Communicating with Alexithymic and Non-Alexithymic Patients: An Experimental Study of the Effect of Psychosocial Communication and Empathy on Patient Satisfaction
Bibliographic record
Abstract
BACKGROUND: Previous studies have shown that alexithymia is associated with a wide range of somatic and psychiatric conditions. The aim of this study was to investigate experimentally how psychosocial communication and empathic response from the physician affects satisfaction in alexithymic and non-alexithymic patients. METHOD: Seven physicians and 65 female patients from a fibromyalgia patient association participated in the study. The Toronto Alexithymia Scale (TAS-20) was used to categorise patients as alexithymic or non-alexithymic. Patients also completed questionnaires regarding trait anxiety and satisfaction with their consultation. Physicians were instructed to differentiate their communication in terms of both psychosocial matters and empathic response. The content of the consultation was analysed using the Roter Interactional Analysis System. RESULTS: Regression analyses revealed that alexithymic patients were significantly more satisfied when they received a greater empathic response from the physician. Non-alexithymic patients, however, were more satisfied when the consultation was of longer duration. Psychosocial communication did not have any statistically significant effect on satisfaction in either of the two subgroups. CONCLUSIONS: Verbalised empathic response from the physician may be crucial for the alexithymic patient's post-consultation satisfaction and may thereby become the basis for a solid treatment alliance. The validity of this hypothesis should be tested in different clinical settings and with different patient populations. Future research on alexithymic patients' response to psychosocial communication may benefit from determining to what extent this communication is concerned with general distress or more complex emotional phenomena.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".