Adolescent Screen Time and Sleep Quality: Predictive Factors and Their Effect on Academic Achievement Among Adolescents in Jordan

SummaryThe COVID‐19 pandemic had a major impact on people of all ages. Adolescents' exposure to online learning is linked to excessive screen time on digital devices, which leads to poor sleep quality. This study aimed to investigate the association between screen time on different electronic devices and sleep quality among adolescents in the United Arab Emirates. This study was based on a self‐reported questionnaire, which was administered online to school‐aged adolescents (aged 12–19 years). The multicomponent questionnaire collected information on sociodemographic characteristics, sleep quality using the Pittsburgh Sleep Quality Index (PSQI), and screen time (minutes) on TV, TV‐connected devices, laptops, smartphones, and tablets on weekdays, weeknight, and weekends using the Screen Time Questionnaire (STQ). Univariate and multivariate analyses were used to identify factors correlated with poor sleep quality. A total of 1720 adolescents were recruited from private and public schools (mean age 14.6 ± 1.97 years). The mean PSQI score was 8.09 ± 3.37, and 74.3% of participants reported poor sleep (cutoff score >5). Mean scores were highest for the sleep latency (1.85 ± 0.97) and sleep disturbance (1.56 ± 0.62) domains. The highest STQ score was observed for smartphones, with a median screen time of 420 min on weekdays and 300 min on weekends. Screen time related to smartphones on weekends (p = 0.003) and increased screen time in bed (p < 0.001) were significantly associated with poor sleep. Our results confirmed the correlation between sleep and screen time in adolescents. The results may inform educational polices that target screen time and sleep among adolescents during and after the COVID‐19 pandemic.

BackgroundTime spent on screen devices affects sleep quality and duration leading to several health impairments in youth. Although physical activity (PA) benefits sleep patterns and decreases screen time in adolescents, it is unclear whether the relationship between sleep quality/duration and screen time could be influenced by PA levels. ObjectiveTo analyze the association between sleep quality and duration with screen time in Brazilian adolescents according PA levels. MethodsThe sample included 1010 adolescents aged 13.2 ± 2.4 years (n = 556 females − 55 % of the sample). Sleep quality and sleep duration, and PA were assessed by Mini Sleep and Baecke questionnaires, respectively. Participants in the highest quartile were classified as physically active. Screen time was analyzed by the self-reported number of hours spent on different screen devices (i.e., television, computer, videogame, and cellphone/tablet). Participants in the highest tertile were classified as having high screen time. Sex, age, and body mass index were considered covariates in binary logistic regression models. ResultsPoor sleep quality was observed in 52.3 % of the sample, whereas 46.6 % reported sleeping less than eight hours/day. High screen time was associated with poor sleep quality (OR = 1.45; 95 %CI = 1.01–2.12) and insufficient sleep duration (OR = 1.52; 95 %CI = 1.01–2.03) in adolescents insufficiently active. There were no associations between screen time and sleep parameters in active adolescents. ConclusionHigh screen time was associated with poor sleep quality and insufficient sleep duration only in insufficiently active adolescents. These results suggest that high PA levels may contribute to improving sleep patterns in pediatric population.

The pervasive influence of technology, particularly screen usage, on daily routines and its implications for sleep quality, mental health, academic performance, and physical activity has become an increasing area of concern. Objective: To evaluate the daily screen time of students from different fields of study and to assess its association with demographic variables, sleep quality, psychological symptoms, physical activity, and academic performance. Methods: This study was performed at Isra University, Hyderabad from February 2024 to August 2024, with 152 participants. Data on demographics, sleep quality (PSQI), mental distress (DASS-42), academic performance, and screen time were collected after informed consent. Statistical analysis, conducted using SPSS version 25.0, determined correlations between daily screen time, PSQI, and DAS scores. Results: The participants had a mean age of 20.59 ± 2.16 years, with most residing in urban areas (87.5%) and being day scholars (74.34%). Average daily screen time was 5.85 ± 1.14 hours, significantly higher among those with GPAs below 2.5 and low physical activity levels (p&lt;0.05). Mean scores for depression, anxiety, stress, and PSQI were 13.34 ± 12.01, 11.17 ± 9.41, 15.32 ± 11.09, and 6.45 ± 3.48, respectively. Screen time positively correlated with depression (r = 0.81, p&lt;0.01), anxiety (r = 0.78, p&lt;0.01), stress (r = 0.83, p&lt;0.01), and PSQI (r = 0.75, p&lt;0.01). Conclusion: Increased screen time was linked to poorer sleep quality, elevated mental distress, and reduced academic performance, particularly in urban populations and individuals using screens for recreation.

Objectives: This study aims to investigate the relationship between screen time, sleep quality, and BMI among students at the University of Jordan. Specific objectives include assessing the levels of sleep quality and average screen time, examining gender differences in these variables, and exploring their correlation with BMI. Methods: A cross-sectional study was conducted involving 541 students (299 males and 242 females) from the University of Jordan. Participants completed health and lifestyle questionnaires, including the Sleep Quality Scale (SQS) and the Questionnaire for Screen Time of Adolescents (QueST). BMI was calculated from measured height and weight. Statistical analyses, including t-tests and correlation coefficients, were employed to explore the relationships between variables. Results: The study found a moderate level of sleep quality among students (mean SQS score: 1.45). The average daily screen time was 4 hours and 31 minutes, with significant differences between males and females in non-academic screen time activities. A significant negative correlation was observed between sleep quality and BMI (p &lt; 0.05). Additionally, higher screen time was significantly associated with higher BMI (p &lt; 0.05), with gender differences observed in both sleep quality and screen time behaviors. Conclusions: The findings indicate that prolonged screen time and poor sleep quality are prevalent among university students and are significantly associated with higher BMI. These insights highlight the need for interventions targeting screen time reduction and sleep quality improvement to promote healthier lifestyles and prevent obesity among students.

Background The percentage of adults spending >40hrs/week online has increased by 14% in the last decade.1 Increased screen time is associated with poor sleep quality, which in turn influences memory and attention. This study tested the hypothesis that increased daily screen time was associated with significantly decreased sleep quality. Methods Data was collected, with ethical approval, over three mornings (May 2019) from 399 randomly selected members of the public in South Kensington. A questionnaire with 15 questions, including age, gender, total daily screen time, sleep onset latency, and daytime alertness was used. A representative sample size of 369 was calculated, based on the daily footfall of Exhibition Road (32,422). 16 responses were excluded due to incomplete questionnaires, sleep disorders and jet lag. Results Data from participants aged 18–34 was selected for analysis (n=223, 55.9% of the total responses). Respondents who answered ‘no’ to the question ‘Have you had enough sleep to feel alert?’ had a significantly higher mean total screen time than those who answered ‘yes’ (figure 1: Mean±SEM, alert (‘yes’): 10± 0.38 hours, not alert (‘no’): 11.2±0.45 hours, p=0.02). There was no significant correlation between the total daily screen time and sleep onset latency (Figure 2: spearman’s ρ=0.059 and p=0.38). Conclusion The main finding of this study was that increased total daily screen time was associated with reduced daytime alertness, and a reduced sleep quality in members of the public aged 18–34 years. Although, screen time did not have a significant impact on sleep onset latency. This research could potentially raise awareness about the impact of screen time on sleep, and help inform future research into this area. Acknowledgements With special thanks to our fellow Sleep CRI project members for their contribution to data collection. Reference Ofcom. A decade of digital dependency. Available from: https://www.ofcom.org.uk/about-ofcom/latest/features-and-news/decade-of-digital-dependency [Accessed 04.06.19]

Background: Academic performance and screen time are closely linked, as excessive screen use can impact focus, retention, and overall learning outcomes. Understanding this relationship is essential for promoting healthier digital habits and improving student achievement. This study explores the relationship between screen time and students' academic performance. Methods: This cross-sectional study examined the association between screen time and academic achievement among 80 dental students. The study employed a convenience sampling method. Participants reported their daily screen usage through the Digital Wellbeing tool. Statistical analysis was conducted using the chi-square test in SPSS software version 25.0. Results: This study explored the relationship between gender, year of study, and screen time among dental students. Students with lower screen time showed better academic performance, with a higher proportion in the "good" and "average" categories. These findings suggest a potential association between increased screen time and poorer academic performance, though further research is needed to establish causality. Conclusion: This study suggests a potential link between higher screen time and poorer academic performance among dental students. Students with more screen exposure tended to perform worse academically, while those with less screen time performed better. However, further research is needed to confirm causality and explore ways to manage screen time for improved academic outcomes.

Introduction Studies have emphasized the significance of sleep in performance and well-being of young athletes. Physical activity has been shown to improve various aspects of sleep in adolescents, including sleep quality. Yet, excessive screen time has been found to have a negative impact on sleep among adolescents, possibly dampening the beneficial effects of physical activity. Hence, our research aimed to investigate the moderating effect of screen time on the relationship between physical activity and sleep quality in young athletes. Methods 211 young elite athletes (M=14.9±1.6 years old; 60.4% females) completed online questionnaires, including the Pittsburgh Sleep Quality Index (PSQI) and a homemade sports and lifestyle habits questionnaire. A moderation analysis was conducted using PROCESS 4.2 to examine the moderating effect of screen time (the average number of hours per day spent on screens) on the relationship between physical activity (the average number of training hours per week) and sleep quality (subscale #1 of the PSQI). Age, BMI, and sex were added as covariates, since they were correlated with the physical activity and sleep quality variables. Results The moderation model was significant (F(6,203)=8.14, p&amp;lt;.001) and accounted for 16.2% of the variance. Results indicate a significant main effect of screen time on sleep quality (b=.294, p=.004) and a significant interaction of screen time and physical activity on sleep quality (b=.005, p=.021). Physical activity was associated with sleep quality when screen time was at one SD below the mean (b=-.025, p&amp;lt;.018) but not at the mean (b=-.006, p&amp;lt;.433) nor above the mean (b=.014, p&amp;lt;.236). The simple plot analysis revealed that when young athletes had low screen time, more physical activity was related to better sleep quality, while lower training hours were associated with poorer sleep quality. However, in athletes with high and average screen time, their level of physical activity was not related to their sleep quality. Conclusion This study highlights the possible mitigating effect of screen time on the potential beneficial association between physical activity and sleep in young athletes. This underscores the importance of promoting healthy lifestyle habits and appropriate sleep hygiene among athletes, who are also a population at greater risk of sleep disturbances. Support (if any)

Background: Excess screen viewing can deteriorate the well-being of under-five children. Identifying the modifiable screen determinants can pave the way to develop strategies for optimization. Objectives: The objective of the study was to study the profile of screen time among children between 12 and 59 months of age and to determine the risk factors associated with increased screen time. Materials and Methods: A community-based cross-sectional study was done in rural villages of Tamil Nadu among 418 children aged 12–59 months by universal sampling method during August 2021 to January 2022. Parents of the children were interviewed using a predesigned semi-structured questionnaire. Results: The prevalence of screen viewing among the study population was 96.9% and their average screen time was 106.85 ± 77.95 min/day. The prevalence of excess screen time (nonadherence to the WHO recommendations) was estimated to be 70%. The most common reason for offering screen time to children was feeding/mealtime (45.7%). The risk determinants identified for higher screen time were access to multiple gadgets (P &lt; 0.001), first screen exposure before 1 year of age (P &lt; 0.001), having erratic screen-viewing hours (P = 0.002), snacking during screen time (P &lt; 0.001), screen time before bed (P &lt; 0.001), and those who were overweight (P = 0.027). Maternal screen time and children’s screen time had a positive association (r = 0.367, P &lt; 0.001), whereas children’s screen time and sleep duration were negatively associated (r = −0.139, P = 0.004). Conclusions: This study reiterates the high prevalence of excess screen time among the study population. Multiple risk determinants identified can be utilized to plan interventions and awareness programs to regulate screen time in under-five children.

Under the burden caused by COVID-19 and rapid lifestyle changes, many people increased their screen time due to psychological needs and social requirements. The current study investigated the relationship between screen time changes and anxiety symptoms during the pandemic of COVID-19. Furthermore, we examined whether sleep and physical activity would mediate the association between screen time changes and anxiety. The self-developed questionnaire was delivered online to collect people’s changes in anxiety, sleep patterns, and screen time during COVID-19. 970 participants (74.4% female) with an average age of 23 years were involved in this study. After adjusting demographic variables, the ordinal logistic regression analyses revealed that a significant increase in screen time was linked with anxiety. Slightly increased screen time, slightly and significantly decreased screen time did not predict anxiety symptoms during the pandemic. The level of anxiety was significantly higher among respondents who reported decreased sleep quality. Sleep quality directly mediated the association between screen time changes and anxiety, while sleep latency did not. The longer sleep latency caused by increased screen time would amplify anxiety by affecting sleep quality. In addition, the relationship between screen time changes and anxiety was also mediated by physical activity. We concluded that the fluctuation of screen time in a modest range does not affect the anxiety level substantially. The significantly increased screen time would contribute to poor sleep (including longer sleep latency and worse sleep quality) and lack of physical activity, which would lead to higher levels of anxiety.

BackgroundThe widespread use of digital devices among adolescents has raised concerns about the potential impact of screen time on sleep quality. This study aimed to investigate the relationship between screen time and self-reported sleep quality in adolescents.MethodsA cross-sectional study was conducted on adolescents (13- to 19-year-olds) using multi-stage cluster sampling with probability proportional to the size of public schools. Data were collected in November 2022 through self-administered questionnaires. The questionnaire collected sociodemographic characteristics, sleep quality using the Pittsburgh Sleep Quality Index (PSQI), and screen time on weekdays and weekends using the Screen Time Questionnaire (STQ). A scoring system was used in the PSQI and a global score of more than 5 indicates poor sleep quality. The relationship between screen time and sleep quality was analysed using simple and multiple linear regression.ResultsA total of 547 adolescents participated in the study, with a mean (SD) age of 16.66 (1.54) years. The mean (SD) PSQI score was 5.98 (2.70), and 52% of participants had poor sleep quality. The sleep disturbance component had the highest mean (SD) score at 1.35 (0.5) out of a total score of 3.0. The mean (SD) screen time for a weekday was 537.6 (301.5) minutes, and a weekend day was 725.5 (339.2) minutes. The highest median screen time was spent on smartphones during the whole week. A significant linear relationship was observed between age and PSQI global score (p = 0.008), with a 0.2 increase in PSQI global score for each year increase in age (95% CI: 0.05, 0.35). Being female was also significantly associated with a high PSQI global score (p < 0.001). Additionally, a significant linear relationship was observed between screen time on a weekend and PSQI score (p = 0.032).ConclusionsThe study found that half of the adolescents had poor sleep quality, which was associated with being female, increased screen time on weekends, and older age. Future research endeavours should focus on conducting longitudinal studies to assess the temporal relationship between screen time and sleep quality.

Academic performance is a complex and multifaceted concept encompassing psychological, behavioral, and lifestyle components. The current study investigates the relations between sleep quality, stress, screen time, and physical activity with regard to predicting academic performance of students. Furthermore, it examines the role of sleep quality in mediating stress, screen time, and academic performance. The study adopted a cross-sectional design in collecting the data from the students using standardized questionnaires about sleep quality, stress levels, screen time, physical activity, and academic performance. In the correlation analysis, poor sleep quality showed significant correlation with lower academic performance (r = -0.45, p &lt; 0.001) and high stress (r = -0.50, p &lt; 0.001). Stress (r = -0.30, p &lt; 0.001) and screen time (r = -0.25, p &lt; 0.001) also exhibited negative correlation with academic performance, while physical activity showed a positive correlation (r = 0.20, p &lt; 0.05). Multiple regression analysis confirmed that stress (B = -0.42, p &lt; 0.001), sleep quality (B = -0.35, p &lt; 0.001), and screen time (B = -0.28, p = 0.001) are negative predictors of academic performance, and physical activity (B = 0.25, p = 0.002) is a positive predictor. It was established by the mediating analysis that sleep quality may have played a partial role in mediating the relations between stress and academic performance (B = -0.28, p &lt; 0.001) and between screen time and academic performance (B = -0.17, p &lt; 0.001). The study highlights sleep quality as one of the critical factors influencing academic performance, thus functioning as a major mediator in the negative impacts of stress and screen time. Stress management strategies and increased screen exposure should be approached with care, coupled with stress management strategies, for improved student success. Physical activity may act as a buffer against negative sleep quality and stress.

Background: Over half of the population in most nations use mobile phones and its use is expanding rapidly. The amount of time spent using a screen-enabled device like a smartphone, computer, television, or video game console is known as screen time. In addition, increased screen time has also been quite prevalent amongst medical students due to the recent trend of screen-based readings and various other reasons. Aims &amp; Objectives: To demonstrate that medical undergraduate students suffer from poor-quality sleep as a result of excessive screen time. Methodology: A cross sectional study was conducted among 279 UG (Undergraduate) students of Medical College at Ahmedabad, Gujarat from August 2021 to September 2022. Results: There was a positive correlation between MRSRF(Mobile Related Sleep Risk Factors Questionnaire) factors like “screen usage time”, “time spent on social media”, “duration of mobile use after lights have been turned off”, “keeping mobile phone near pillow/bed while sleeping” and sleep parameters(PSQI components) like daytime dysfunction, sleep disturbance, sleep latency and worsening of subjective sleep quality and this correlation was statistically significant. Conclusion: Total screen time, time spent on social media, duration of mobile use after lights have been turned off, and keeping a mobile phone on the bed and near the pillow while sleeping worsens the quality of sleep and also leads to daytime dysfunction, sleep disturbance, sleep latency, and worsening of subjective sleep quality.

The coronavirus 2019 (COVID-19) pandemic has led to laws and policies including national school closures, lockdown or shelter in place laws, and social distancing recommendations that may translate to higher overall screen time among children and adolescents for the duration of these laws and policies. These policies may need to be periodically re-instated to control future COVID-19 recurrences or other national emergencies. Excessive screen time is associated with cardiovascular disease risk factors such as obesity, high blood pressure, and insulin resistance because it increases sedentary time and is associated with snacking.

Background: Poor sleep quality in school children can negatively impact their neurocognitive abilities and academic achievement. Increased screen time was shown to interfere with children’s sleep habits and disrupts their sleep pattern. This study aimed to understand the sleep patterns and sleep disorders in school children and the influence of screen time on sleep in children during the COVID-19 pandemic. Methods: This cross-sectional observational school-based study was done on 443 children aged 6-12 years. Data was collected through parent filled online questionnaire having a proforma and child sleep habit questionnaire (CSHQ), a validated questionnaire to assess sleep disorders in children Results: Out of 443 children studied, the average sleep duration of the study population was 9:06 hours ±42:18 min and, 34.3% of the children slept less than 9 hours per day. The prevalence of sleep disorders was found to be 76.52%. Significant screen time after 8 PM was observed in 65.9% and 62.2 % of children had a total screen time of more than 2 hours. Increased screen time after 8 PM, delayed bedtime and wake-up time in children and also contributed to sleep disorders. Bedtime resistance and daytime sleepiness were more commonly observed in children with increased screen time. Conclusions: Sleep disorders in children are more predominant than sleep deprivation. Increased screen time before bed was found to alter sleep patterns in children and increases bedtime resistance, daytime sleepiness, and sleep disorders.

Understanding how children handle screen time in addition to their academic responsibilities has become increasingly important as technology becomes increasingly embedded into their daily lives. Using a descriptive research design, 87 Grade 6 students from 2 elementary schools in Alfonso Lista, Ifugao, Philippines answered survey questionnaires that asked about their screen time activities, study habits, academic performance, and in balancing their screen time and studies. The current study aims to determine the students’ average screen and study time per day, identify the most common screen activities, assess the perceived effects of screen time on study habits and academic performance, and examine the strategies students use to balance screen and study time, including their perceived effectiveness. Data were gathered through a questionnaire and analyzed using frequency, percentage, mean, and standard deviation. Findings revealed that students spend a few hours both for screen time and study time. The most common screen activity was doing homework-related tasks, followed by gaming and watching videos. Students acknowledged both positive and negative impacts of screen time on their study habits and academic performance—highlighting benefits such as improved access to study resources but also distractions and reduced focus. Various self-regulation strategies were used to manage screen time, with studying before using gadgets perceived as the most effective. The results suggest that while respondents reported that screen time enhances learning when used appropriately, it must be managed effectively to prevent poor academic outcomes. The study recommends implementing time-management training, promoting responsible screen use, and involving parents in guiding children’s digital habits. Further research is encouraged to expand the scope and explore the long-term effects of screen usage on academic performance.