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Identifying Variables That Predict Depression Following the General Lockdown During the COVID-19 Pandemic
This study aimed to define the psychological markers for future development of depression symptoms following the lockdown caused by the COVID-19 outbreak. Based on previous studies, we focused on loneliness, intolerance of uncertainty and emotion estimation biases as potential predictors of elevated...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8165248/ https://www.ncbi.nlm.nih.gov/pubmed/34079505 http://dx.doi.org/10.3389/fpsyg.2021.680768 |
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author | Gozansky, Einav Moscona, Gal Okon-Singer, Hadas |
author_facet | Gozansky, Einav Moscona, Gal Okon-Singer, Hadas |
author_sort | Gozansky, Einav |
collection | PubMed |
description | This study aimed to define the psychological markers for future development of depression symptoms following the lockdown caused by the COVID-19 outbreak. Based on previous studies, we focused on loneliness, intolerance of uncertainty and emotion estimation biases as potential predictors of elevated depression levels. During the general lockdown in April 2020, 551 participants reported their psychological health by means of various online questionnaires and an implicit task. Out of these participants, 129 took part in a second phase in June 2020. Subjective loneliness during the lockdown rather than objective isolation was the strongest predictor of symptoms of depression 5 weeks later. Younger age and health related worry also predicted higher non-clinical levels of depression and emotional distress. The results support the diathesis-stress model, which posits that a combination of preexisting vulnerabilities along with stressors such as negative life events are among the factors affecting the development of psychopathology. Moreover, our results correspond with those of previous studies conducted worldwide during the COVID-19 pandemic. Taken together, these findings call for focusing on psychological factors, especially among younger people, to identify individuals at risk for future development of depression and to promote new strategies for prevention. |
format | Online Article Text |
id | pubmed-8165248 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-81652482021-06-01 Identifying Variables That Predict Depression Following the General Lockdown During the COVID-19 Pandemic Gozansky, Einav Moscona, Gal Okon-Singer, Hadas Front Psychol Psychology This study aimed to define the psychological markers for future development of depression symptoms following the lockdown caused by the COVID-19 outbreak. Based on previous studies, we focused on loneliness, intolerance of uncertainty and emotion estimation biases as potential predictors of elevated depression levels. During the general lockdown in April 2020, 551 participants reported their psychological health by means of various online questionnaires and an implicit task. Out of these participants, 129 took part in a second phase in June 2020. Subjective loneliness during the lockdown rather than objective isolation was the strongest predictor of symptoms of depression 5 weeks later. Younger age and health related worry also predicted higher non-clinical levels of depression and emotional distress. The results support the diathesis-stress model, which posits that a combination of preexisting vulnerabilities along with stressors such as negative life events are among the factors affecting the development of psychopathology. Moreover, our results correspond with those of previous studies conducted worldwide during the COVID-19 pandemic. Taken together, these findings call for focusing on psychological factors, especially among younger people, to identify individuals at risk for future development of depression and to promote new strategies for prevention. Frontiers Media S.A. 2021-05-17 /pmc/articles/PMC8165248/ /pubmed/34079505 http://dx.doi.org/10.3389/fpsyg.2021.680768 Text en Copyright © 2021 Gozansky, Moscona and Okon-Singer. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Psychology Gozansky, Einav Moscona, Gal Okon-Singer, Hadas Identifying Variables That Predict Depression Following the General Lockdown During the COVID-19 Pandemic |
title | Identifying Variables That Predict Depression Following the General Lockdown During the COVID-19 Pandemic |
title_full | Identifying Variables That Predict Depression Following the General Lockdown During the COVID-19 Pandemic |
title_fullStr | Identifying Variables That Predict Depression Following the General Lockdown During the COVID-19 Pandemic |
title_full_unstemmed | Identifying Variables That Predict Depression Following the General Lockdown During the COVID-19 Pandemic |
title_short | Identifying Variables That Predict Depression Following the General Lockdown During the COVID-19 Pandemic |
title_sort | identifying variables that predict depression following the general lockdown during the covid-19 pandemic |
topic | Psychology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8165248/ https://www.ncbi.nlm.nih.gov/pubmed/34079505 http://dx.doi.org/10.3389/fpsyg.2021.680768 |
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