Alexithymia and Dissociative Experiences in a Sample of Patients with Alcohol use Disorder
Bibliographic record
Abstract
Aims: Aims of this study were to investigate alexithymic traits and dissociative experiences in a sample of patients with Alcohol Use Disorders, the significance of this association and the possible correlation with temperamental and character personality traits. Methods: Eighty patients with diagnosis of Alcohol Use Disorder (DSM-IV) were consecutively recruited and assessed with the Toronto Alexithymia Scale-20 (TAS-20), to evaluate the alexithymic traits, the Dissociative Experience Scale II (DES II), to investigate the possible presence of dissociative experiences, and the Temperament and Character Inventory - Revised (TCI-R) in order to define a personality profile. Results: The mean scores obtained by the experimental group in both the TAS-20 and DES II do not differ from those estimated during the validation procedure. Pearson's linear correlation between scores was found statistically significant (p < .05). Significant correlations with some personality dimensions have also been found. Conclusions: According to some authors substances related disorders could be classified as “disturbs of emotional regulation”, an active process in which neurophysiological, motor-behavioural and cognitive-experiential systems are involved. The lack of connection or an inadequate development of these systems would result in the malfunction of the symbolic function and then in the inability for the subject to contain the tensions generated by internal needs and/or by environmental stimulations. Both alexithymia and dissociation may assume the form of defence mechanisms against the unbearable emotions. Finally, some personality factors may be involved both in the rise of dissociative states and in the alexithymic traits.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".