Symptoms of Depression, Positive Symptoms of Psychosis, and Suicidal Ideation Among Adults Diagnosed With Schizophrenia Within the Clinical Antipsychotic Trials of Intervention Effectiveness
Bibliographic record
Abstract
Suicide is among leading causes of death for adults diagnosed with schizophrenia. While symptoms of depression are consistently supported factors involved in suicidal ideation, findings on the role of positive symptoms of psychosis have been mixed with limited understandings of risk. Accordingly, this study aimed to identify the pathways of influence between symptoms of depression, positive symptoms of psychosis (i.e. hallucinations and delusions), and suicidal ideation. Data were obtained from the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE; n = 1,460). Suicidal ideation and symptoms of depression were measured by the Calgary Depression Scale (CDRS) and hallucinations and delusions by the Positive and Negative Syndrome Scale (PANSS). The data were analyzed using Structural Equation Modeling (SEM). As symptoms of depression and positive symptoms of psychosis independently increased, on average there were associated increases in suicidal ideation. The present study provides support for the relationship between positive symptoms of psychosis, specifically hallucinations and delusions, and suicidal ideation. Future prospective longitudinal study designs are needed to further increase understandings of the roles that hallucinations, delusions, and additional symptoms of schizophrenia play in both suicidal ideation and attempt to ultimately inform evidence-based interventions aiming to reduce suicidal death.
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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 | 0.016 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".