P-1317 - Evaluation of insight and fuctional recovery in patients with schizophrenia
Bibliographic record
Abstract
The purpose of this study is to examine the factors which influence schizophrenia patients’ levels of insight and functional remission. In this study, 70 outpatients between the ages of 18–65 who applied to the Karadeniz Technical University Psychiatry Clinic and were diagnosed with schizophrenia according to DSM-IV were evaluated. Patients who have disease which affects the central nervous system, whose CGI disease severity score is above four, who were taken as inpatients to the hospital in the last two months were excluded from the study. The patients were evaluated by using socio-demographic data collection form, clinical interview structured for DSM (SCID-I), the Positive and Negative Syndrome Scale (PANSS), Calgary Depression Scale (CDS), the Functional Remission of General Schizophrenia Scale (FROGS), Schedule for Assessing the Three Components of Insight (SAI-E) and cognitive test battery. Patients SAI-E levels were found to be correlated with the PANSS, Stroop Test (ST), Controlled Word Association Test (FAS) and Trail Making Test (TMT) A-B scores. In the regression analysis, FAS scores were the predictor of SAI-E total scores .The FROGS functional levels of patients were found to be related with occupational status, gender, age of onset illness, comorbid psychiatric illness, PANSS, CDS, SAI-E, FAS, TMT, ST and Wisconsin Card Sorting Test scores. In the regression analysis, occupational status, comorbid obsessive compulsive disorder, PANNS negative and general psychopathology and FAS scores were the predictors of patients’ functional status. The effect of cognitive functioning and insight on the patients’ level of functionality is prominent.
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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 | 0.000 |
| 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) | 0.002 | 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".