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Cross-sectional and prospective association between internet addiction and risk of fatigue among Chinese college students
Severe internet addiction (IA) is associated with a higher risk of musculoskeletal pain, but whether there is a significant prospective association between IA and fatigue is unclear. This study aimed to examine the association between IA and fatigue level among Chinese college students. A cross-sect...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Lippincott Williams & Wilkins
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9387967/ https://www.ncbi.nlm.nih.gov/pubmed/35984184 http://dx.doi.org/10.1097/MD.0000000000030034 |
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author | Liang, Siyu Ren, Zhongyu Yang, Guang |
author_facet | Liang, Siyu Ren, Zhongyu Yang, Guang |
author_sort | Liang, Siyu |
collection | PubMed |
description | Severe internet addiction (IA) is associated with a higher risk of musculoskeletal pain, but whether there is a significant prospective association between IA and fatigue is unclear. This study aimed to examine the association between IA and fatigue level among Chinese college students. A cross-sectional (n = 1011) and prospective study (n = 653) was conducted to examine the association between IA and risk of fatigue. IA was measured using Young internet addiction test. Fatigue level was evaluated using the Chalder fatigue scale. Multivariate logistic regression analyses showed a cross-sectional association between IA and the risk of fatigue. The odds ratios (95% CIs) of fatigue for normal, mild, and moderate to severe groups were 1.00 (reference), 1.88 (1.20, 2.95), and 5.60 (3.33, 9.42), respectively (P for trend: <0.001). Similarly, multivariate logistic regression analyses also revealed a significant prospective relationship between IA and the risk of fatigue during the 1-year follow-up period. The odds ratios (95% CIs) of fatigue for normal, mild, and moderate to severe groups were 1.00 (reference), 1.56 (0.67, 3.67), and 3.29 (1.08, 10.04), respectively (P for trend: 0.046). Our findings indicate that IA is positively related to risk of fatigue among Chinese college students. Further interventional studies are needed to explore the causality underlying the effects of IA on fatigue. |
format | Online Article Text |
id | pubmed-9387967 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Lippincott Williams & Wilkins |
record_format | MEDLINE/PubMed |
spelling | pubmed-93879672022-08-23 Cross-sectional and prospective association between internet addiction and risk of fatigue among Chinese college students Liang, Siyu Ren, Zhongyu Yang, Guang Medicine (Baltimore) Research Article Severe internet addiction (IA) is associated with a higher risk of musculoskeletal pain, but whether there is a significant prospective association between IA and fatigue is unclear. This study aimed to examine the association between IA and fatigue level among Chinese college students. A cross-sectional (n = 1011) and prospective study (n = 653) was conducted to examine the association between IA and risk of fatigue. IA was measured using Young internet addiction test. Fatigue level was evaluated using the Chalder fatigue scale. Multivariate logistic regression analyses showed a cross-sectional association between IA and the risk of fatigue. The odds ratios (95% CIs) of fatigue for normal, mild, and moderate to severe groups were 1.00 (reference), 1.88 (1.20, 2.95), and 5.60 (3.33, 9.42), respectively (P for trend: <0.001). Similarly, multivariate logistic regression analyses also revealed a significant prospective relationship between IA and the risk of fatigue during the 1-year follow-up period. The odds ratios (95% CIs) of fatigue for normal, mild, and moderate to severe groups were 1.00 (reference), 1.56 (0.67, 3.67), and 3.29 (1.08, 10.04), respectively (P for trend: 0.046). Our findings indicate that IA is positively related to risk of fatigue among Chinese college students. Further interventional studies are needed to explore the causality underlying the effects of IA on fatigue. Lippincott Williams & Wilkins 2022-08-19 /pmc/articles/PMC9387967/ /pubmed/35984184 http://dx.doi.org/10.1097/MD.0000000000030034 Text en Copyright © 2022 the Author(s). Published by Wolters Kluwer Health, Inc. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License 4.0 (CCBY) (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Liang, Siyu Ren, Zhongyu Yang, Guang Cross-sectional and prospective association between internet addiction and risk of fatigue among Chinese college students |
title | Cross-sectional and prospective association between internet addiction and risk of fatigue among Chinese college students |
title_full | Cross-sectional and prospective association between internet addiction and risk of fatigue among Chinese college students |
title_fullStr | Cross-sectional and prospective association between internet addiction and risk of fatigue among Chinese college students |
title_full_unstemmed | Cross-sectional and prospective association between internet addiction and risk of fatigue among Chinese college students |
title_short | Cross-sectional and prospective association between internet addiction and risk of fatigue among Chinese college students |
title_sort | cross-sectional and prospective association between internet addiction and risk of fatigue among chinese college students |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9387967/ https://www.ncbi.nlm.nih.gov/pubmed/35984184 http://dx.doi.org/10.1097/MD.0000000000030034 |
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