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机器学习识别出与中国儿童和青少年抑郁和自杀意念相关的不同因素。

Machine learning identifies different related factors associated with depression and suicidal ideation in Chinese children and adolescents.

机构信息

Institute of Developmental Psychology, Beijing Normal University, Beijing, China.

State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China.

出版信息

J Affect Disord. 2024 Sep 15;361:24-35. doi: 10.1016/j.jad.2024.06.006. Epub 2024 Jun 4.

Abstract

BACKGROUND

Depression and suicidal ideation often co-occur in children and adolescents, yet they possess distinct characteristics. This study sought to identify the different related factors associated with depression and suicidal ideation.

METHODS

A nationwide cross-sectional survey collected data from Chinese children and adolescents aged 8 to 18 (N = 160,962; 48.91 % girls). The survey included inquiries about demographics, depression, suicidal ideation, anxiety, perceived stress, academic burnout, internet addiction, non-suicidal self-injury, bullying, and being bullied. Fifteen machine learning algorithms were conducted to identify the different related factors associated with depression and suicidal ideation. Additionally, we conducted external validation on an independent sample of 1,812,889 children and adolescents.

RESULTS

Our findings revealed seven related factors linked to depression and six associated with suicidal ideation, with average accuracy rates of 86.86 % and 85.82 %, respectively. For depression, the most influential factors were anxiety, perceived stress, academic burnout, internet addiction, non-suicidal self-injury, experience of bullying, and age. Similarly, anxiety, non-suicidal self-injury, perceived stress, internet addiction, academic burnout, and age emerged as paramount factors for suicidal ideation. Moreover, these related factors showed notable variations in their predictive capacities for depression and suicidal ideation across different subgroups.

CONCLUSION

Anxiety emerged as the predominant shared factor for both depression and suicidal ideation, whereas the other related factors displayed distinct predictive patterns for each condition. These findings highlight the critical need for tailored strategies from public mental health service providers and policymakers to address the pressing concerns of depression and suicidal ideation.

摘要

背景

抑郁和自杀意念在儿童和青少年中经常同时发生,但它们具有不同的特征。本研究旨在确定与抑郁和自杀意念相关的不同因素。

方法

一项全国性的横断面调查从中国 8 至 18 岁的儿童和青少年(N=160962;48.91%为女孩)中收集数据。调查包括询问人口统计学、抑郁、自杀意念、焦虑、感知压力、学业倦怠、网络成瘾、非自杀性自我伤害、欺凌和被欺凌等问题。我们使用了 15 种机器学习算法来识别与抑郁和自杀意念相关的不同因素。此外,我们还对 1812889 名独立的儿童和青少年样本进行了外部验证。

结果

我们的研究结果揭示了与抑郁相关的七个因素和与自杀意念相关的六个因素,准确率分别为 86.86%和 85.82%。对于抑郁,最具影响力的因素是焦虑、感知压力、学业倦怠、网络成瘾、非自杀性自我伤害、欺凌经历和年龄。同样,焦虑、非自杀性自我伤害、感知压力、网络成瘾、学业倦怠和年龄也是自杀意念的重要因素。此外,这些相关因素在不同亚组中对抑郁和自杀意念的预测能力存在显著差异。

结论

焦虑是抑郁和自杀意念的共同主要因素,而其他相关因素对每种情况的预测模式不同。这些发现强调了公共心理健康服务提供者和政策制定者制定有针对性的策略来解决抑郁和自杀意念这两个紧迫问题的必要性。

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