Alexithymia and Personality in Relation to Dimensions of Psychopathology
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: The authors examined the capacity of alexithymia to predict a broad range of psychiatric symptoms relative to that of other personality dimensions, age, and gender. METHOD: The Toronto Alexithymia Scale, the Temperament and Character Inventory, and the SCL-90-R were administered to 254 psychiatric patients. Multivariate linear regression analyses were performed. RESULTS: The difficulties identifying feelings factor of the Toronto Alexithymia Scale significantly predicted all SCL-90-R subscale scores and was particularly effective, relative to the personality dimensions of the Temperament and Character Inventory, in predicting somatization. The Temperament and Character Inventory dimensions emerged as distinct and conceptually meaningful predictors for the different SCL-90-R subscales. CONCLUSIONS: A broad range of current psychopathology is associated with difficulties in cognitively processing emotional perceptions. Further research needs to clarify whether alexithymia represents a risk factor for mental illness and poorer outcome.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 it