Association of Alexithymia With Positive Symptoms in Chinese Chronic Schizophrenia Patients With and Without Obesity
Bibliographic record
Abstract
OBJECTIVE: A growing body of research suggests the presence of alexithymia (a form of social cognitive impairment) in patients with schizophrenia (SCZ), which may be related to their psychopathological symptoms. Patients with SCZ exhibit high rates of obesity. Interestingly, studies of the general population have found that alexithymia acts a pivotal role in the development and maintenance of obesity. However, little is known regarding the relationship between obesity, alexithymia, and clinical symptoms in SCZ patients. The study was aim to explore the relationship between obesity, alexithymia, and clinical symptoms in SCZ patients. METHODS: Demographic and clinical data were collected from 507 patients with chronic SCZ. Their symptoms were assessed with the Positive and Negative Syndrome Scale (PANSS), and alexithymia was assessed with the Toronto Alexithymia Scale (TAS). RESULTS: Compare with nonobese SCZ patients, obese SCZ patients scored higher on PANSS positive symptoms, TAS total score, difficulty identifying feelings, and difficulty describing feelings (all p<0.05). Correlation analysis revealed a significant association between difficulty identifying feelings and positive symptoms in SCZ patients. Further correlation analysis showed that this association was only present in obese SCZ patients (p<0.05). CONCLUSION: Obesity may moderate the association between alexithymia and positive symptoms in chronic SCZ patients.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".