Temperament, character traits, and alexithymia in patients with panic disorder
Bibliographic record
Abstract
BACKGROUND: The primary aim of the present study was to compare temperament and character traits and levels of alexithymia between patients with panic disorder and healthy controls. METHODS: Sixty patients with panic disorder admitted to the psychiatry clinic at Fırat University Hospital were enrolled in the study, along with 62 healthy age-matched and sex-matched controls. The Structured Clinical Interview for DSM-IV axis I (SCID-I), Temperament and Character Inventory (TCI), Toronto Alexithymia Scale (TAS-20), and Panic Agoraphobia Scale (PAS) were administered to all subjects. RESULTS: Within the temperament dimension, the mean subscale score for harm avoidance was significantly higher in patients with panic disorder than in controls. With respect to character traits, mean scores for self-directedness and cooperativeness were significantly lower than in healthy controls. Rates of alexithymia were 35% (n=21) and 11.3% (n=7) in patients with panic disorder and healthy controls, respectively. The difficulty identifying feelings subscale score was significantly higher in patients with panic disorder (P=0.03). A moderate positive correlation was identified between PAS and TAS scores (r=0.447, P<0.01). Moderately significant positive correlations were also noted for PAS and TCI subscale scores and scores for novelty seeking, harm avoidance, and self-transcendence. CONCLUSION: In our study sample, patients with panic disorder and healthy controls differed in TCI parameters and rate of alexithymia. Larger prospective studies are required to assess for causal associations.
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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) | 0.001 | 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".