Alexithymia and Severe Psychopathology: A Study on Psychiatric Inpatients
Bibliographic record
Abstract
BACKGROUND: The influence of severe psychopathology on alexithymic features has been poorly studied. This study aimed at investigating whether alexithymia is affected by the presence of psychosis and the severity of psychopathology. SAMPLING AND METHODS: 199 consecutive adult psychiatric inpatients, 60 of whom received a Structured Clinical Interview for DSM-IV Axis I diagnosis of psychotic disorder, were administered the 20-item Toronto Alexithymia Scale (TAS-20) and the 24-item Brief Psychiatric Rating Scale (BPRS). A random sample of 50 patients was reassessed at discharge. For all analyses, the Holm-Bonferroni correction was applied when appropriate to account for multiple testing. RESULTS: The TAS-20 showed good internal consistency, acceptable relative stability, and good absolute stability both in patients with and without a psychotic disorder. Internal consistency and relative stability were higher in nonpsychotic than in psychotic patients. Mean TAS-20 score at admission did not differ between psychotic and nonpsychotic patients, and the TAS-20 score showed only a nonsignificant correlation (rho = 0.26) with BPRS score. Alexithymia at discharge was mostly explained (60%) by alexithymia at admission, while it was only modestly explained (4%) by BPRS scores at admission and discharge, with the latter being the only significant predictor. Changes in BPRS scores between admission and discharge explained a nonsignificant proportion (16%) of changes in TAS-20 scores and a moderate (21%) proportion of changes in difficulty identifying feelings. CONCLUSION: Despite some limitations, these findings suggest that the severity of psychopathology and the presence of a psychotic disorder only modestly influence alexithymic characteristics, and that the TAS-20 may provide a reliable assessment of alexithymia in patients with severe psychopathology, except the most severely impaired ones.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".