卫生预防
ENGLISH ABSTRACT
大学生自杀潜在风险特征的潜在剖面分析
刘爱楼
鲍学峰
作者及单位信息
·
DOI: 10.3760/cma.j.cn371468-20221103-000655
Potential profile analysis of potential risk characteristics for suicide among college students
Liu Ailou
Bao Xuefeng
Authors Info & Affiliations
Liu Ailou
Department of Student Affairs, Hubei Normal University, Huangshi 435002, China
Bao Xuefeng
Graduate School, South China Normal University, Guangzhou 510631, China
·
DOI: 10.3760/cma.j.cn371468-20221103-000655
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摘要

目的分析我国大学生自杀潜在风险的类别特征与变化趋势,及各自杀潜在风险亚群的预测因子,为自杀潜在风险的早期识别与精准干预提供科学依据。

方法2017—2021年整群抽取湖北地区6所高校共14 653名在校本科生,每年新生入学后10月份收集1次数据(共5次)。采用Mplus 8.3和SPSS 26.0软件进行统计分析。采用潜在剖面分析(latent profile analysis,LPA)分析大学生自杀潜在风险的亚组及其特征,构建无序多分类Logistic回归模型分析性别、入学年份、心理健康因子对自杀潜在风险类别的预测效应,以及自杀潜在风险差异是否会随着时间的推移而扩大、缩小或保持的年份效应。

结果(1)大学生自杀潜在风险可分为3个亚群,分别是C1低风险组(75.6%)、C2无助高风险组(3.7%)和C3人格高风险组(20.7%);(2)"C2无助高风险组"和"C3人格高风险组"2个高自杀风险组具有明显的性别和年级效应。在性别上,女生进入"C3人格高风险组"的概率显著小于男生。随着入学年级的增加,进入2个高自杀潜在风险组的概率呈现出增加的趋势;(3)人际关系敏感对进入"C3人格高风险组"具有显著正向预测作用( B=0.150, OR=1.162,95% CI=1.140~1.185),偏执对进入"C2无助高风险组"具有显著正向预测( B=0.103, OR=1.109,95% CI=1.051~1.170),而恐怖则对进入"C2无助高风险组"( B=-0.041, OR=0.976,95% CI=0.937~1.016)和"C3人格高风险组"( B=-0.031, OR=0.987,95% CI=0.965~1.010)均有显著负向预测;(4)随着时间推移,"C2无助高风险组"和"C3人格高风险组"2个高自杀风险组的占比均呈上升趋势,且"C3人格高风险组"占比上升趋势更为明显,5年间占比上升10%。

结论大学生自杀潜在风险可分为3个亚群,性别、入学年级和心理健康症状中的人际关系敏感、恐怖和偏执对自杀潜在风险不同亚群的影响差异显著。对于高自杀风险组大学生应根据其特征采取有针对性的干预措施,重点关注高自杀风险组中的高神经质人格特质的大学生,减少危机事件的发生。

大学生;自杀潜在风险;变迁趋势;潜在剖面分析
ABSTRACT

ObjectiveTo explore the characteristics and trends of potential suicide risk among college students in China, as well as the predictive factors for the potential suicide risk subgroups, in order to provide scientific basis for early identification and precise intervention of potential suicide risks.

MethodsFrom 2017 to 2021, a total of 14 653 undergraduate students were selected from 6 universities in Hubei Province through cluster sampling.Data were collected once a year in October after freshmen enrolled (a total of 5 times). Mplus 8.3 and SPSS 26.0 softwares were used for statistics.Latent profile analysis(LPA)was used to analyze the category characteristic of suicide risk in 5 dimensions, and multinomial logistic regression was constructed to analyze the gender and school year effects of suicide risk categories, as well as whether the differences in suicide risk would expand, decrease or maintain over time.

Results(1) According to the fitting indexes of the LPA, the potential suicide risk of college students could be divided into three heterogeneous categories, namely C1 low-risk group (75.6%), C2 helpless high-risk group (3.7%) and C3 personality high-risk group (20.7%). (2) The 2 high suicide risk groups (C2 and C3) had significant gender and grade effects.In terms of gender, female students were significantly less likely to be in the " C3 personality high-risk group" than male students.As the enrollment grade increased, the probability of entering the two high suicide risk groups showed an increasing trend.(3) Interpersonal sensitivity was a significant positive predictor of entry into the " C3 personality high-risk group" ( B=0.150, OR=1.162, 95% CI=1.140-1.185). Paranoid Ideation was a significant positive predictor of entry into the " C2 helpless high-risk group" ( B=0.103, OR=1.109, 95% CI=1.051-1.170). Phobic anxiety was a significant negative predictor of entry into both the " C2 helpless high-risk group" ( B=-0.041, OR=0.976, 95% CI=0.937-1.016)and the " C3 personality high-risk group" ( B=-0.031, OR=0.987, 95% CI=0.965-1.010). (4)Over time, the probability of entering the two high-risk suicide groups(C2 and C3) increased.The proportion of C2 and C3 showed an upward trend, and the proportion of C3 showed a more significant upward trend, with a 10% increase over the past 5 years.

ConclusionsThe potential suicide risk of college students can be divided into three heterogeneous categories.There are significant differences in the impact of gender, grade of enrollment, and mental health symptoms (interpersonal sensitivity, phobic anxiety, and paranoia ideation) on potential suicide risk among different subgroups.Targeted intervention measures should be taken based on the characteristics of college students in the high-risk group of suicide and should focus on college students with high neurotic personality traits in the high suicide risk group to reduce the occurrence of crisis events.

College students;Potential suicide risk;Development tendency;The latent profile analysis
Liu Ailou, Email: mocdef.3ab61666iamoahs
引用本文

刘爱楼,鲍学峰. 大学生自杀潜在风险特征的潜在剖面分析[J]. 中华行为医学与脑科学杂志,2023,32(08):738-745.

DOI:10.3760/cma.j.cn371468-20221103-000655

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自杀是世界性的公共卫生问题 [ 1 ]。研究显示,在全球范围内,自杀已成为15~24岁人群的主要死亡原因 [ 2 ]。大学生身心发展处于一个迅速走向成熟而又未真正成熟的特殊发展时期,是抑郁、焦虑等负面情绪的高发人群 [ 3 ],很多调查表明大学生的自杀率是同龄人的2~4倍 [ 4 ]。因此,加强大学生自杀问题研究,实现自杀风险的早期识别,以便针对不同自杀风险人群进行及时有效的干预,已然成为危机干预研究的一个重要方向。
回顾已有研究发现,对自杀的评估与诊断多为变量中心的传统视角,即根据自杀意念或自杀态度量表的临界值简单地将个体二分为有无自杀意念,并未充分考虑到个体的异质性,缺乏一定的严谨性。潜在剖面分析(latent profile analysis,LPA)从多元分类数据中确定同质分组或类别 [ 5 ],是一种以个体为中心的、基于概率的多变量分类统计方法(即个体以一定概率归属到不同类别)。LPA能够保证和验证分类的准确性和有效性 [ 6 ],帮助研究者比较准确地识别和分辨个体间的类别异质性与特征,从而提高对不同类别自杀风险特点的认识与理解。此外,既往关于自杀风险变迁趋势的分析,重点聚焦自杀比例的整体上升或下降趋势,而本研究拟从个体中心视角出发分析自杀风险不同亚群随时间的变化趋势。应激-易感模型认为,自杀是个体内在易感因素或特质、外在应激因素和保护性因素之间相互作用和影响的结果。因此,自杀不能用单一因素来解释。已有大量研究证实,个体的心理健康症状与自杀密切相关,是自杀意念的重要影响因素 [ 7 , 8 , 9 ],但目前关于心理健康问题及其症状对大学生自杀亚群的预测缺少系统性分析。
据此,本研究从大样本横断面视角,采用LPA对大学生自杀潜在风险的亚群进行分析,总结大学生自杀潜在风险的群体异质性及特征,并在此基础上探索自杀潜在风险不同亚组随时间的变化趋势及相关预测因素,为准确识别自杀高风险人群标示"靶点",提高危机识别的可靠性与准确性,为不断完善心理危机预防和干预措施提供有益参考。
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备注信息
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刘爱楼,Email: mocdef.3ab61666iamoahs
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刘爱楼:项目设计、数据处理与统计分析、论文撰写与修改;鲍学峰:数据收集和整理

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教育部人文社会科学研究项目 (19YJCZH101)
湖北省教育科学规划项目 (2021GA046)
湖北省高等学校哲学社会科学研究项目 (21Y136)
教育部高校思想政治工作队伍培训研修中心(华南师范大学)2021年度开放课题 (SCNUKFYB011)
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