Relationship between behavioral disorders and quality of life in patients with celiac disease.
Bibliographic record
Abstract
Background: Celiac disease (CD) has an autoimmune disease in response to ingestion of foods containing gluten sausing damage to the mucosal tissue of small intestine. The disease can severely affect quality of life. This study aims to assess the relationship between behavioral disorders and quality of life (QOL) in patients with celiac disease. Materials and Methods: 87 celiac patients and 100 healthy individuals are selected and matched for age, sex and education. Patients with Celiac disease were recruited from a subspecialty clinic in Imam Reza (AS) Hospital and clinic in Ghaem in Mashhad. The control group consisted of healthy participants. Participants completed the Beck Depression Inventory, State Anxiety Inventory-Trait Spielberger, Toronto Alexithymia Questionnaire and SF-36 Quality of Life Questionnaire. Research data were analyzed by Pearson correlation and multiple regression analyses. Results: There was no significant difference between the two groups in demographic variables. However significant differences existed between the variables of anxiety, depression and alexithymia. The patient group had higher depression and anxiety levels compared to healthy controls. Multiple regression analysis showed behavioral disorders, explains 43% of the variance in quality of life in patients with CD. Conclusion: Overall, the findings indicate there is a direct link between behavioral disorder and reduced quality of life of celiac patients. Psychotherapy and cognitive behavioral therapy can improve emotional patterns and cognition of celiac 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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".