Alexithymic Characteristics and Patient-Therapist Interaction: A Video Analysis of Facial Affect Display
Bibliographic record
Abstract
Alexithymia as a disorder of affect regulation entails a patient's reduced ability to process emotional information. The purpose of this study was to evaluate the impact of alexithymia [as measured by the Toronto Alexithymia Scale (TAS)-26, German version] on affective correlates in a dyadic therapeutic interaction (as recorded by the Emotional Facial Action Coding System). Interviews with 12 in-patients with various psychosomatic disorders (anxiety, depression, somatisation) were videotaped and evaluated for facial affect display. The corresponding emotional reactions of the therapists (split screen) were recorded separately. Patients with high alexithymia scores (TAS-26 total score) tended to display less aggressive affects than those with low scores. The therapists' predominant emotional reaction to alexithymic patients was contempt. Our findings underscore the deep-rooted nature of alexithymia as a disorder of affect regulation. Since facial affects play a major role in the regulation of emotional interaction, this disorder may evoke negative reactions of potential caregivers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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) | 0.002 | 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".