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

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 ma...

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Detalles Bibliográficos
Autores principales: Kimhi, Shaul, Marciano, Hadas, Eshel, Yohanan, Adini, Bruria
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Ltd. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7518838/
https://www.ncbi.nlm.nih.gov/pubmed/33039732
http://dx.doi.org/10.1016/j.socscimed.2020.113389
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author Kimhi, Shaul
Marciano, Hadas
Eshel, Yohanan
Adini, Bruria
author_facet Kimhi, Shaul
Marciano, Hadas
Eshel, Yohanan
Adini, Bruria
author_sort Kimhi, Shaul
collection PubMed
description 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 (−0.220 and −0.255 respectively; p < .001) and distress symptoms (- 0.398 and −0.544 respectively; p < .001). Significant positive correlations were found between gender, community size, economic difficulties and sense of danger (0.192, 0.117 and 0.244 respectively; p < .001). Gender and economic difficulties also positively correlated with distress symptoms (0.130 and 0.214 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.
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spelling pubmed-75188382020-09-28 Resilience and demographic characteristics predicting distress during the COVID-19 crisis Kimhi, Shaul Marciano, Hadas Eshel, Yohanan Adini, Bruria Soc Sci Med Article 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 (−0.220 and −0.255 respectively; p < .001) and distress symptoms (- 0.398 and −0.544 respectively; p < .001). Significant positive correlations were found between gender, community size, economic difficulties and sense of danger (0.192, 0.117 and 0.244 respectively; p < .001). Gender and economic difficulties also positively correlated with distress symptoms (0.130 and 0.214 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. Elsevier Ltd. 2020-11 2020-09-25 /pmc/articles/PMC7518838/ /pubmed/33039732 http://dx.doi.org/10.1016/j.socscimed.2020.113389 Text en © 2020 Elsevier Ltd. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Article
Kimhi, Shaul
Marciano, Hadas
Eshel, Yohanan
Adini, Bruria
Resilience and demographic characteristics predicting distress during the COVID-19 crisis
title Resilience and demographic characteristics predicting distress during the COVID-19 crisis
title_full Resilience and demographic characteristics predicting distress during the COVID-19 crisis
title_fullStr Resilience and demographic characteristics predicting distress during the COVID-19 crisis
title_full_unstemmed Resilience and demographic characteristics predicting distress during the COVID-19 crisis
title_short Resilience and demographic characteristics predicting distress during the COVID-19 crisis
title_sort resilience and demographic characteristics predicting distress during the covid-19 crisis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7518838/
https://www.ncbi.nlm.nih.gov/pubmed/33039732
http://dx.doi.org/10.1016/j.socscimed.2020.113389
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