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Examining the Associations between COVID-19-Related Psychological Distress, Social Media Addiction, COVID-19-Related Burnout, and Depression among School Principals and Teachers through Structural Equation Modeling
This study aims to investigate the relationships between COVID-19-related psychological distress, social media addiction, COVID-19-related burnout, and depression. The research, which was designed according to the relational survey model, was conducted with the participation of 332 school principals...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8871564/ https://www.ncbi.nlm.nih.gov/pubmed/35206140 http://dx.doi.org/10.3390/ijerph19041951 |
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author | Karakose, Turgut Yirci, Ramazan Papadakis, Stamatis |
author_facet | Karakose, Turgut Yirci, Ramazan Papadakis, Stamatis |
author_sort | Karakose, Turgut |
collection | PubMed |
description | This study aims to investigate the relationships between COVID-19-related psychological distress, social media addiction, COVID-19-related burnout, and depression. The research, which was designed according to the relational survey model, was conducted with the participation of 332 school principals and teachers who received graduate education in the field of educational administration. Research data were collected through online surveys and then structural equation modeling (SEM) was used to test and analyze the proposed hypotheses. The study’s findings revealed that COVID-19-related psychological distress strongly predicted COVID-19-related burnout. In this context, as the psychological distress associated with COVID-19 increased, the sense of burnout associated with COVID-19 also increased. However, it was found that burnout associated with COVID-19 significantly and positively predicted depression. SEM results revealed that COVID-19-related psychological distress directly affected COVID-19-related burnout, depression, and social media addiction. In addition, it was determined that an indirect effect of COVID-19-related burnout and social media addiction exists in the relationship between COVID-19-related psychological distress and depression. |
format | Online Article Text |
id | pubmed-8871564 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-88715642022-02-25 Examining the Associations between COVID-19-Related Psychological Distress, Social Media Addiction, COVID-19-Related Burnout, and Depression among School Principals and Teachers through Structural Equation Modeling Karakose, Turgut Yirci, Ramazan Papadakis, Stamatis Int J Environ Res Public Health Article This study aims to investigate the relationships between COVID-19-related psychological distress, social media addiction, COVID-19-related burnout, and depression. The research, which was designed according to the relational survey model, was conducted with the participation of 332 school principals and teachers who received graduate education in the field of educational administration. Research data were collected through online surveys and then structural equation modeling (SEM) was used to test and analyze the proposed hypotheses. The study’s findings revealed that COVID-19-related psychological distress strongly predicted COVID-19-related burnout. In this context, as the psychological distress associated with COVID-19 increased, the sense of burnout associated with COVID-19 also increased. However, it was found that burnout associated with COVID-19 significantly and positively predicted depression. SEM results revealed that COVID-19-related psychological distress directly affected COVID-19-related burnout, depression, and social media addiction. In addition, it was determined that an indirect effect of COVID-19-related burnout and social media addiction exists in the relationship between COVID-19-related psychological distress and depression. MDPI 2022-02-10 /pmc/articles/PMC8871564/ /pubmed/35206140 http://dx.doi.org/10.3390/ijerph19041951 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Karakose, Turgut Yirci, Ramazan Papadakis, Stamatis Examining the Associations between COVID-19-Related Psychological Distress, Social Media Addiction, COVID-19-Related Burnout, and Depression among School Principals and Teachers through Structural Equation Modeling |
title | Examining the Associations between COVID-19-Related Psychological Distress, Social Media Addiction, COVID-19-Related Burnout, and Depression among School Principals and Teachers through Structural Equation Modeling |
title_full | Examining the Associations between COVID-19-Related Psychological Distress, Social Media Addiction, COVID-19-Related Burnout, and Depression among School Principals and Teachers through Structural Equation Modeling |
title_fullStr | Examining the Associations between COVID-19-Related Psychological Distress, Social Media Addiction, COVID-19-Related Burnout, and Depression among School Principals and Teachers through Structural Equation Modeling |
title_full_unstemmed | Examining the Associations between COVID-19-Related Psychological Distress, Social Media Addiction, COVID-19-Related Burnout, and Depression among School Principals and Teachers through Structural Equation Modeling |
title_short | Examining the Associations between COVID-19-Related Psychological Distress, Social Media Addiction, COVID-19-Related Burnout, and Depression among School Principals and Teachers through Structural Equation Modeling |
title_sort | examining the associations between covid-19-related psychological distress, social media addiction, covid-19-related burnout, and depression among school principals and teachers through structural equation modeling |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8871564/ https://www.ncbi.nlm.nih.gov/pubmed/35206140 http://dx.doi.org/10.3390/ijerph19041951 |
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