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《大流行病影响清单(EPII)》:一项多样本研究,旨在调查与大流行病相关的经历及其与心理健康的关系。

The Epidemic-Pandemic Impacts Inventory (EPII): A multisample study examining pandemic-related experiences and their relation to mental health.

机构信息

Center for Alcohol and Addiction Studies, School of Public Health, Brown University.

Department of Psychology, Dole Human Development Center, Clinical Child Psychology Program, University of Kansas.

出版信息

Psychol Assess. 2023 Nov;35(11):1019-1029. doi: 10.1037/pas0001248.

Abstract

The Epidemic-Pandemic Impacts Inventory (EPII) was developed to assess pandemic-related adverse and positive experiences across several key domains, including work/employment, home life, isolation, and quarantine. Several studies have associated EPII-assessed pandemic-related experiences with a wide range of psychosocial factors, most commonly depressive and anxiety symptoms. The present study investigated the degree to which specific types of COVID-19 pandemic-related experiences may be associated with anxiety and depression risk, capitalizing on two large, independent samples with marked differences in sociodemographic characteristics. The present study utilized two adult samples: participants ( = 635) recruited online over a 4-week period in early 2020 (Sample 1) and participants ( = 908) recruited from the student body of a large Northeastern public university (Sample 2). We employed a cross-validated, least absolute shrinkage and selection operator (LASSO) regression approach, as well as a random forest (RF) machine learning algorithm, to investigate classification accuracy of anxiety/depression risk using the pandemic-related experiences from the EPII. The LASSO approach isolated eight items within each sample. Two items from the work/employment and emotional/physical health domains overlapped across samples. The RF approach identified similar items across samples. Both methods yielded acceptable cross-classification accuracy. Applying two analytic approaches on data from two large, sociodemographically unique samples, we identified a subset of sample-specific and nonspecific pandemic-related experiences from the EPII that are most predictive of concurrent depression/anxiety risk. Findings may help to focus on key experiences during future public health disasters that convey greater risk for depression and anxiety symptoms. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

摘要

《大流行相关影响清单》(EPII)旨在评估与大流行相关的几个关键领域的负面和积极体验,包括工作/就业、家庭生活、隔离和检疫。多项研究表明,EPII 评估的大流行相关体验与广泛的心理社会因素相关,最常见的是抑郁和焦虑症状。本研究利用两个具有显著社会人口特征差异的大型独立样本,调查了特定类型的 COVID-19 大流行相关体验与焦虑和抑郁风险的关联程度。本研究利用了两个成人样本:在 2020 年初的 4 周内通过在线招募的参与者(n=635)(样本 1)和从一所大型东北公立大学的学生中招募的参与者(n=908)(样本 2)。我们采用了交叉验证的最小绝对收缩和选择算子(LASSO)回归方法以及随机森林(RF)机器学习算法,使用 EPII 中的大流行相关体验来研究焦虑/抑郁风险的分类准确性。LASSO 方法在每个样本中隔离了 8 个项目。工作/就业和情感/身体健康领域的两个项目在样本之间重叠。RF 方法在样本中识别出相似的项目。两种方法都产生了可接受的交叉分类准确性。在来自两个大型、社会人口学独特样本的数据上应用两种分析方法,我们从 EPII 中确定了与当前抑郁/焦虑风险最相关的一组样本特异性和非特异性大流行相关体验。研究结果可能有助于在未来的公共卫生灾难中集中关注那些与抑郁和焦虑症状风险相关的关键体验。(PsycInfo 数据库记录(c)2023 APA,保留所有权利)。

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