Crisis Occurrence and Resolution in Patients with Severe and Persistent Mental Illness
Bibliographic record
Abstract
Assertive community treatment appears to have limited impact on the risk of suicide in persons with severe and persistent mental illness (SPMI). This exploratory prospective study attempts to understand this observation by studying the contribution of suicidality to the occurrence of crisis events in patients with SPMI. Specifically, an observer-rated measure of the need for hospitalization, the Crisis Triage Rating Scale, was completed at baseline, crisis occurrence, and resolution to determine how much the level of suicidality contributed to the deemed level of crisis. Second, observer-ratings of suicidal ideation, the Modified Scale for Suicide Ideation, and psychopathology and suicidality, Brief Psychiatric Rating Scale, were measured at baseline, crisis occurrence, and resolution. A self-report measure of distress, the Symptom Distress Scale, was completed at baseline, crisis occurrence, and resolution. Finally, the patients' crisis experiences were recorded qualitatively to compare with quantitative measures of suicidality. Almost 40% of the subjects experienced crisis events and more than a quarter of these events were judged to be severe enough to warrant the need for hospitalization. Our findings suggest that elevation of psychiatric symptoms is a major contributor to the crisis occurrences of individuals with SPMI; although the risk of suicide may have to be conceived as somewhat separate from crisis occurrence.
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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 | 0.006 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".