A correlation study of emotion recognition, alexithymia and flat affect in schizophrenic patients
Bibliographic record
Abstract
ObjectiveTo analyze the correlation between the facial emotion deficits and alexithymia or flat affect in patients with schizophrenia. MethodsEighty-two schizophrenic patients and eighty-eight healthy subjects were tested with the Chinese Facial Emotion Test (CFET)and Toronto Alexithymia Scale(TAS-26),and rated on the flatten affective subscale of the SANS. ResultsFor patients with schizophrenia, the total correct score and scores of recognition for each of six basic emotions were significantly less(P<0.01), and the scores of factor I, II, or IV on TAS-26 were significantly more (P<0.01)than that of controls. There was a significantly negative correlation between scores of CFET and the scores of factor I, II, or IV on TAS-26, in which 27 of 35(71.4%) correlation coefficients reach statistic significance. and also a significantly negative correlation between some scores of CFET and flatten affective subscale of the SANS, in which 9 of 49 (18.4%) correlation coefficients reach statistic significance. There was no significant correlation between scores of TAS-26 and subscales of symptom, apart from subscale of eye attach. ConclusionThe impairment of facial emotion recognition as well as alexithymia indicated a special trait in schizophrenics. both of two symptoms may be involved in a common neural substrates, while the dissociation between alexithymia and flatten affection may suggested a different pathological emotion processing. Key words: Emotion recognition; Alexithymia; Flat affect; Schizophrenia
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".