Universal Suicide Risk Screening for Youths in the Emergency Department: A Systematic Review
Bibliographic record
Abstract
OBJECTIVES: To address escalating youth suicide rates, universal suicide risk screening has been recommended in pediatric care settings. The emergency department (ED) is a particularly important setting for screening. However, EDs often fail to identify and treat mental health symptoms among youths, and data on implementation of suicide risk screening in EDs are limited. A systematic review was conducted to describe the current literature on universal suicide risk screening in EDs, identify important gaps in available studies, and develop recommendations for strategies to improve youth screening efforts. METHODS: A systematic literature search of PubMed, MEDLINE, CINAHL, PsycINFO, and Web of Science was conducted. Studies focused on universal suicide risk screening of youths served in U.S. EDs that presented screening results were coded, analyzed, and evaluated for reporting quality. Eleven studies were included. RESULTS: All screening efforts occurred in teaching or children's hospitals, and research staff administered suicide screens in eight studies. Thus scant information was available on universal screening in pediatric community ED settings. Large variation was noted across studies in participation rates (17%-86%) and in positive screen rates (4.1%-50.8%), although positive screen rates were influenced by type of presenting concern (psychiatric versus nonpsychiatric). Only three studies concurrently examined barriers to screening, providing little direction for effective implementation. STROBE guidelines were used to rate reporting quality, which ranged from 51.9% to 87.1%, with three studies having ratings over 80%. CONCLUSIONS: Research is needed to better inform practice guidelines and clinical pathways and to establish sustainable screening programs for youths presenting for care in EDs.
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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 | 0.010 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".