scholarly journals Validation of Self-Reported Smartphone Usage Against Objectively-Measured Smartphone Usage in Hong Kong Chinese Adolescents and Young Adults

Author(s):  
Paul H. Lee ◽  
Andy C. Y. Tse ◽  
Cynthia S. T. Wu ◽  
Yim Wah Mak ◽  
Uichin Lee
2020 ◽  
Vol 74 ◽  
pp. 39-47 ◽  
Author(s):  
Shuang-Jiang Zhou ◽  
Lei-Lei Wang ◽  
Rui Yang ◽  
Xing-Jie Yang ◽  
Li-Gang Zhang ◽  
...  

2022 ◽  
Vol 22 (1) ◽  
Author(s):  
Xuechan Lyu ◽  
Tianzhen Chen ◽  
Zhe Wang ◽  
Jing Lu ◽  
Chenyi Ma ◽  
...  

Abstract Background In recent years, there have been frequent reports of gaming disorder in China, with more focus on young people. We developed and psychometrically tested a Gaming Disorder screening scale (i.e., Gaming Disorder Screening Scale - GDSS) for Chinese adolescents and young adults, based on the existing scales and diagnostic criteria, but also considering the development status of China. Methods For testing content and criterion validity, 1747 participants competed the GDSS and the Internet Addiction Test (IAT). After 15 days, 400 participants were retested with the scales for to assess test-retest reliability. Besides, 200 game players were interviewed for a diagnosis of gaming disorder. Results The Cronbach’s alpha coefficient on the GDSS was 0.93. The test-retest coefficient of 0.79. Principal components analysis identified three factors accounting for 62.4% of the variance; behavior, functioning, cognition and emotion. Confirmatory factor analysis showed a good model fit to the data (χ2 /df = 5.581; RMSEA =0.074; TLI = 0.916, CFI = 0.928). The overall model fit was significantly good in the measurement invariance tested across genders and different age groups. Based on the clinical interview, the screening cut-off point was determined to be ≥47 (sensitivity 41.4%, specificity 82.3%). Conclusions The GDSS demonstrated good reliability and validity aspects for screening online gaming disorder among Chinese adolescents and young adults.


2007 ◽  
Vol 84 (5) ◽  
pp. 704-721 ◽  
Author(s):  
Joseph T. F. Lau ◽  
Hi Yi Tsui ◽  
Lawrence T. Lam ◽  
Mason Lau

SLEEP ◽  
2008 ◽  
Vol 31 (2) ◽  
pp. 185-194 ◽  
Author(s):  
Ka-Fai Chung ◽  
Miao-Miao Cheung

2020 ◽  
Author(s):  
Paul H Lee ◽  
Andy C. Y. Tse ◽  
Cynthia S. T. Wu ◽  
Yim Wah Mak ◽  
Uichin Lee

Abstract Objectives: We studied the association between objectively-measured smartphone usage and objectively-measured sleep quality and physical activity for seven consecutive days among Hong Kong adolescents and young adults aged 11–25 (n = 357, 67% female).Methods: We installed an app that tracked the subjects’ smartphone usage and had them wear an ActiGraph GT3X accelerometer on their wrist to measure their sleep quality and physical activity level. Smartphone usage data were successfully obtained from 187 participants (52.4%).Results: The participants on average spent 2 hours 46 minutes per day on their smartphone. Multilevel regression showed that, among secondary school students, one minute of daytime smartphone usage was associated with 0.12 minute decrease in total sleeping time that night (p = 0.042, 95% CI: -0.23, -0.007). One minute of bedtime smartphone usage was associated with 0.32 minute increase in wake after sleep onset that night (p = 0.04, 95% CI: 0.02, 0.62). One minute of smartphone usage during sleep was associated with sleep efficiency (β = 0.013%, p = 0.01, 95% CI: 0.003%, 0.023%) and WASO (β=-0.05, p = 0.04, 95% CI: -0.10, -0.005). One minute of daytime smartphone usage was associated with 7.15 steps increase in the number of steps (p = 0.02, 95% CI: 1.02, 13.28) among secondary school students and 3.52 steps increase in the number of steps (p = 0.03, 95% CI: 0.37, 6.66) among university students on the next day.Conclusion: Time spent on smartphone was associated with total sleeping time, the number of steps, and MVPA among Hong Kong adolescents and young adults.


Sign in / Sign up

Export Citation Format

Share Document