Inpatient Treatment of Suicidality
Bibliographic record
Abstract
Psychiatric inpatients represent an acutely vulnerable population with high rates of suicidality (ie, suicidal ideation, attempts, and completed suicide). This systematic review aimed to evaluate treatments for suicidality delivered within inpatient settings. MEDLINE, Embase, APA PsycInfo, CINAHL, and The Cochrane Library were systematically searched using 3 concepts: suicidality, inpatient population/setting, and treatment/ interventions. Searches were limited to years 2001-2024, with no language restrictions. Of 19,921 articles identified, 11,519 were screened, and 179 underwent full-text review. We included clinical trials on pharmacologic and nonpharmacologic interventions for suicidality in psychiatric inpatients aged 18-65 with moderate to high levels of suicidality that measured changes in suicidality. Studies were organized into tables by study design, treatments, participants, suicide measure, outcomes, and key findings. Due to heterogeneity, a meta-analysis was not conducted; instead, a narrative synthesis was used for qualitative analysis. Forty-nine studies were included. Of 14 pharmacologic trials, intravenous ketamine showed most consistent rapid reduction in suicidality. Thirty-five nonpharmacologic trials, covering a broad spectrum of treatments including chronotherapy, neurostimulations, and psychotherapies, were reviewed. The results were mixed, with some interventions showing potential in reducing suicidality, particularly in the mood, personality, and trauma-related disorders. Many studies had methodological concerns including nonrandomized designs, lack of control arms, and retrospective assessments. A range of interventions for treating suicidality in inpatient settings have been evaluated, with mixed results. The current review underscores the need for larger, well-designed trials to assess the effectiveness of these treatments in inpatient settings.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".