[Clinical correlates of social anxiety disorder comorbidity in schizophrenia].
Bibliographic record
Abstract
OBJECTIVE: The aim of this study is to investigate the social anxiety disorder comorbidity and clinical features in schizophrenia. METHOD: 102 (23 women and 79 men) outpatients who had been followed in the Psychotic Disorders Unit in Bakırköy Research and Training Hospital for Psychiatry, Neurology and Neurosurgery were diagnosed with schizophrenia according to DSM-IV criteria were included in the study. Schizophrenia and Social anxiety disorder were assessed by a structured clinical interview for DSM-IV. Patients were evaluated with a questionnaire which included demographics, clinical characteristics, Liebowitz social anxiety scale, Positive and Negative Syndrome Scale (PANSS), Calgary depression scale for schizophrenia (CDSS),The Scale of Unawareness of Mental Disorders (SUMD), Short form-36 health survey questionnaire and state-trait anxiety ınventory. RESULTS: In remission, 22 patients (21.6%) had co-morbid social anxiety disorder. Patients with social anxiety disorder comorbidity, had higher levels of awareness. Their depression scores were higher and functional impairments were lower. These patients had been treated with typical and atypical antipsychotics and antidepressants. CONCLUSION: Social anxiety disorder comorbidity in schizophrenia adversely affects the quality of life and is not rare. Future studies should be planned with the assesment of social anxiety disorder treatment as well as schizophrenia treatment.
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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 | 0.000 | 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) | 0.003 | 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".