Depressive symptoms in first episode schizophrenia : A six-month follow-up study -
Bibliographic record
Abstract
Objective: In this study we aimed to find the prevalence of depressive symptoms in first-episode schizophrenia, and to determine the relationship between depressive symptoms and positiveĞnegative symptoms of schizophrenia. Method: Twenty-six patients receiving neuroleptic medication were followed-up throughout six months. Schizophrenia was diagnosed by using the Structured Clinical Interview for DSM-IV (SCID-I). Severity of psychosis, positive symptoms, and negative symptoms were measured using of the Brief Psychiatric Rating Scale, the Scale for the Assessment of Positive Symptoms, and the Scale for the Assessment of Negative Symptoms, respectively. Depressive symptoms were assessed by using the Hamilton Rating Scale for Depression and Calgary Depression Scale. Results: At pretreatment, the frequency of depressive symptoms was 69.2%. The results indicated that depressive symptoms were correlated with severity of schizophrenia and with positive symptoms at beginning and at the end of the study. With neuroleptic treatment, depressive and psychotic symptoms decreased significantly during follow-up. Conclusion: The frequency of depressive symptoms in first-episode schizophrenia was high. Moreover, a positive correlation was found between depressive symptoms and severity of schizophrenia. Thus, we concluded that depressive symptoms might be core symptom of 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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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; both teacher heads agree on what is shown here.
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".