Characterizing suicidal thoughts and behaviours in individuals presenting to a psychiatric emergency department: a protocol for a multimethod approach for suicide prevention research
Bibliographic record
Abstract
INTRODUCTION: Identifying individuals at risk of suicide remains an ongoing challenge. Previous research investigating risk factors for suicidal thoughts and behaviours (STB) has been informative for assessing suicide risk. However, the complex biological, psychological and sociocultural factors underlying STB have not been comprehensively captured to date, which has limited our understanding of how these factors interact to influence STB. Moreover, acute care settings, such as emergency departments (EDs), are often first points of contact for individuals with STB, highlighting a need for more research in these settings. METHODS AND ANALYSIS: We aim to (1) characterize a cohort seeking care for STB and their clinical trajectories; (2) situate the cohort by comparing its characteristics and outcomes to other groups seeking emergency care; (3) explore their experiences of seeking care; and (4) examine blood-based biomarkers modulating risk for STB. Using a multimethod, prospective cohort design, we will follow up to 500 people aged 16 or older presenting to the ED with STB at a psychiatric hospital over 1 year. Analyses will involve descriptive statistics and latent profile analysis to characterize the cohort, hypothesis tests and regression models to situate the cohort, qualitative analysis based on a realist research framework to understand experiences, and within-participant comparisons of proteins, mRNA and epigenetic DNA modifications to examine biomarkers of contrasting states of STB. ETHICS AND DISSEMINATION: This study was approved by the hospital's Research Ethics Board with safeguards in place to ensure the well-being of participants and research team. An integrated knowledge translation approach will be used for dissemination, wherein patient and family advisors are engaged throughout each study phase. Findings will enhance our understanding of the multifactorial nature of suicide risk, inform strategies for prevention and provide important insights into characteristics, experiences and outcomes of individuals with STB, who are under-represented in mental health research.
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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 | 0.072 | 0.053 |
| Meta-epidemiology (narrow) | 0.003 | 0.004 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.031 | 0.012 |
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".