Adverse childhood experiences, sexual orientation, and depressive symptoms among Chinese college students: An ecological framework analysis

社会心理的 性取向 潜在类模型 压力源 临床心理学 心理学 女同性恋 性少数派 心理干预 性虐待 毒物控制 性认同 萧条(经济学) 医学 自杀预防 精神科 环境卫生 人类性学 性别研究 数学 宏观经济学 社会学 统计 经济 精神分析 社会心理学
作者
Mengtong Chen,Naiqi Tian,Qingsong Chang
出处
期刊:Child Abuse & Neglect [Elsevier BV]
卷期号:134: 105881-105881 被引量:10
标识
DOI:10.1016/j.chiabu.2022.105881
摘要

Extensive evidence has demonstrated that adverse childhood experiences (ACEs) predict a high risk of negative health and behavioral outcomes in later life. However, the influence of individuals' psychosocial characteristics and environmental stressors have been mostly omitted in previous research.This study aimed to examine the prevalence of ACEs among LGB (lesbian, gay, and bisexual) and heterosexual emerging adults, and the associations between different patterns of ACE exposure and depressive symptoms after adjusting for factors at different levels.A representative sample of 928 college students in Xiamen city, China was recruited.Latent class analysis was applied to identify the patterns of ACEs. A series of regression analyses were conducted to examine the associations between ACEs and depression and whether ACEs interacted with sexual identity to influence depression, after controlling for individual characteristics, family, school, and society-level factors.Over 35 % of the participants reported they had experienced at least one type of moderate to extreme childhood maltreatment, and those who identified as LGB reported a higher level of ACE exposure. Higher levels of ACE exposure based on score and clustering approaches were associated with higher risks of depression among Chinese emerging adults. However, the associations between ACEs and depression were not significantly moderated by sexual identity.The findings highlighted the importance of early screening for ACEs particularly among sexual minorities and of delivering tailored interventions based on ecological backgrounds. Both the traditional scoring approach and a data-driven approach can be effective in detecting the cumulative effect of ACEs.
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