关于不良童年经历的全面审查 使用潜阶级分析的研究:优势和挑战
Xiafei Wang1, Linghua Jiang1, Lauren Barry1
1Syracuse University, NY, USA.
Trauma, violence & abuse
|August 18, 2023
概括
潜在类分析 (LCA) 揭示了不同的不良童年经历 (ACE) 集群,提供了超越传统累积风险模型的见解. 这种方法有助于识别影响健康和福祉的特定ACE模式.
科学领域:
- 心理学 心理学 心理学
- 公共卫生 公共卫生
- 流行病学 流行病学
背景情况:
- 不良童年经历 (ACE) 研究强调了童年创伤的影响.
- 传统的累积风险模型掩盖了ACE的异质性,阻碍了干预.
- 隐性类分析 (LCA) 识别了具有明显 ACE 模式的子组.
研究的目的:
- 使用LCA进行ACE研究的范围审查.
- 分析LCA研究中的ACE措施,指标和发现.
- 通过在ACE研究中综合当前的LCA应用来为该领域提供信息.
主要方法:
- 按照阿克西和奥马利的框架进行系统的范围审查.
- 搜索了EBSCOhost,PubMed,Scopus的"不良童年经历"和"潜伏阶级分析".
- 包括58项同行评审的实证研究 (2012-2022年) 分析与LCA一起的ACE.
主要成果:
- 在不同人群的ACE研究中,LCA越来越多地被使用.
- LCA确定了与健康和福祉结果相关的特定ACE集群.
- 这些发现揭示了LCA克服传统ACE方法的局限性的潜力.
结论:
- LCA提供了一种细微的方法来理解ACE,超越累积风险.
- 为了在这个领域推进LCA,需要对ACE测量的标准化和理论基础.
- 进一步的研究应侧重于一致的指标选择和理论整合,以获得可靠的研究结果.
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