Evaluatıon of Alexıtımıa Level in Cystıc Fıbrosıs Patıents
Bibliographic record
Abstract
Introduction: Alexithymia, which is defined as the difficulty in recognizing, recognizing, distinguishing and expressing emotions, is a term that has emerged in the clinical field. Although it is controversial whether alexithymia is a personality trait or a symptom associated with mental problems, it is known that alexithymia is associated with the symptoms of physical and mental health problems. In this study, we planned to measure the alexithymia level of cystic fibrosis patients followed in our clinic. Material-Method: Patients aged 5-18 years who were followed up with the diagnosis of Cystic Fibrosis (CF) in the Pediatric Chest Diseases Outpatient Clinic of the Meram Medical Faculty Hospital were included in the study. Patients younger than 5 years old and patients older than 18 years were excluded from the study. Patients filled out a questionnaire including sociodemographic characteristics and Toronto Alexithymia Scale. Results: This study included 22 girls (46.8%) and 25 (53.2%) boys. According to the Toronto Alexithymia scale, the total score of the children with CF was 57.45±9.8, the difficulty of recognizing emotion sub-score of the scale was 16.61±6.19, the difficulty of expressing emotions was 13.73±3.45, and the extroverted thinking sub-score was 27.12±3.24. The alexithymia total score of 12 children (25.5%) was above 60 points. A total of 23 children (48.9%) had a total scale score above 50. Discussion: It is known that children with chronic diseases may have difficulties in recognizing and expressing their emotions. In this study, it was observed that children with CF had difficulties in recognizing and expressing emotions, and their expressive thoughts increased.
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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".