Resilience and demographic characteristics predicting distress during the COVID-19 crisis

Kimhi, Shaul; Marciano, Hadas; Eshel, Yohana; Adini, Bruria

RATIONALE: Due to lack of vaccine or cure, the COVID-19 pandemic presents a threat to all human beings, undermining people’s basic sense of safety and increasing distress symptoms. OBJECTIVE: To investigate the extent to which individual resilience, well-being and demographic characteristics may predict two indicators of Coronavirus pandemic: distress symptoms and perceived danger. METHOD: Two independent samples were employed: 1) 605 respondents recruited through an internet panel company; 2) 741 respondents recruited through social media, using snowball sampling. Both samples filled a structured online questionnaire. Correlations between psychological/demographic variables and distress and perceived danger were examined. Path analysis was conducted to identify predictive indicators of distress and perceived danger. RESULTS: Significant negative correlations were found between individual/community resilience and sense of danger (-.220 and -.255 respectively; p <.001) and distress symptoms (- .398 and -.544 respectively; p <.001). Significant positive correlations were found between gender, community size, economic difficulties and sense of danger (.192, .117 and .244 respectively; p <.001). Gender and economic difficulties also positively correlated with distress symptoms (.130 and .214 respectively; p <.001). Path analysis revealed that all paths were significant ( p <.008 to .001) except between family income and distress symptoms ( p =.12). The seven predictors explained 20% of sense of danger variance and 34% the distress symptoms variance. The most highly predictive indicators were the two psychological characteristics, individual resilience, and well-being. Age, gender, community size, and economic difficulties due to COVID-19 further add to predicting distress, while community and national resilience do not. . CONCLUSIONS: Individual resilience and well-being have been found as the first and foremost predictors of COVID-19 anxiety. Though both predictors are complex and may be influenced by many factors, given the potential return of COVID-19 threat and other future health pandemic threats to our world, we must rethink and develop ways to reinforce them.