeing scale has been developed specifically for this patient population. This research describes the multi-phase process used to develop and validate a novel mental wellbeing scale for patients with gastroduodenal DGBIs. Methods: A patient-centred co-development process was implemented, employing a multi-phase mixed-methods approach. In Phase 1, the most relevant concepts for this patient population were selected from existing mental health scales, utilising data collected from a sample of 79 patients with gastroduodenal DGBIs. During Phase 2, an interdisciplinary team of experts generated scale items based on the identified concepts and existing literature. In Phase 3, the scale underwent pre-testing with external gastroenterologists (n=9), health psychologists (n=3), and patients with gastroduodenal DGBIs (n=12). Feedback was incorporated through multiple rounds to refine the scale. Lastly, in Phase 4, the psychometric properties of the final scale were assessed in a sample of 182 patients via an online survey. Results: The final Alimetry Gut-Brain Wellbeing (AGBW) Survey comprises a patient preface, 10 close-ended questions, and a final optional open-ended question. This multi-dimensional scale can be used to assess general mental wellbeing, alongside specific subscales relating to depression, stress, and anxiety. Cronbach’s alpha coefficients were 0.91 for the total scale and ranged from 0.72-0.87 for the subscales, indicating high internal consistency. Comparisons with other validated questionnaires demonstrated good convergent, divergent, concurrent, and known-groups validity of the total score and subscale scores. Conclusion: The AGBW Survey is a brief, novel scale, developed to assess mental wellbeing in patients with gastroduodenal DGBIs. It serves as a valuable tool to complement physiological tests, enabling the routine assessment of mental wellbeing in these patients. The AGBW Survey has the potential to guide psychological referrals, inform multidisciplinary management plans, and evaluate treatment outcomes in both clinical and research settings.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".