关键词: adverse childhood experiences indicators latent class analysis measures scoping review theories

Mesh : Humans Adverse Childhood Experiences

来  源:   DOI:10.1177/15248380231192922

Abstract:
Adverse childhood experiences (ACEs) studies reveal the profound impacts of experiencing trauma and hardships in childhood. However, the cumulative risk approach of treating ACEs obscures the heterogeneity of ACEs and their consequences, making actionable interventions impossible. latent class analysis (LCA) has increasingly been used to address these concerns by identifying underlying subgroups of people who experience distinctive patterns of co-occurring ACEs. Though LCA has its strengths, the existing research produces few comparable findings because LCA results are dependent on ACEs measures and indicators, which vary widely by study. Therefore, a scoping review of ACEs studies using LCA that focuses on ACEs measures, indicators, and findings is needed to inform the field. Following Arksey and O\'Malley\'s five-stage scoping review methodological framework, we first identified 211 articles from databases of EBSCOhost, PubMed, and Scopus using \"adverse childhood experiences\" for title search and \"latent class analysis\" for abstract search. Based on the inclusion criteria of peer-reviewed articles written in English published from 2012 to 2022 and the exclusion criteria of nonempirical studies and the LCA not analyzing ACEs, we finally selected 58 articles in this scoping review. Results showed LCA has been increasingly endorsed in the ACEs research community to examine the associations between ACEs and human health and well-being across culturally diverse populations. LCA overcame the limitations of the traditional methods by revealing specific ACEs clusters that exert potent effects on certain outcomes. However, the arbitrary nature of selecting ACEs indicators, measures, and the limited use of theory impedes the field from moving forward.
摘要:
不良童年经历(ACE)研究揭示了童年经历创伤和艰辛的深远影响。然而,治疗ACE的累积风险方法掩盖了ACE的异质性及其后果,使可行的干预变得不可能。潜在类别分析(LCA)已越来越多地用于通过识别经历共同发生ACE的独特模式的人群的潜在亚组来解决这些问题。尽管LCA有其优势,现有的研究几乎没有产生可比较的发现,因为LCA结果取决于ACE措施和指标,因研究而异。因此,使用LCA对ACE研究进行范围审查,重点关注ACE措施,指标,需要调查结果来告知现场。遵循Arksey和O'Malley的五阶段范围审查方法论框架,我们首先从EBSCOhost数据库中识别出211篇文章,PubMed,Scopus使用“不良童年经历”进行标题搜索,并使用“潜在类别分析”进行抽象搜索。根据2012年至2022年发表的英文同行评审文章的纳入标准,以及非实证研究和LCA不分析ACE的排除标准,我们最终在这篇范围审查中选择了58篇文章。结果显示,LCA在ACEs研究界得到了越来越多的认可,以研究不同文化人群中ACEs与人类健康和福祉之间的关联。LCA通过揭示对某些结果产生有效影响的特定ACEs集群,克服了传统方法的局限性。然而,选择ACE指标的随意性,措施,理论的有限使用阻碍了该领域的发展。
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