Female suicides: Psychosocial and psychiatric characteristics identified by a psychological autopsy study in Japan
Bibliographic record
Abstract
AIM: Although the female suicide rate in Japan is one of the highest among OECD countries, little has been done to assess the psychosocial and psychiatric characteristics of Japanese female suicide completers. This study aimed to examine sex differences in psychosocial and psychiatric characteristics of suicide completers using a psychological autopsy study method, and to identify female suicide factors and intervention points to prevent female suicides. METHODS: A semi-structured interview was conducted with close family members of adult suicide completers. The interview included questions regarding sociodemographic factors, suicide characteristics, previous suicidal behaviors and a family history of suicidal behaviors, financial problems, and physical/psychiatric problems. Fisher's exact test and the Student's t-test were used to explore sex differences in these survey items, and individual descriptive information of female suicide cases was also examined. RESULTS: Of the 92 suicide completers, 28 were female and 64 were male. Females had a significantly higher prevalence of a history of self-harm/suicide attempts (P < 0.001). The prevalence of eating disorders was significantly higher among females than males (P < 0.01). CONCLUSION: The findings of this study highlight the importance of providing psychological and social support to caregivers of those who repeatedly attempt suicide and express suicidal thoughts, and to suggest the need to improve community care systems to be aware of suicide risk factors among female suicide attempters.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".