Xue Wang

Xue Wang

orcid

Research Focus & Metrics

Academic Career Length

5Years (2022-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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17 February 2023 in Journal of Medical Internet Research
Verified
Journal Article
Open access
XWXue Wang
Xue Wang
Yibo WuYibo Wu
Yibo Wu
ZMZhiyu Meng
Zhiyu Meng
JLJiayuan Li
Jiayuan Li
LXLi Xu
Li Xu
SZShuang Zang
Shuang Zang
Background: Despite the increased development and use of mobile health (mHealth) devices during the COVID-19 pandemic, there is little knowledge of willingness of the Chinese people to use mHealth devices and the key factors associated with their use in the post–COVID-19 era. Therefore, a more comprehensive and multiangle investigation is required. Objective: We aimed to probe Chinese attitudes regarding the use of mHealth and analyze possible associations between the attitude of willingness to use mHealth devices and some factors based on the socioecological model. Methods: A survey was conducted using quota sampling to recruit participants from 148 cities in China between June 20 and August 31, 2022. Data from the survey were analyzed using multiple stepwise regression to examine the factors associated with willingness to use mHealth devices. Standardized regression coefficients (β) and 95% CIs were calculated using multiple stepwise regression. Results: The survey contained a collection of 21,916 questionnaires and 21,897 were valid questionnaires, with a 99.91% effective response rate. The median score of willingness to use mHealth in the post–COVID-19 era was 70 points on a scale from 0 to 100. Multiple stepwise regression results showed that the female gender (β=.03, 95% CI 1.04-2.35), openness personality trait (β=.05, 95% CI 0.53-0.96), higher household per capita monthly income (β=.03, 95% CI 0.77-2.24), and commercial and multiple insurance (β=.04, 95% CI 1.77-3.47) were factors associated with the willingness to use mHealth devices. In addition, people with high scores of health literacy (β=.13, 95% CI 0.53-0.68), self-reported health rating (β=.22, 95% CI 0.24-0.27), social support (β=.08, 95% CI 0.40-0.61), family health (β=.03, 95% CI 0.03-0.16), neighbor relations (β=.12, 95% CI 2.09-2.63), and family social status (β=.07, 95% CI 1.19-1.69) were more likely to use mHealth devices. Conclusions: On the basis of the theoretical framework of socioecological model, this study identified factors specifically associated with willingness of the Chinese people to use mHealth devices in the post–COVID-19 era. These findings provide reference information for the research, development, promotion, and application of future mHealth devices.

23 June 2023 in Frontiers in Nutrition
Verified
Journal Article
Open access
XWXue Wang
Xue Wang
Yibo WuYibo Wu
Yibo Wu
XSXinji Shi
Xinji Shi
YCYu Chen
Yu Chen
YXYahong Xu
Yahong Xu
SZShuang Zang
Shuang Zang
Background: A healthy lifestyle is beneficial to individuals’ health. However, little is known about the associations of lifestyle factors with mental health and well-being. This study examined the associations of lifestyle factors with mental health (i.e., depression, anxiety, loneliness, perceived pressure, and self-rated health status) and well-being in Chinese adults.Methods: A nationally representative survey was conducted in China from 20 June 2022 to 31 August 2022. Data from the survey were analyzed using multiple linear regression to determine the associations of lifestyle with mental health and well-being in Chinese adults. Standardized regression coefficients (β) and 95% confidence intervals (CIs) were estimated using multiple linear regression.Results: The survey included 28,138 Chinese adults. Multiple linear regression results showed that there were significant negative associations of lifestyle scores with scores of depression (β = −0.93, 95% CI: −0.98, −0.88), anxiety (β = −0.71, 95% CI: −0.76, −0.67), loneliness (β = −0.23, 95% CI: −0.24, −0.21), and perceived pressure (β = −0.19, 95% CI: −0.22, −0.16). Moreover, there were significant positive associations of lifestyle with self-rated health status (β = 1.99, 95% CI: 1.79, 2.20) and well-being (β = 0.96, 95% CI: 0.91, 1.02).Conclusion: This study provides insight into the associations of lifestyle factors with mental health and well-being and highlights the importance of improving and maintaining healthy lifestyle behaviors for favorable mental health and well-being.

16 February 2023 in Journal of Affective Disorders
Verified
Journal Article
Closed access
XWXue Wang
Xue Wang
HCHefang Chen
Hefang Chen
YLYu Liu
Yu Liu
ZZZhe Zhao
Zhe Zhao
SZShuang Zang
Shuang Zang

5 September 2023 in BMC Public Health
Verified
Journal Article
Open access
PDF file
XWXue Wang
Xue Wang
Yibo WuYibo Wu
Yibo Wu
JMJuanxia Miao
Juanxia Miao
KPKeping Pu
Keping Pu
WMWai-Kit Ming
Wai-Kit Ming
SZShuang Zang
Shuang Zang
Background: The eating behaviors of older adults are associated with multiple factors. To promote older adults’ healthy diets, it is imperative to comprehensively study the factors associated with the eating behaviors of the aging population group. This study aimed to probe the associated factors of older adults’ eating behaviors from a socioecological model (SEM) perspective. Methods: In 2021, a cross-sectional survey was performed to recruit participants in China. The survey data were analyzed using a multivariate generalized linear model to identify the factors associated with eating behaviors in older adults. Standardized regression coefficients (β) and 95% confidence intervals (CIs) were estimated using a multivariate generalized linear model. Results: The survey contained 1147 valid older adult participants. Multivariate generalized linear model results showed that older adults with older age [aged 71–80 (β = -0.61), ≥ 81 (β = -1.12)], conscientiousness personality trait (β = -0.27), and higher family health levels (β = -0.23) were inclined to have better eating behaviors. The older adults with higher education levels [junior high school and high school (β = 1.03), junior college and above (β = 1.71)], higher general self-efficacy (β = 0.09), more severe depression symptoms (β = 0.24), and employment (β = 0.82) tended to have poorer eating behaviors. Conclusions: This study identified factors that are specifically associated with older adults’ eating behaviors from an SEM perspective. The comprehensive multiple-angle perspective consideration may be a valuable idea for studying healthy eating behaviors in older adults.

24 January 2024 in Journal of Affective Disorders
Verified
Journal Article
Closed access
XWXue Wang
Xue Wang
ZYZhihua Yin
Zhihua Yin
YYYing Yang
Ying Yang
XFXiao Fu
Xiao Fu
CGChaowei Guo
Chaowei Guo
SZShuang Zang
Shuang Zang