Alexithymia in chronic gastrointestinal and hepatologic diseases
Bibliographic record
Abstract
Alexithymia, a multifaceted personality construct that represents a deficit in the cognitive processing of emotions, is currently understood to be related to a variety of medical and psychiatric conditions. In the present paper, the relationship of alexithymia with chronic gastrointestinal (GI) disorders as functional gastrointestinal disorders (FGID, as irritable bowel syndrome (IBS) and functional dyspepsia) and inflammatory bowel disease (IBD) [ulcerative colitis (UC) and Crohn’s disease (CD)] and liver diseases as chronic hepatitis C (CHC), cirrhosis, and liver transplantation. Alexithymia is mostly investigated with the 20-item Toronto Alexithymia Scale (TAS-20) and the studies reviewed in this paper are those that used this scale for allowing cross-comparisons. The prevalence of alexithymia is higher in FGID (more than two third of patients) than IBD and liver diseases (from one third to 50% of patients, consistent with other chronic non-GI diseases) than general population (10–15%). The role of alexithymia in the different disorders is partly overlapping and partly distinct. In functional GI disorders, alexithymia may be viewed as a primary driver for higher visceral perception, symptom reporting, health care use, symptom persistence, and negative treatment outcomes, even when a comorbid GI condition as cholelithiasis and UC is present. Also, it has been found associated with psychological distress and specific GI-related forms of anxiety in predicting symptom severity as well as post-treatment outcomes and is associated with several psychological factors increasing the burden of disease and impairing levels of quality of life. In chronic GI diseases, alexithymia may predict somatization symptoms, even independently of the primary medical condition, likely because of difficulty identifying and communicating the underlying distress emotions.
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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 | 0.001 |
| Research integrity | 0.000 | 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".