Identifying Psychological Intervention Points for Alexithymia Based on the Process of Emotional Expression
Bibliographic record
Abstract
Abstract Background: Alexithymia is a central concept in the field of psychosomatic disease. Patients afflicted with alexithymia have difficulties identifying feelings preventing them from responding well to psychotherapy. This study aims to evaluate in detail which steps of emotional expression (Steps 1–5) proposed by Kennedy-Moore et al. (Kennedy-Moore E and Watson JC. Expressing emotion. In: Salovey P, editor. Expressing Emotion. New York: Guilford; c1999. p. 8-18) are disrupted in alexithymia to enable the administration of effective treatment to such patients and identify appropriate methods of intervention for each step. Methods: To investigate the relationship between the Japanese version of the Difficulties in Emotion Regulation Scale (J-DERS) total score and subscales and the 20-item version of the Toronto Alexithymia Scale (TAS-20) subscales, multiple linear regression was performed using the former as dependent variables. The psychological examination records of eligible patients were retrospectively investigated. To evaluate the effect of alexithymia on each step of the process of emotional expression, the scores on the total and subscale J-DERS of the group that scored high on TAS-20 were compared with those of the group that scored low on TAS-20. Results: Of the 188 total subjects, 106 (56%) were included in the analysis. The median total J-DERS score was significantly different (p < 0.01) between the high-scoring group (defined as 52 points or higher) and the low-scoring group on the TAS-20, with a median score of 42.0 (interquartile range (IQR) 52.8 [upper limit]–31.0 [lower limit]) and 29.5 (IQR 37.3–23.0), respectively. Similarly, a significant difference was seen with each subscale (p < 0.01). Thus, disruption of the process of emotional expression in alexithymic patients is not only observed in Step 3 but also in Steps 4 and 5. Of the three TAS-20 subscales, only difficulty in identifying feelings correlated with the J-DERS total score and subscales (p < 0.01).Conclusions: The results indicate that, when dealing with alexithymic patients individually in a clinical setting, therapeutic intervention should be adapted to Steps 3, 4, and 5 as appropriate for the patient, and that assessing each step using J-DERS may be more clinically useful.
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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 | 0.001 | 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".