Are individual differences in personality associated with COVID-19 infection? Examining the role of normative, maladaptive, and dark personality traits using structural equation modeling

Objective: During the COVID-19 pandemic, people’s behaviors have been considered an important factor in the spread of coronavirus. This situation led us to examine the role of personality in human behavior and its outcomes during the pandemic. This study examined the effect of normative, maladaptive, and dark personality traits on the probability of COVID-19 infection as mediated by psychological and behavioral responses to the pandemic. Methods: The data was collected from 740 Iranians (mean age = 33.34) completing Big Five-10, Personality Inventory for DSM-5-Brief Form (PID-5-BF)-Adult, Short Dark Triad (SD3), Depression, Anxiety and Stress Scale - 21 Items (DASS-21), and Protective Behaviors inventories. We used structural equation modeling to fit a model from the personality traits to COVID-19 infection through mediating effects of psychological and behavioral responses using cross-sectional data. Results: All path models examined fit the data well. The normative traits openness, conscientiousness, neuroticism, introversion, and disagreeableness were positively related to social distancing. The pathological traits antagonism, detachment, negative affectivity, disinhibition, and psychoticism, and dark traits psychopathy, narcissism, and Machiavellianism were negatively associated with social distancing. Finally, social distancing was negatively related to infection rates and fully mediated all personality links with infection (β = −0.17, p < 0.001). Conclusion: The findings demonstrate that individual differences in personality predict behaviors crucial to pandemic mitigation. Social distancing can be, directly or indirectly, a significant underlying mechanism linking personality traits to the COVID-19 infection. Public health policymakers should consider personality-tailored interventions for maximizing preventive health behaviors and slowing the spread of infection. This knowledge also could contribute to more effective measures to prepare for public health emergencies in the future.