Alexithymia and Functional Gastrointestinal Disorders (FGID)
Bibliographic record
Abstract
NTRODUCTION: The purpose of this study was to examine alexithymia symptoms, demographic variables and the severity of gastrointestinal symptoms in a sample of patients with functional gastrointestinal disorders (FGID) and a comparative sample of healthy controls. MATERIALS AND METHODS: The sample consisted of 237 individuals, 129 of whom were patients diagnosed with FGIDs. The patients referred to the psychosomatic disorders clinic_of Nour Hospital, Isfahan, Iran. The controlled group included 108 healthy individuals (without digestive diagnosis) matched with the patients by age, gender, marital and educational status. The Toronto Alexithymia Scale (TAS-20) and the Gastrointestinal Symptoms Rating Scale (GSRS) were used to collect data. Data was analyzed using multivariate analysis of variance (MANOVA), correlation coefficients and Fisher's z. RESULTS: There was a significant difference between patients with FGIDs and healthy controls in terms of number of alexithymia symptoms and severity of gastrointestinal symptoms. The results also indicated the existence of a relationship between educational level and alexithymia as well as its dimensions (difficulty identifying feelings and difficulty describing feelings) in both groups. However, no significant differences were found between the two groups in this regard. CONCLUSION: The findings of this study indicated that compared to the healthy control group, patients with FGIDs had higher scores of alexithymia and more severe somatic symptoms. Furthermore, higher educational levels were associated with decreased risk of alexithymia. Such finding might be due to higher ability to describe and identify emotions in patients with higher levels of education.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| 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".