Association analysis between illness behavior and alexithymia in patients with panic disorder
Bibliographic record
Abstract
Objective To explore the relationship between the illness behavior and alexithymia of patients with panic disorder. Methods Forty-seven patients with panic disorder participated the study. Toronto Alexithymia Scale(TAS) was used to assess mood expression and Illness Behavior Questionnaire(IBQ) to evaluate the illness behavior. Results The subscale scores of general hypochondriasis,affective inhibition,affection state in IBQ were significantly positively correlated with subscales scores of I and Ⅱ in TAS,but negatively with subscale score of Ⅲ. The subscale score of affective disturbance was significantly positively correlated with subscale I score,but negatively with subscale Ⅲ score. The subscale score of irritability was significantly positively correlated with subscal I score. The subscale score of disease conviction was significantly positively correlated with the subscale scores of I and Ⅱ. The subscales scores of disease affirmation and whitely index of hypochondriasis were significantly positively correlated with the subscale I score. The subscale score of denial was significantly negatively correlated with the subscale scores of I and Ⅱ. There were no significant correlation between the subscale score of psychological versus somatic perception of IBQ and all subscale scores and total score of TAS. Conclusion The illness behavior in patients with panic disorder is associated with deficiency in the ability of describing emotion ,recognizing and making distinguish between emotion and body feeling.
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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 | 0.000 |
| 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".