[The effects of psychosocial skills training on symptomatology, insight, quality of life, and suicide probability in schizophrenia].
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to determine the effect of psychosocial skills training (PST) on symptomatology, insight, quality of life, and suicide probability in patients with schizophrenia. METHOD: The sample consisted of 22 schizophrenic outpatients diagnosed according to DSM-IV diagnostic criteria. Three PST groups were formed and each group's training lasted approximately 6 months. Nineteen (86%) patients completed the study. The Scale for the Assessment of Positive Symptoms, Scale for the Assessment of Negative Symptoms, Calgary Depression Rating Scale for Schizophrenia, Schedule for Assessing the Three Components of Insight, Quality of Life Scale for Patients with Schizophrenia, and Suicide Probability Scale were administered to the patients before and after PST. RESULTS: At the end of the study mean score for the Scale for the Assessment of Positive Symptoms score (baseline 8.5+/- +/- 9.9, post-PST 3.4 +/- +/-6.0, P = 0.004), Scale for the Assessment of Negative Symptoms (baseline 33.7 +/- +/-19.3, post-PST 22.1 +/- +/-15.7, P = 0.001), Calgary Depression Rating Scale for Schizophrenia (baseline 4.2 +/- +/-4.1, post-PST 0.7 +/- +/-1.0, P = 0.001), Schedule for Assessing the Three Components of Insight (baseline 11.1 +/- +/-3.4, post-PST 16.2 +/- +/-1.1, P < 0.0001), and Quality of Life Scale for Patients with Schizophrenia (baseline 53.5 +/- +/-20.0, post-PST 79.6 +/- +/-20.8, P < 0.0001) changed significantly, whereas the change in mean score for the Suicide Probability Scale (baseline 75.1+/- +/- 11.7, post-PST 71.3+/- +/- 8.0, P = 0.06) did not reach statistical significance. CONCLUSION: This study demonstrated the effects of PST on the symptoms and functioning of patients with schizophrenia. It can be concluded that using PST for the treatment of schizophrenia, as an adjuvant to pharmacotherapy, could produce significant positive results.
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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 | 0.000 | 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".