Bibliographic record
Abstract
Objectives \nFormal thought disorder has been regarded as an essential symptom in the diagnostic criteria for schizophrenia. The aim of our study was to present gender differences in the formal thought disorder among patients with schizophrenia. \n \nMethods \nWe tested for potential gender differences in the formal thought disorder among 167 inpatients with schizophrenia (86 men and 81 women). The Scale for the Assessment of Thought, Language and Communication (TLC scale), Clinical Language Disorder Rating Scale (CLANG), Brief Psychiatric Rating Scale, Young Mania Rating Scale, and Calgary Depression Scale for Schizophrenia were used for evaluation of thought disorder, language disorder, overall symptoms, manic symptoms, and depressive symptoms, respectively. Using the analysis of covariance for continuous variables and logistic regression analysis for discrete variables, gender differences in the formal thought disorder were evaluated. \n \nResults \nAfter adjusting for the effects of marital status and religious affiliation, men showed a significantly higher score on the perseveration (TLC scale ; F=7.538, p=0.007), blocking (TLC scale ; F=8.956, p=0.003), stilted speech (TLC scale ; F=6.921, p=0.009), lack of details (CLANG ; F=7.375, p=0.007), dysfluency (CLANG ; F=21.250, p<0.0001), and dysarthria (CLANG ; F=31.198, p<0.0001) items than women. \n \nConclusion \nOur study has a virtue of exploring gender differences in the formal thought disorder in patients with schizophrenia. Based on our findings, further study might enlighten regarding neural correlates (namely, cerebral asymmetry/lateralization) for gender-differed patterns of the formal thought disorder in patients with schizophrenia.
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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 | 0.001 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".