Alexithymia, empathy, negative affect and physical symptoms in patients with asthma
Bibliographic record
Abstract
Although alexithymia has been found to be associated with physical symptoms in psychosomatic disorders such as asthma, mechanisms linking this association are unknown. However, affective alexithymic features may be associated with physical symptoms in the presence of deficits in affective characteristics such as low empathy and high negative affect. This study aimed to assess direct effects of alexithymic traits on physical symptoms and indirect effects of these subscales through empathy and negative affect (e.g. depressive, anxious and stress symptoms) by controlling for asthma severity in patients with asthma. Three hundred patients with asthma completed the Toronto Alexithymia Scale-20 (TAS-20), the Basic Empathy Scale (BES), the Depression Anxiety Stress Scales-21 (DASS-21) and the Physical Symptoms Inventory (PSI). After controlling for asthma severity, the results showed that alexithymia subscales of the TAS-20 had no direct effects on physical symptoms, but the difficulty in identifying feelings (DIF) subscale of the TAS-20 was associated with affective empathy and negative affect. Affective empathy was significantly related to negative affect. Affective empathy and negative affect were associated with physical symptoms. The affective subscale of alexithymia on the TAS-20, that is DIF, indirectly affected physical symptoms through affective empathy and negative affect. Findings suggest that patients with asthma who have high levels of DIF may show high physical symptoms in the presence of low affective empathy and high negative affect.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".