Psychosis and Hopelessness Mediate the Relationship Between Reduced Sleep and Suicidal Ideation in Schizophrenia Spectrum Disorders
Bibliographic record
Abstract
OBJECTIVE: Suicide is a major cause of death amongst individuals with schizophrenia spectrum disorders (SSD). Despite numerous risk factors being identified, accurate prediction of suicidality and provision of tailored and effective treatment is difficult. One factor that may warrant particular attention as a contributor to increased psychopathology and suicidality in SSD is disturbed sleep. Sleep disturbances have been reliably linked to greater levels of suicidal ideation and are highly prevalent amongst individuals with SSD. This study aimed to examine if reduced sleep duration and psychopathology are associated with increased suicidal ideation. METHOD: One-hundred and eighteen adults with chronic SSD living within the community participated in this cross-sectional study. Psychosis symptoms were assessed using the Positive and Negative Syndrome Scale. Items 4 and 10 from the Montgomery-Asperg Depression Rating Scale and Item 2 from the Calgary Depression Scale for Schizophrenia were used to assess reduced sleep duration, current suicidal ideation, and hopelessness, respectively. All measures were rated concurrently. RESULTS: A hierarchical logistic regression revealed that greater acute sleep disturbances were associated with increased suicidal ideation and this relationship was found to be uniquely mediated by both positive symptom severity and hopelessness. CONCLUSION: These results suggest that individuals with SSD who exhibited disrupted or disordered sleep, positive symptoms and/or hopelessness should be routinely screened for suicidal thinking. Furthermore, interventions that effectively target sleep disruptions may provide much-needed action against suicidal ideation.HIGHLIGHTSReduced sleep found to be associated with increased suicidal ideationThis was uniquely mediated by both hopelessness and positive symptomsMore regular screening of sleep problems in schizophrenia is needed.
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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 | 0.003 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".