Vargová Lenka, Kačmár Pavol, Lačný Martin, Baník Gabriel
Institute of Psychology, Faculty of Arts, University of Presov, 17. Novembra 1, 080 01 Presov, Slovakia.
Department of Psychology, Faculty of Arts, Pavol Jozef Safarik University in Kosice, Moyzesova 9, 040 59 Kosice, Slovakia.
Curr Psychol. 2023 Feb 8:1-14. doi: 10.1007/s12144-023-04277-x.
Since the outbreak of COVID-19, understanding and describing the changes in experiences related to the pandemic and its correlates have become crucial. The current study aims to provide a psychometric evaluation and examination of the relationship of two COVID-related anxiety scales through the latent and network approach. The data was collected from the same participants at two time points (Nwave 1 = 1283; Nwave 2 = 1326). The study examined the psychometric properties of the Pandemic Anxiety Scale and Coronaphobia scale. It also examined the factor structure, invariance and relationship with selected variables through both the latent and network approach. The results revealed that both scales provided good fit and psychometric properties-PAS (wave1: CFI = 0.97, TLI = 0.95, RMSEA = 0.05 [0.04, 0.07], SRMR = 0.048; wave2: CFI = 0.97, TLI = 0.95, RMSEA = 0.05 [0.04, 0.07], SRMR = 0.049), and Coronaphobia scale (wave1: CFI = 0.99, TLI = 0.98, RMSEA = 0.05 [0.03, 0.07], SRMR = 0.027; wave2: CFI ~ 1, TLI = 0.99, RMSEA = 0.03 [0.002, 0.06], SRMR = 0.015). The results also indicated that distinguishing between them is crucial as they were related differently to various variables. The global network models provided a more complex insight in their connections with the set of selected variables. The PAS and Coronaphobia scales are brief and valid measures that can be used in research looking at mental health issues related to the pandemic. The present study shows a unique pattern of relationships of these scales with other variables, extending previous studies into the topic of COVID-related anxiety.
自新冠疫情爆发以来，了解和描述与疫情相关的经历变化及其相关因素变得至关重要。本研究旨在通过潜在和网络方法对两个与新冠相关的焦虑量表进行心理测量评估，并检验它们之间的关系。数据在两个时间点从相同的参与者中收集（第一次浪潮：N = 1283；第二次浪潮：N = 1326）。该研究考察了大流行焦虑量表和新冠恐惧症量表的心理测量特性。它还通过潜在和网络方法考察了因素结构、不变性以及与选定变量的关系。结果显示，两个量表都具有良好的拟合度和心理测量特性——大流行焦虑量表（第一次浪潮：CFI = 0.97，TLI = 0.95，RMSEA = 0.05 [0.04, 0.07]，SRMR = 0.048；第二次浪潮：CFI = 0.97，TLI = 0.95，RMSEA = 0.05 [0.04, 0.07]，SRMR = 0.049），以及新冠恐惧症量表（第一次浪潮：CFI = 0.99，TLI = 0.98，RMSEA = 0.05 [0.03, 0.07]，SRMR = 0.027；第二次浪潮：CFI ≈ 1，TLI = 0.99，RMSEA = 0.03 [0.002, 0.06]，SRMR = 0.015）。结果还表明，区分这两个量表至关重要，因为它们与各种变量的关系不同。全局网络模型为它们与选定变量集的联系提供了更复杂的见解。大流行焦虑量表和新冠恐惧症量表是简短且有效的测量工具，可用于研究与疫情相关的心理健康问题。本研究展示了这些量表与其他变量关系的独特模式，扩展了先前关于新冠相关焦虑主题的研究。
