当前位置: X-MOL 学术Eur. J. Psychotraumatol. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Unpacking the impact of the COVID-19 pandemic: identifying structural domains
European Journal of Psychotraumatology ( IF 5.783 ) Pub Date : 2021-06-24 , DOI: 10.1080/20008198.2021.1932296
Kaitlin E Bountress 1 , Shannon E Cusack 1, 2 , Abigail H Conley 3 , Steven H Aggen 1 , Jasmin Vassileva 2, 4, 5 , Danielle M Dick 2, 6 , Ananda B Amstadter 1, 2, 4, 6 ,
Affiliation  

ABSTRACT

Background: The novel coronavirus-19 (COVID-19) pandemic is a collective crisis that imposed an abrupt and unprecedented impact on college students, as universities were closed with little warning. Paired with the challenges associated with physical distancing (e.g. economic stress, job loss, food insecurity, housing challenges) and the simultaneous need to balance continued and new academic demands, impact will be wide-ranging. It is critical to determine the structure of the impact of this heterogeneous stressor (e.g. health concerns, pandemic worry, financial concerns) for prevention and intervention planning.

Objective: Through an existing recruitment pipeline we were in a unique position to study the wide-ranging reach of this pandemic in a cohort of students for whom their university experiences were like no other cohort in history.

Method: Data were collected from students who were in their third year of college during the onset of the pandemic; of the N = 1,899 in the cohort who were invited to participate in this COVID-related survey, 897 (47.2%) completed measures of impact between May and July of 2020.

Results: A series of confirmatory and exploratory models were fit to examine the structure of the pandemic-related domains. Following estimation of a single-factor model, a correlated five factors model, as well as two second-order factor structures, the five correlated factors (exposure, worry, housing/food instability, social media, substance use) model was found to represent the data most appropriately, while producing an interpretable solution.

Conclusions: These measurement model analyses set the stage for future research to examine how these correlated factors impact psychiatric, substance, and academic outcomes in this vulnerable population.



中文翻译:

揭开 COVID-19 大流行的影响:识别结构域

摘要

背景:新型冠状病毒 19 (COVID-19) 大流行是一场集体危机,由于大学在几乎没有警告的情况下关闭,对大学生造成了突然和前所未有的影响。再加上与身体距离相关的挑战(例如经济压力、失业、粮食不安全、住房挑战)以及同时需要平衡持续的和新的学术需求,影响将是广泛的。确定这种异质性压力源(例如健康问题、流行病担忧、财务问题)的影响结构对于预防和干预计划至关重要。

目标:通过现有的招聘渠道,我们处于一个独特的位置,可以研究这一流行病在一群学生中的广泛影响,他们的大学经历在历史上是独一无二的。

方法:数据收集自大流行病爆发期间大学三年级的学生;在受邀参加这项 COVID 相关调查的队列中,N = 1,899人中有 897 人 (47.2%) 在 2020 年 5 月至 2020 年 7 月期间完成了影响测量。

结果:一系列验证性和探索性模型适用于检查大流行相关领域的结构。在对单因素模型、相关五因素模型以及两个二阶因素结构进行估计之后,发现五个相关因素(暴露、担忧、住房/食物不稳定、社交媒体、物质使用)模型代表最合适的数据,同时产生可解释的解决方案。

结论:这些测量模型分析为未来的研究奠定了基础,以检验这些相关因素如何影响这一弱势群体的精神、物质和学业成果。

更新日期:2021-06-24
down
wechat
bug