Relationship between Alexithymia, Dissociation and Personality in Psychiatric Outpatients
Bibliographic record
Abstract
BACKGROUND: The relationship between alexithymia and dissociation is not known. Both mechanisms ward off overwhelming affective states; hence, this report examines the relationship between dissociation, alexithymia, depressed mood and the five-factor model of personality in a sample of psychiatric outpatients. METHODS: One hundred and sixteen outpatients were evaluated using the Toronto Alexithymia Scale (TAS), the Dissociative Experiences Scale (DES), NEO Five-Factor Inventory and visual analog scales assessing depression and anxiety. Data was analyzed using multivariate analysis of variance, logistic regression and linear regression techniques. RESULTS: Depressed mood accounted for the group differences between the global TAS and DES scores. Using DES both dimensionally and categorically with regression models, there was minimal contribution of DES or its subfactors to predict TAS. CONCLUSIONS: These data reaffirm previous findings that dissociation fundamentally differs from alexithymia. Dissociation involves a change of one's sense, of self, whereas alexithymia reflects a cognitive state of externally oriented thinking with an inability to identify and report discrete emotions.
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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 | 0.003 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".