Relative stability of alexithymia and openness to emotions in one psychiatric day hospital setting
Bibliographic record
Abstract
Alexithymia (literally, difficulty finding words for emotions) and openness to emotions (OE: referring to the cognitive representation, communication, regulation, perception of internal and external bodily sensations, and social restriction of emotions) are strongly linked to psychopathology. The absolute and relative stability hypotheses were tested in order to determine whether significant changes occurred on these constructs after therapy, a condition where changes were expected for both constructs. Negative attitudes toward treatment (NTI) and perceived social support (PSS) were expected to significantly predict alexithymia and OE. Patients (N = 179) who participated in this longitudinal study filled in the Toronto Alexithymia Scale, the Dimensions of Openness to Emotions Scale, the NTI subscale, the Multidimensional Scale of Perceived Social Support, and the Social Desirability Scale. After treatment, we observed significant decrease of all alexithymia scores and significant increases of three OE scores, that is, cognitive representation, communication, and regulation of emotions. Regression analyses revealed that gender, age, NTI, and PSS were significant predictors of alexithymia and OE. NTI strongly predicted lower OE levels and higher alexithymia levels, whereas PSS had opposite predicting effects on these constructs. In conclusion, the significant changes, and the moderate to high correlational levels observed between before and after alexithymia and OE scores, strengthen the relative stability hypothesis for both constructs. In addition, PSS represents a protective factor and NTI a vulnerability indicator for therapists. Our aim is to optimize treatment by providing therapists treating emotion difficulties a more concrete array of variables that potentially either promote or subvert recovery.
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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 | 0.004 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".