利用童年逆境和心理健康入院模式预测青少年自杀。

IF 3.9 3区医学 Q1 PSYCHIATRY

BJPsych Open Pub Date : 2025-06-20 DOI:10.1192/bjo.2025.787

Anna Tarasenko, Dennis Ougrin

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引用次数: 0

摘要

Dougall等人发现，心理健康入院是年轻人自杀风险的一个强有力的预测指标。这一发现可以改进预测自杀风险的机器学习模型。机器学习模型的局限性包括COVID-19大流行期间医疗保健使用模式的最新变化以及较差的长期预测价值。

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Use of childhood adversity and mental health admission patterns to predict suicide in young people.

Dougall et al found that mental health admissions are a strong predictor of suicide risk in young people. The findings can improve machine learning models for predicting suicide risk. Limitations of machine learning models include recent changes in healthcare use patterns during the COVID-19 pandemic and poor long-term predictive value.

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来源期刊

BJPsych Open Medicine-Psychiatry and Mental Health

CiteScore

6.30

自引率

3.70%

发文量

610

审稿时长

16 weeks

期刊介绍： Announcing the launch of BJPsych Open, an exciting new open access online journal for the publication of all methodologically sound research in all fields of psychiatry and disciplines related to mental health. BJPsych Open will maintain the highest scientific, peer review, and ethical standards of the BJPsych, ensure rapid publication for authors whilst sharing research with no cost to the reader in the spirit of maximising dissemination and public engagement. Cascade submission from BJPsych to BJPsych Open is a new option for authors whose first priority is rapid online publication with the prestigious BJPsych brand. Authors will also retain copyright to their works under a creative commons license.