Parallel Exploratory And Confirmatory Factor Analysis Of The Hungarian Fear Of Covid-19 Scale In A Large General Population Sample: A Psychometric And Dimensionality Evaluation

Abstract

Background: The seven-item Fear of Covid-19 Scale (FCV-19S) is the most frequently applied instruments for assessing fear of COVID-19 infection. Our objectives were to develop a Hungarian version of FCV-19S, to evaluate its psychometric properties and dimensionality.Methods: In May 2021, a sample of adults representative of the Hungarian general population completed an online questionnaire survey with respect of the COVID-19 pandemic. Outcome measures included FCV-19S, General Anxiety Disorder (GAD-7) questionnaire and Patient Health Questionnaire (PHQ-9) depressive severity score. Item characteristics, validity and internal consistency reliability of FCV-19S were determined. Maximum likelihood method EFA was used to measure item-factor relationships (h²; factor loading; eigenvalues), while goodness-of-fit of the FCV-19 was evaluated by comparison of one and two-factor CFA model fits (RMSEA, SRMR, χ²/df, CFI, NFI, RFI, IFI, TLI). Correlations explored the relationships between fear, anxiety and depression and FCV-19 scores were compared in vaccinated and non-vaccinated subgroups.Results: Overall, n=2000 responded the online questionnaire. The mean age was 49.1, majority being females (62.2%). EFA identified a maximum of two factors (eig=4.2 and 1.01). Items 3,4,6,7 strongly correlated with Factor 1 (physiological fear) and items 1,2,5 linked to Factor 2 (emotional fear). FCV-19 items showed good internal consistency (Cronbach α=0.88) and correlated moderately or highly, while showing weak to moderate correlation with PHQ-9 (r=0.364) and GAD-7 (r=0.424). Significant differences were observed between vaccinated (14.2) and non-vaccinated (13.1) FCV-19 mean scores.Conclusions: The Hungarian version of the FCV-19 Scale seems valid and reliable construct to measure fear associated with COVID-19. Both uni- and bi-dimensional CFA is feasible, though the two-factor structure faces some limitations.