Smartphone Use Time and Total Screen Time Among Students Aged 10–19 and the Effects on Academic Stress: A Large Longitudinal Cohort Study in Shanghai, China
Abstract:ObjectiveThis study aimed to assess smartphone use time and total screen time among students aged 10–19 in Shanghai, China, and examine their effects on academic stress.MethodsBaseline and follow-up surveys were conducted in December 2017 and December 2018, respectively, using a cohort study design with 1,771 participants. Questionnaire surveys and physical examinations of participants were conducted by trained investigators and professional school physicians, respectively. The self-administered questionnaire … Show more
“…Therefore, when testing the mediating effects, we controlled for these variables to ensure the accuracy and reliability of the results. [50][51][52] The significance level for this study was set at alpha=0.05.…”
During the period of COVID-19 pandemic, the social restrictions and isolation exerted a significant impact on the sleep quality of Chinese college students. This study aims to delve into the influence of physical activity on the sleep quality of college students as well as the mediating roles of stress and smartphone addiction. Materials and Methods: A cohort of 274 eligible college students (146 males and 128 females) were selected for the investigation. The International Physical Activity Questionnaire Short Form, Stress Perception Scale, Smartphone Addiction Scale, and Pittsburgh Sleep Quality Index were employed to assess the levels of physical activity, stress, smartphone addiction, and sleep quality among college students. For data analysis, descriptive statistics, correlation analysis, and chained mediation effect tests were performed sequentially. Results: The findings revealed: (1) a significant negative correlation between physical activity and stress, smartphone addiction, and sleep quality among college students (r = −0.216, p < 0.001; r = −0.224, p < 0.001; r = −0.259, p < 0.001); (2) independent mediating roles of stress and smartphone addiction in the relationship between physical activity and sleep quality; and (3) chained mediating effects of stress and smartphone addiction in the association between physical activity and sleep quality.
Conclusion:This study deepens our comprehension of how physical activity augments the quality of slumber, concurrently emphasizing that mitigating stress levels and alleviating smartphone addiction constitute effective strategies for preventing sleep issues among college students.
“…Therefore, when testing the mediating effects, we controlled for these variables to ensure the accuracy and reliability of the results. [50][51][52] The significance level for this study was set at alpha=0.05.…”
During the period of COVID-19 pandemic, the social restrictions and isolation exerted a significant impact on the sleep quality of Chinese college students. This study aims to delve into the influence of physical activity on the sleep quality of college students as well as the mediating roles of stress and smartphone addiction. Materials and Methods: A cohort of 274 eligible college students (146 males and 128 females) were selected for the investigation. The International Physical Activity Questionnaire Short Form, Stress Perception Scale, Smartphone Addiction Scale, and Pittsburgh Sleep Quality Index were employed to assess the levels of physical activity, stress, smartphone addiction, and sleep quality among college students. For data analysis, descriptive statistics, correlation analysis, and chained mediation effect tests were performed sequentially. Results: The findings revealed: (1) a significant negative correlation between physical activity and stress, smartphone addiction, and sleep quality among college students (r = −0.216, p < 0.001; r = −0.224, p < 0.001; r = −0.259, p < 0.001); (2) independent mediating roles of stress and smartphone addiction in the relationship between physical activity and sleep quality; and (3) chained mediating effects of stress and smartphone addiction in the association between physical activity and sleep quality.
Conclusion:This study deepens our comprehension of how physical activity augments the quality of slumber, concurrently emphasizing that mitigating stress levels and alleviating smartphone addiction constitute effective strategies for preventing sleep issues among college students.
“…Moreover, compared with primary and middle school students, high school students had less exercise time, more sedentary time, and worse mental health as a result of the higher requirements for study ( 50 , 51 ), which could weaken the relationship between PSU and BP. So far, the majority of literature only use screen time to explore the association between the use of electronic devices and adolescents' health ( 32 , 52 ). However, increasing researchers argued that researchers should not only focus on screen time when exploring the health impact of the use of electronic devices for adolescents ( 53 , 54 ).…”
Section: Discussionmentioning
confidence: 99%
“…Teachers were enrolled to distribute the questionnaires. The detailed questionnaire design has been mentioned in previous study ( 32 ). All participants were asked to fill out a questionnaire regarding several variables, covering demographic information (e.g., age, sex, grade group), behavioral variables (indoor physical activity time, outdoor physical activity time, sedentary time, and screen time), and physiological characteristics (study pressure and well-being).…”
ObjectivesThis study aimed to (1) examine the cross-sectional association between problematic smartphone use (PSU) and blood pressure (BP) in children and adolescents and (2) determine whether the association between PSU and BP differs by the grade of students.MethodsWe recruited a total of 2,573 participants from 14 schools in Shanghai by a two-stage sampling method. We derived BP data from the participant's most recent medical examination data, including systolic blood pressure (SBP) and diastolic blood pressure (DBP). We measured PSU by a modified PSU Classification Scale. We also assessed demographic characteristics, body mass index, behavioral variables, and physiological characteristics.ResultsHigh school students had higher BP and PSU scores than primary and middle school students. PSU on the dimension of information collection was associated positively with both SBP and DBP among primary and middle school students, with the β (95% CI) values of 0.282 (0.018, 0.546) and 0.229 (0.031, 0.427). Meanwhile, the dimension of the relationship of social network was associated positively with SBP among primary and middle school students, with a β (95% CI) value of 0.390 (0.062, 0.717). PSU on the dimension of information collection was positively associated with the development of high BP, with a OR (95% CI) value of 1.072 (1.011, 1.137) among primary and middle school students.ConclusionsPSU might be a potential correlate of high BP among school-age children and adolescents. The associations between PSU and BP differed by the grade of students as well as according to the four dimensions of PSU.
“…The current literature supports links between negative associations of social ST and educational activities. Liu et al (2022) examined the effects of smartphone use in students aged 10-19 in Shanghai, China and found that more than 30% of adolescents used smartphones for social and entertainment purposes. Spending ample time on social media and entertainment took time away from participation in other various activities and, therefore, may have influenced children's interest and preferences in completing self-improvement activities such as doing homework, which is vital for their learning development.…”
Section: Association Between Children's St Use and Their Self-reporte...mentioning
Introduction: In recent years, screen-based activities have become increasingly popular amongst children and adolescents. Several studies have found increased screen time to be associated with sleep disturbances, poorer academic performance and reduced physical activity. However, not much is known about children’s activity preferences and participation in relation to their screen time. This study investigated the association between school-aged children’s screen time use and their activity participation and physical activity. Method: A sample of 25 parents/caregivers with typically developing children aged 8–12 years in Australia participated. Parents/caregivers completed the Children Screen Time Use Report (CSTUR) and Children Participation Questionnaire-School (CPQ-S). Child participants completed the CSTUR, Preferences for Activities of Children (PAC), Perceived Meaning of Occupations Questionnaire (PMOQ) and Physical Activity Questionnaire-Children (PAQ-C). Data were analyzed using Spearman Rho correlations. Results: Findings from this study found no statistically significant associations between the CSTUR and PAQ-C subscales in children aged 8–12 years. However, there were several significant correlations found between CSTUR and the PAC, PMOQ and CPQ-S scale scores. Conclusion: Occupational therapists need to consider screen-based activities in school age children and the impact it can have on their daily participation.
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