Relationship between alexithymia and coping strategies in patients with somatoform disorder
Bibliographic record
Abstract
PURPOSE: A multidimensional intervention integrating alexithymia, negative affect, and type of coping strategy is needed for the effective treatment of somatoform disorder; however, few studies have applied this approach to the three different dimensions of alexithymia in patients with somatoform disorder. The purpose of this study was to determine the relationship between type of coping strategy and three different dimensions of alexithymia expressed in patients. PATIENTS AND METHODS: A total of 196 patients with somatoform disorder completed the 20-item Toronto Alexithymia Scale, the Zung Self-Rating Depression Scale, the Spielberger State-Trait Anxiety Inventory, the Somatosensory Amplification Scale, and the Lazarus Stress Coping Inventory. The relationships between alexithymia (Toronto Alexithymia Scale - 20 score and subscales), demographic variables, and psychological inventory scores were analyzed using Pearson's correlation coefficients and stepwise multiple regression analysis. RESULTS: The mean Toronto Alexithymia Scale - 20 total score (56.1±10.57) was positively correlated with the number of physical symptoms as well as with psychopathology scores (Self-Rating Depression Scale, State-Trait Anxiety Inventory trait, state, and Somatosensory Amplification Scale), but negatively correlated with planful problem solving, confrontive coping, seeking social support, and positive reappraisal coping scores. With respect to coping strategy, multiple regression analyses revealed that "difficulty in identifying feelings" was positively associated with an escape-avoidance strategy, "difficulty in describing feelings" was negatively associated with a seeking social support strategy, and "externally oriented thinking" was negatively associated with a confrontive coping strategy. CONCLUSION: Alexithymia was strongly associated with the number of somatic symptoms and negative affect. Patients with high "difficulty in describing feelings" tend to rely less on seeking social support, and patients with high "externally oriented thinking" tend to rely less on confrontive coping strategies. The coping skills intervention implemented should differ across individuals and should be based on the alexithymia dimension of each patient.
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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 | 0.000 | 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) | 0.001 | 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".