Factors Associated With Suicide in the Month Following Contact With Different Types of Health Services in Quebec
Bibliographic record
Abstract
OBJECTIVE: The aim of the study was to identify factors associated with suicide death occurring in the month following an outpatient visit, emergency room contact, or hospitalization. METHODS: The results of this study are based on data for 8,851 individuals ages 11 years and older who died between January 1, 2000, and December 15, 2007, and whose death was confirmed as suicide by the coroner's office in Quebec, Canada. Health service use in the year prior to death was assessed by review of data from the province's public health insurance agency. Multivariate logistic regression models were used to assess the association of clinical and sociodemographic factors and the occurrence of suicide death in the month following versus more than one month after the last use of health services. RESULTS: A total of 81.6% of suicide decedents had consulted on an outpatient basis, 48.7% had visited an emergency department, and 28.5% were hospitalized in the year prior to death. Among individuals who had been discharged from an emergency department or a hospital closest to their death, 29.5% and 75.3%, respectively, died in the month following discharge. The most consistent modifiable factor associated with death in the month following last contact was number of outpatient consultations following discharge. CONCLUSIONS: Ensuring follow-up care after an emergency department visit or hospitalization may be associated with a longer period between discharge and suicide, allowing for more time to intervene and, possibly, prevent suicide.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".