Dr. CUI Dandan (first author), associate professor of the Institute of Artificial Intelligence in Sports (IAIS), and ZHANG Xiangning (co first author), a master’s student of Grade 2022 of IAIS, under Dr. CUI’s guidance, co-published an academic paper entitled “The Impact of the COVID-19 Pandemic on Physical Activity and Sleep among Healthy Adults: A Systematic Review and Meta-analysis” in the Movement Science column of Frontiers in Psychology (IF=3.8).
Background: The COVID-19 pandemic has had a significant impact on physical and mental health, while physical activity and sleep are two important indicators of the impact that have been explored in recent studies. However, the results of studies with different measurement methods and populations with different levels of physical activity have been diverse in that physical activity and sleep are affected by the COVID-19 pandemic in some studies but not in others. Our study aimed to investigate the impact of the COVID-19 pandemic on physical activity and sleep and the role of measurement methods and populations on results.
Methods: PubMed, Web of Science, and CNKI databases were used to search for related studies systematically. Study characteristics and data on physical activity and sleep were collected and analyzed from each included study. Standardized mean differences (SMDs) with 95% confidence intervals (CIs) were used to estimate pooled effect sizes.
Results: A total of 13 articles were included in the systematic review, 11 of which were included in the meta-analysis. We found that moderate-to-vigorous physical activity (MVPA) time was 0.33 (95% CI 0.07 to 0.59) and sleep quality was 0.37 (95% CI 0.21 to 0.53) decreased, while sleep duration was −0.24 (95% CI −0.28 to −0.20) increased during the lockdown; overall physical activity time had no significant difference (p = 0.07) during the lockdown. The “wearables” subgroup had no heterogeneity (p = 0.89, I2 = 0) in sleep duration, while MVPA time measured by subjective scales was not significantly changed. The “elite athletes” subgroup had lower heterogeneity (p = 0.69, I2 = 0) in sleep duration than general adults, while the results of sleep quality for population subgroups were significant and there was no heterogeneity within either.
Conclusion: The COVID-19 pandemic had a significant impact on MVPA time, sleep duration, and sleep quality, instead of overall physical activity time among healthy adults. The results of MVPA time and sleep duration were greatly influenced by the measurement methods, and sleep behavior differed among populations with varying physical activity levels. Thus, when researching physical activity, especially MVPA time, should consider measurement methods, and more attention should be given to differences in populations when researching sleep behavior.
Journal Introduction
Frontiers in Psychology focuses on psychological research, covering clinical research, imaging research, social psychology research and other fields. The Movement Science and Sport Psychology column aims to provide a platform for innovative research and promote people’s understanding on the multifaceted nature of sports performance. The interdisciplinary characteristics of scientific investigation are encouraged, and high-quality research in the fields of motion control and learning, sports and exercise psychology, social psychology of human sports, and physical rehabilitation has been published.
Author Information
First author and correspondence author: Dr. CUI Dandan is an associate professor at IAIS, with all her bachelor’s, master’s and doctoral degrees granted from the Department of Computer Science and Technology of Tsinghua University. Her main research interests are sports big data analysis and intelligent sports training decision-making. She formerly served as the project leader of the National Sprint Relay Team in preparation for the Tokyo Olympics in 2021, and currently leads a youth program funded by the National Natural Science Foundation of China.
First author (co): ZHANG Xiangning, a master’s student of Grade 2022 of IAIS, mainly focuses on sports training intelligence and sports big data analysis, under the supervision of associate professor CUI Dandan.
