Rasch Modeling and Multilevel Confirmatory Factor Analysis for the Usability of the Impact of Event Scale-Revised (IES-R) during the COVID-19 Pandemic

Musheer A. Aljaberi, Kuo Hsin Lee, Naser A. Alareqe, Mousa A. Qasem, Abdulsamad Alsalahi, Atiyeh M. Abdallah, Sarah Noman, Ala’a B. Al-Tammemi, Mohamed Izham Mohamed Ibrahim, Chung Ying Lin

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41 Citations (Scopus)

Abstract

Background: Several instruments are currently used to assess Coronavirus Disease 2019 (COVID-19) -induced psychological distress, including the 22-item Impact of Event Scale-Revised (IES-R). The IES-R is a self-administered scale used to assess post-traumatic stress disorder (PTSD). The current study aimed to examine the construct validity of the IES-R, based on the Rasch model, with COVID-19-related data, as well as to test the multilevel construct validity of the IES-R within and among countries during the pandemic crisis. Methods: A multi-country web-based cross-sectional survey was conducted utilizing the 22-item IES-R. A total of 1020 participants enrolled in our survey, of whom 999 were included in the analyses. Data were analyzed using Rasch modeling and multilevel confirmatory factor analysis (MCFA). Results: The Rasch modeling results of the IES-R demonstrated that the IES-R is a satisfactory instrument with the five-point Likert scale, asserting that its 22 items are significant contributors to assessing PTSD as a unidimensional construct covered by the items of the IES-R. The MCFA confirmed that the 22-item IES-R, with its three factors, including intrusion, avoidance, and hyperarousal, demonstrates adequate construct validity at the within- and among-country levels. However, the results of the Akaike information criterion (AIC) model determined that the 16-item IES-R is better than the 22-item IES-R. Conclusion: The results suggested that the 22-item IES-R is a reliable screening instrument for measuring PTSD related to the COVID-19 pandemic, and can be utilized to provide timely psychological health support, when needed, based on the screening results.

Original languageEnglish
Article number1858
JournalHealthcare (Switzerland)
Volume10
Issue number10
DOIs
Publication statusPublished - 2022 Oct

All Science Journal Classification (ASJC) codes

  • Leadership and Management
  • Health Policy
  • Health Informatics
  • Health Information Management

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