Course of insight, depression and suicidality in inpatients with first‐episode schizophrenia who received group psychoeducation
Bibliographic record
Abstract
AIM: We aimed to investigate whether gaining insight through psychoeducation for first-episode schizophrenia is associated with increased suicidality. METHODS: We conducted a secondary analysis of a prospective cohort study that included inpatients with first-episode schizophrenia who attended a group psychoeducation program during their admission. The group psychoeducation program consisted of four weekly sessions provided by a multidisciplinary team. The primary outcome was the correlation between changes in insight and suicidality. We also examined whether change in insight was associated with changes in hopelessness and depression. We measured insight using the Birchwood Insight Scale. Suicidality, hopelessness and depression were measured using the Calgary Depression Rating Scale for Schizophrenia. RESULTS: A total of 125 people participated in the educational program. The Spearman's correlation coefficient between changes in insight and suicidality was -0.14 (95% confidence interval, -0.31 to 0.04; p = .12). Similarly, gain in insight did not significantly correlate with change in depression (0.01, 95% confidence interval, -0.17 to 0.18; p = .93) and change in hopelessness (0.01, 95% confidence interval, -0.16 to 0.19; p = .88). CONCLUSIONS: We observed almost no association between gaining insight and suicidality after a group psychoeducation program in inpatients with first-episode 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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".