A confirmatory factor analysis of a cognitive model of COVID-19 related anxiety and depression

Abstract

The mental health impact of the COVID-19 pandemic has been significant, with many regions across the globe reporting significant increases in anxiety, depression, trauma, and insomnia. This study aims to validate a potential cognitive model of maintenance factors of COVID-19 related distress by examining psychological predictors of distress, and their goodness-of-fit as a coherent model. Participants from the general population (n = 555) were recruited using a cross-sectional on-line survey design, assessing Demographic factors, Anxiety, Depression, Loneliness, COVID-19 related distress, Trauma Cognitions related to COVID-19, Rumination, Safety Behaviours, Personality Factors, and Mental Effort related to COVID-19. A series of stepwise linear regressions found that components of the model were significant and accounted for a large percentage of variance when examining Covid-19 related distress (R2 = 0.447 Covid Stress Scale), Anxiety (R2 = 0.536 DASS-Anxiety Subscale) and Depression (R2 = 0.596 Depression DASS-subscale). In a confirmatory factor analysis, Loneliness, Post-Traumatic Cognitions about Self, Post-Traumatic Cognitions about the World, Emotional Stability, and Mental Effort related to COVID-19 loaded onto a single factor. The final model showed adequate fit (CFI = 0.990, TLI = 0.983, RMSEA = 0.053 (0.027–0.080), GFI = 0.986, SRMR = 0.0216, χ2 = 23.087, p = .006). The results highlight the importance of cognitive factors, such as post-traumatic cognitions, rumination, and mental effort in maintaining COVID-19 related distress.

Keywords

• COVID-19
• Cognitive Behavioural Therapy
• CBT
• Predictive model
• Confirmatory factor analysis