Effectiveness of Cognitive-Analytical Therapy on Alexithymia and Interpersonal Problems in Patients with Functional Dyspepsia
Bibliographic record
Abstract
Cognitive-Analytical Therapy (CAT) appears to be a suitable approach for intervening in the improvement of interpersonal problems in individuals with psychosomatic disorders. The present study aimed to determine the effectiveness of Cognitive-Analytical Therapy on alexithymia and interpersonal problems in patients with functional dyspepsia. The present study employed a quasi-experimental method with a pretest, posttest, and follow-up design, along with a control group. The statistical population consisted of patients with functional dyspepsia who visited the gastroenterology clinic of Shariati Hospital in Tehran in 2021, from which 30 eligible volunteers were selected through convenience sampling and randomly assigned to two groups: the "Cognitive-Analytical Therapy" group and a control group. Research tools included a demographic questionnaire, the Toronto Alexithymia Scale and the Inventory of Interpersonal Problems-32. The content validity of the tools was measured qualitatively, and their reliability was assessed using internal consistency by calculating Cronbach’s alpha. After conducting 16 therapeutic sessions for the intervention group, the data were collected and analyzed using SPSS software version 26. In the present study, there was a significant difference between the pretest, posttest, and follow-up scores for both variables (P = .001). There was also a significant difference between the intervention and control groups for both alexithymia (P = .001, F = 69.938) and interpersonal problems (P = .001, F = 70.598). The results indicated that Cognitive-Analytical Therapy is effective in reducing alexithymia and interpersonal problems in patients with functional dyspepsia. It is recommended that, in addition to medical treatments, psychotherapy interventions such as "Cognitive-Analytical Therapy" be provided for patients with functional dyspepsia.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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".