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. 2020 Nov:50:101843.
doi: 10.1016/j.ijdrr.2020.101843. Epub 2020 Sep 15.

Recovery from the COVID-19 pandemic: Distress and resilience

Shaul Kimhi  1 , Hadas Marciano  1   2 , Yohanan Eshel  3 , Bruria Adini  4
Affiliations

Recovery from the COVID-19 pandemic: Distress and resilience

Shaul Kimhi et al. Int J Disaster Risk Reduct. 2020 Nov.

Abstract

The current study analyzed repeated responses to the coronavirus. Data for the first phase was gathered during the peak of the COVID-19 pandemic crisis in Israel (T1), which included the overall lock-down of the Israeli society. The repeated measurement was conducted approximately two months later, on the initial phase of lifting the lock-down (T2). The sample size was 300 people. Results indicated four significant differences between the first and the second measurements: Sense of danger, distress symptoms, and national resilience significantly decreased, while perceived well-being increased at T2. No significant differences were noted between the two measurements regarding individual and community resilience and economic difficulties. The data indicated that the highest decrease in national resilience was accounted for by low respondent trust in governmental decisions during the COVID-19 crisis. The negative impact of the COVID-19 pandemic on the participants was determined by two indicators: level of distress symptoms and sense of danger. Path analyses showed that five variables significantly predicted these two indicators. Their best predictor at T1 and T2 was well-being followed by individual resilience, economic difficulties due to the pandemic crisis, community resilience, and gender. It was concluded that psychological attributes may help in decreasing the impact of the threats of the COVID-19 pandemic.

Keywords: Community and national resilience; Distress symptoms; Individual; Repeated measure of response to COVID-19; Sense of danger; Wellbeing.

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Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Fig. 1
Fig. 1
General model of three models of path analysis, predicting sense of danger and distress symptoms.
See this image and copyright information in PMC

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