Testing alternative models and predictive utility of the Death Anxiety Inventory-Revised: A COVID-19 related longitudinal population based study.

ABSTRACT

The beginning of the COVID-19 pandemic had a profound effect on all aspects of daily life and triggered a swell of anxiety across the world. Some suggest this emotional response to the pandemic can be explained through death anxiety (DA), a transdiagnostic dimension associated with numerous psychological disorders. However, it remains unclear as to whether DA is a unidimensional or multidimensional construct. The primary aim of this study was to examine the underlying structure of the Death Anxiety Inventory-Revised (DAI-R; Tomás-Sábado et al., 2005) and assess its associations with mental health and demographic variables during the COVID-19 pandemic. To achieve these aims, we utilized data from Waves 1 (N = 2205 collected between March 23 and March 28, 2020) and 2 (N = 1406 collected between April 22 and May 1, 2020) of the COVID-19 Psychological Research Consortium (C19PRC), a multi-wave nationally representative study. Results showed that a 4-factor model provided the best fit to the data compared to a unidimensional and 4-factor second-order model. Further analyses showed that DA at Wave 1 was positively associated with somatic symptoms, paranoia, depression, anxiety, and traumatic stress symptoms at Wave 2, supporting previous research that suggests that the fear of death is predictive of psychopathology. Significantly, the factor labelled 'Thoughts about Death' at Wave 1 was the strongest predictor of the five main psychological variables at Wave 2, after statistically controlling for the other latent variables. These findings highlight the transdiagnostic nature of DA and support this important diagnostic construct becoming a measure of mental health more generally within the population. It is hoped that this research will shine a light on those suffering from DA and become a catalyst for increased therapeutic intervention, funding, and research in this area.