SP3-30 Characteristics of attempted suicide patients presenting to secondary and tertiary emergency rooms, Tochigi prefecture, Japan
Bibliographic record
Abstract
Introduction Suicide rate has increased dramatically in Japan since 1998. It is important to reveal the characteristics of attempted suicide patients at emergency rooms (ERs) to prevent future suicides. Methods Questionnaires were sent to all 74 secondary and tertiary ERs in Tochigi prefecture. Data were collected for attempted suicide patients who presented in September 2009. Results All ERs responded to the survey. Only nine ERs had psychiatric departments. There were 81 attempted suicides (36 men, 45 women). 43% were in their 20s or 30s. Approximately half (47%) were unemployed. The majority (85%) resided with other family members. The average number of patients presenting to ERs were 3.2 for workdays and 1.6 for weekends/holidays. The most common method of suicide attempt was drug overdose (57%) followed by stabbing (18%), hanging (8%), and jumping from height (8%). Half (49%) used prescription drugs to commit suicide. The majority (59%) had presented to psychiatric departments, 38% had a history of depressive disorders in the past, and a quarter had previous suicide attempt. About half (47%) were admitted to medical or surgery departments, 33% were discharged home, and 9% died. After excluding those who died, 46% were not referred to a psychiatrist, and 39% were confirmed to have seen a psychiatrist. Conclusion Although attempted suicide patients should be referred for psychiatric assessment, many of them were not. It is important to strengthen the chain of care as well as to educate health providers and family members to prevent repeated suicide attempts.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".