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Leveraging twitter data to understand nurses’ emotion dynamics during the COVID-19 pandemic
The nursing workforce is the largest discipline in healthcare and has been at the forefront of the COVID-19 pandemic response since the outbreak of COVID-19. However, the impact of COVID-19 on the nursing workforce is largely unknown as is the emotional burden experienced by nurses throughout the di...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10289963/ https://www.ncbi.nlm.nih.gov/pubmed/37359480 http://dx.doi.org/10.1007/s13755-023-00228-9 |
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author | Zhou, Jianlong Sheppard-Law, Suzanne Xiao, Chun Smith, Judith Lamb, Aimee Axisa, Carmen Chen, Fang |
author_facet | Zhou, Jianlong Sheppard-Law, Suzanne Xiao, Chun Smith, Judith Lamb, Aimee Axisa, Carmen Chen, Fang |
author_sort | Zhou, Jianlong |
collection | PubMed |
description | The nursing workforce is the largest discipline in healthcare and has been at the forefront of the COVID-19 pandemic response since the outbreak of COVID-19. However, the impact of COVID-19 on the nursing workforce is largely unknown as is the emotional burden experienced by nurses throughout the different waves of the pandemic. Conventional approaches often use survey question-based instruments to learn nurses’ emotions, and may not reflect actual everyday emotions but the beliefs specific to survey questions. Social media has been increasingly used to express people’s thoughts and feelings. This paper uses Twitter data to describe the emotional dynamics of registered nurse and student nurse groups residing in New South Wales in Australia during the COVID-19 pandemic. A novel analysis framework that considered emotions, talking topics, the unfolding development of COVID-19, as well as government public health actions and significant events was utilised to detect the emotion dynamics of nurses and student nurses. The results found that the emotional dynamics of registered and student nurses were significantly correlated with the development of COVID-19 at different waves. Both groups also showed various emotional changes parallel to the scale of pandemic waves and corresponding public health responses. The results have potential applications such as to adjust the psychological and/or physical support extended to the nursing workforce. However, this study has several limitations that will be considered in the future study such as not validated in a healthcare professional group, small sample size, and possible bias in tweets. |
format | Online Article Text |
id | pubmed-10289963 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-102899632023-06-25 Leveraging twitter data to understand nurses’ emotion dynamics during the COVID-19 pandemic Zhou, Jianlong Sheppard-Law, Suzanne Xiao, Chun Smith, Judith Lamb, Aimee Axisa, Carmen Chen, Fang Health Inf Sci Syst Research The nursing workforce is the largest discipline in healthcare and has been at the forefront of the COVID-19 pandemic response since the outbreak of COVID-19. However, the impact of COVID-19 on the nursing workforce is largely unknown as is the emotional burden experienced by nurses throughout the different waves of the pandemic. Conventional approaches often use survey question-based instruments to learn nurses’ emotions, and may not reflect actual everyday emotions but the beliefs specific to survey questions. Social media has been increasingly used to express people’s thoughts and feelings. This paper uses Twitter data to describe the emotional dynamics of registered nurse and student nurse groups residing in New South Wales in Australia during the COVID-19 pandemic. A novel analysis framework that considered emotions, talking topics, the unfolding development of COVID-19, as well as government public health actions and significant events was utilised to detect the emotion dynamics of nurses and student nurses. The results found that the emotional dynamics of registered and student nurses were significantly correlated with the development of COVID-19 at different waves. Both groups also showed various emotional changes parallel to the scale of pandemic waves and corresponding public health responses. The results have potential applications such as to adjust the psychological and/or physical support extended to the nursing workforce. However, this study has several limitations that will be considered in the future study such as not validated in a healthcare professional group, small sample size, and possible bias in tweets. Springer International Publishing 2023-06-23 /pmc/articles/PMC10289963/ /pubmed/37359480 http://dx.doi.org/10.1007/s13755-023-00228-9 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Research Zhou, Jianlong Sheppard-Law, Suzanne Xiao, Chun Smith, Judith Lamb, Aimee Axisa, Carmen Chen, Fang Leveraging twitter data to understand nurses’ emotion dynamics during the COVID-19 pandemic |
title | Leveraging twitter data to understand nurses’ emotion dynamics during the COVID-19 pandemic |
title_full | Leveraging twitter data to understand nurses’ emotion dynamics during the COVID-19 pandemic |
title_fullStr | Leveraging twitter data to understand nurses’ emotion dynamics during the COVID-19 pandemic |
title_full_unstemmed | Leveraging twitter data to understand nurses’ emotion dynamics during the COVID-19 pandemic |
title_short | Leveraging twitter data to understand nurses’ emotion dynamics during the COVID-19 pandemic |
title_sort | leveraging twitter data to understand nurses’ emotion dynamics during the covid-19 pandemic |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10289963/ https://www.ncbi.nlm.nih.gov/pubmed/37359480 http://dx.doi.org/10.1007/s13755-023-00228-9 |
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