Although the COVID-19 pandemic has impacted the psychological wellbeing of some people, there is evidence that many have been much less affected. The Ecological Model of Resilience (EMR) may explain why some individuals are not resilient whilst others are. In this study we test the EMR in a comparison of UK survey data collected from the COVID-19 Psychological Research Consortium (C19PRC) longitudinal study of a representative sample of the United Kingdom (UK) adult population and data from an Italian arm of the study. We first compare data from the third wave of the UK arm of the study, collected in July/August 2020, with data from an equivalent sample and stage of the pandemic in Italy in July 2020. Next, using UK longitudinal data collected from C19PRC Waves 1, 3 and 5, collected between March 2020 and April 2021 we identify the proportion of people who were resilient. Finally, we examine which factors, drawn from the EMR, predict resilient and non-resilient outcomes. We find that the 72% of the UK sample was resilient, in line with the Italian study. In the cross-sectional logistic regression model, age and self-esteem were significantly associated with resilience whilst death anxiety thoughts, neuroticism, loneliness, and Post Traumatic Stress Disorder (PTSD) symptoms related to COVID-19 were significantly associated with Non-Resilient outcomes. In the longitudinal UK analysis, at Wave 5, 80% of the sample was Resilient. Service use, belonging to wider neighbourhood, self-rated health, self-esteem, openness, and externally generated death anxiety were associated with Resilient outcomes. In contrast, PTSD symptoms and loneliness were associated with Non-Resilient outcomes. The EMR effectively explained the results. There were some variables which are amenable to intervention which could increase resilience in the face of similar future challenges.
|Number of pages||28|
|Early online date||11 May 2023|
|Publication status||Published online - 11 May 2023|
Bibliographical noteCopyright: © 2023 Bennett et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
- COVID-19 - epidemiology
- Cross-Sectional Studies
- Longitudinal Studies
- United Kingdom - epidemiology