Screen time and sleep among medical students in Germany.
Ontology highlight
ABSTRACT:
SUBMITTER: Liebig L
PROVIDER: S-EPMC10509232 | biostudies-literature | 2023 Sep
REPOSITORIES: biostudies-literature
Publications
Screen time and sleep among medical students in Germany.
Liebig Lukas L Bergmann Antje A Voigt Karen K Balogh Erika E Birkas Béla B Faubl Nora N Kraft Theresa T Schöniger Konrad K Riemenschneider Henna H
Scientific reports 20230919 1
Medical students are a vulnerable group for harmful health behaviours due to academic stress. Increased screen time is associated with adverse health behaviour, particularly delayed bedtime, shorter sleep duration and poorer sleep quality. This possible relationship has not yet been examined among medical students in Europe. Medical students at the Technical University of Dresden were invited to participate in an online questionnaire based cross-sectional study. To analyse correlations between s ...[more]
Similar Datasets
Project description:ObjectiveOn 20 July 2021, after the outbreak of COVID-19 at Nanjing Lukou International Airport, several universities started closed management and online teaching. This had a large impact on students' daily life and study, which may lead to mental health problems. The purpose of this study is to study the effect of screen time on mental health status of university students and the possible mediating effect of sleep status.MethodsThis was a cross-sectional study. A web-based questionnaire survey was employed that included demographic characteristics, sleep status and mental health status (depression, anxiety and loneliness). The Pittsburgh Sleep Quality Index scale was used to assess sleep status, while the Centre for Epidemiologic Studies Depression (CES-D) scale, Generalised Anxiety Disorder-7 (GAD-7) scale and Emotional versus Social Loneliness Scale (ESLS) were used to assess depression, anxiety and loneliness, respectively. Linear and logistic regression models were developed and adjusted for confounding factors, and finally the mediating effects were tested using the Karlson-Holm-Breen method.ResultsFinally, 1070 valid questionnaires were included. Among these, 604 (56.45%) indicated depressive symptoms (CES-D score ≥16) and 902 (84.30%) indicated anxiety symptoms (GAD-7 score ≥10). The mean ESLS score (for loneliness) was 26.51±6.64. The relationship between screen time and depressive symptoms (OR 1.118, 95% CI 1.072 to 1.166) and anxiety symptoms (OR 1.079, 95% CI 1.023 to 1.138) remained significant after adjusting for confounding factors. Meanwhile, sleep status plays an intermediary role in screen time and mental health status (depression and anxiety) and accounts for 13.73% and 19.68% of the total effects, respectively. We did not find a significant association between screen time and loneliness.ConclusionDuring the outbreak of COVID-19, screen time is inevitably prolonged among university students. There is a relationship between mental health and screen time, and sleep status plays a mediating role.
| S-EPMC10729102 | biostudies-literature
Project description:To test the independent and interactive associations of physical activity (PA) and screen time (ST) with self-reported mental health and sleep quality among Chinese college students.Data were collected in October, 2013. The gender, age, residential background, body mass index (BMI), perceived family economy and perceived study burden were obtained from a total of 4747 college students (41.6% males and 58.4% females). The outcomes were self-reported PA status, ST, anxiety, depression, psychopathological symptoms and sleep quality. Analyses were conducted with logistic regression models.Overall, 16.3%, 15.9% and 17.3% of the students had psychological problems, such as anxiety, depression and psychopathological symptoms, respectively. The prevalence of poor sleep quality was 9.8%. High ST was significantly positively associated with anxiety (OR=1.38, 95%CI: 1.15-1.65), depression (OR=1.76, 95%CI: 1.47-2.09), psychopathological symptoms (OR=1.69, 95%CI: 1.43-2.01) and poor sleep quality (OR=1.32, 95%CI: 1.06-1.65). High PA was insignificantly negatively associated with anxiety, depression, psychopathological symptoms and poor sleep. Low PA and high ST were independently and interactively associated with increased risks of mental health problems and poor sleep quality (p<0.05 for all).Interventions are needed to reduce ST and increase PA in the lifestyles of young people. Future research should develop and measure the impacts of interventions and their potential consequences on sleep, health, and well being.
| S-EPMC4364939 | biostudies-other
Project description:IntroductionPhysical inactivity, high screen time, and short sleep are targets of public health initiatives for children. However, few data exist on how many U.S. children meet guidelines for these behaviors-data vital to inform which needs greater targeting. This study describes national prevalence estimates of U.S. children who meet physical activity, screen time, and sleep guidelines alone or in combination across each childhood year.MethodsThis analysis (completed in 2019) used cross-sectional data from the 2016-2017 National Survey of Children's Health, a nationally representative sample of U.S. children. Child physical activity (days per week with ≥60 minutes), recreational screen time (hours per day of TV viewing and electronic device use), and sleep duration (hours per day) were assessed through parental report. Guidelines recommend ≥60 minutes per day of physical activity, ≤2 hours per day of screen time, and 9-12 hours per day of sleep for individuals aged 6-12 years (8-10 hours for those aged 13-17 years).ResultsOnly 8.8% (95% CI=8.2%, 9.5%) of U.S. children meet all the 3 guidelines combined. Majority of children/adolescents attain the sleep guideline (86.0%, 95% CI=85.2%, 86.7%), but a lower proportion meet physical activity (23.0%, 95% CI=22.1%, 23.9%) or screen time (32.9%, 95% CI=31.9%, 33.8%) guidelines. A substantial age effect was identified, with prevalence of meeting each distinct guideline and all the 3 declining with age (p<0.001).ConclusionsFew U.S. children meet all the 3 movement guidelines, with prevalence rates of children meeting guidelines declining with age. Although many meet sleep guidelines, few meet physical activity or screen time guidelines. Initiatives targeting physical activity and screen time, especially for adolescents, should be pursued.
| S-EPMC7574791 | biostudies-literature
Project description:Objective To assess the association between abdominal obesity, food intake, sleep deprivation, and screen time in adolescents. Methods This cross-sectional study was conducted with 432 adolescents aged 14–19 years, from public and private schools. Anthropometric and body composition measures included body weight, waist circumference, body mass index for age, waist-to-hip ratio, waist-to-height ratio, and body fat percentage. Abdominal obesity was defined by age and sex specific cut-off points for waist circumference. Food intake, screen time, sexual maturation, and sleep duration were evaluated by self-administered questionnaires. Results The prevalence of excess body weight and abdominal obesity was 16.7% and 27.5%, respectively. Students in the adult phase (post-puberty), with inadequate waist-to-height ratio, high body fat percentage, and screen time ≥ 3 h/day were, respectively, 2.5 (95% CI 1.40–4.46), 7.44 (95% CI 1.08–51.46), 2.79 (95% CI 1.04–7.50), and 1.43 (95% CI 1.24–3.89) more likely to have abdominal obesity. Low intake of unprocessed or minimally processed foods was associated with inadequate sleep duration, while high intake of ultra-processed foods was associated with high screen time. Conclusions Abdominal obesity was associated with the adult phase, short sleep duration and high screen time. The degree of food processing was associated with screen time and sleep duration. Assessing the risk factors of abdominal obesity may be a useful strategy for preventing cardiovascular disease in adolescents.
| S-EPMC9875269 | biostudies-literature
Project description:Approximately 4 μg of DNA was isolated from blood of each of 16 subjects using the Qiagen DNEasy Blood and Tissue Kit. Of the 16 samples, 8 were from group 1 (CESD-H/TST-H; 5 female, 3 male) and 8 were from group 2 (CESD-H/TST-L; 5 female, 3 male). All DNA samples were confirmed to be of high purity (A260/280: 1.7-2.0). Pooled samples were prepared for each group by combining approximately 75 ng of DNA from each of the eight subjects. These two samples were submitted to the Yale Genomics Core for epigenome-wide methylation profiling using the Illumina Infinium HumanMethylation450 BeadChip, which measures the level of methylation β (a value ranging from 0 to 1, where 0 represents a completely unmethylated site and 1 a completely methylated site) at each of the 485,577 CpG sites on the array. Illumina’s GenomeStudio software was used to calculate the degree of differential methylation by group for each CpG site on the array, and FDR-adjusted p-values (Q-values) were calculated for each site in order to adjust for multiple comparisons. CESD=depression score; TST=sleep score
2016-08-01 | GSE80559 | GEO
Project description:Objective/backgroundConsumption of added sugar and excessive screen-time is increasing worldwide and is associated with sleeping and behavior disorders, which are related with possible Sleep Bruxism (SB) in children. Therefore, the objective of this investigation was to examine the relationship between screen-time and sugar-consumption and possible SB in children.Patients/methodsA cross-sectional study, including parents of 460 4- to 8-year-old children, was performed. Frequency of possible SB was assessed with the Children's Sleep Habits Questionnaire; sugar consumption with the Health Behaviour in School-Aged Children Food-Frequency Questionnaire. Comprehensive measures of screen-time (including cell phones, computers, electronic devices, electronic games, and TV) were taken. The time was recorded in hour/day. All data were analyzed with STATA© data analysis and statistical software version 13.0 (Copyright 1996-2016; Stata-Corp LP, College Station, TX, USA). Spearman correlation test and ordinal-multiple-variable regression analyses were used.ResultsData of 440 subjects Mean age 6.2 years (S.D. 1.8) were analyzed. Prevalence of possible SB was 35% and screen-time was available for 92.9% of the children. Mean screen-time was 2.1 h/day. Parents reported 73% of the children (n = 319) to consume added sugar once a day every day and 20% more than once every day. Correlations of possible SB were statistically significant with screen-time (Rho = 0.8; p = 0.002) and sugar-consumption (Rho = 0.7; p = 0.03). Associations were found between possible SB and increase-to-increase screen-time and sugar-consumption (OR > 2).ConclusionThe results of this study demonstrated that as screen-time and sugar consumption increased, the frequency of bruxism in children increased.
| S-EPMC8122107 | biostudies-literature
Project description:BackgroundSmartphones are increasingly integrated into everyday life, but frequency of use has not yet been objectively measured and compared to demographics, health information, and in particular, sleep quality.AimsThe aim of this study was to characterize smartphone use by measuring screen-time directly, determine factors that are associated with increased screen-time, and to test the hypothesis that increased screen-time is associated with poor sleep.MethodsWe performed a cross-sectional analysis in a subset of 653 participants enrolled in the Health eHeart Study, an internet-based longitudinal cohort study open to any interested adult (≥ 18 years). Smartphone screen-time (the number of minutes in each hour the screen was on) was measured continuously via smartphone application. For each participant, total and average screen-time were computed over 30-day windows. Average screen-time specifically during self-reported bedtime hours and sleeping period was also computed. Demographics, medical information, and sleep habits (Pittsburgh Sleep Quality Index-PSQI) were obtained by survey. Linear regression was used to obtain effect estimates.ResultsTotal screen-time over 30 days was a median 38.4 hours (IQR 21.4 to 61.3) and average screen-time over 30 days was a median 3.7 minutes per hour (IQR 2.2 to 5.5). Younger age, self-reported race/ethnicity of Black and "Other" were associated with longer average screen-time after adjustment for potential confounders. Longer average screen-time was associated with shorter sleep duration and worse sleep-efficiency. Longer average screen-times during bedtime and the sleeping period were associated with poor sleep quality, decreased sleep efficiency, and longer sleep onset latency.ConclusionsThese findings on actual smartphone screen-time build upon prior work based on self-report and confirm that adults spend a substantial amount of time using their smartphones. Screen-time differs across age and race, but is similar across socio-economic strata suggesting that cultural factors may drive smartphone use. Screen-time is associated with poor sleep. These findings cannot support conclusions on causation. Effect-cause remains a possibility: poor sleep may lead to increased screen-time. However, exposure to smartphone screens, particularly around bedtime, may negatively impact sleep.
| S-EPMC5102460 | biostudies-literature
Project description:IntroductionStudies consistently link excessive smartphone use to poor sleep quality, depression, anxiety, and stress. This study specifically aimed to investigate these associations among medical students in Belgrade and Nis (Central Serbia).Materials and methodsThe cross-sectional study included a sample of 761 students, who were selected from both the Faculties of Medicine at the University of Belgrade and the University of Nis. Questionnaires, including the International Physical Activity Questionnaire - Short Form (IPAQ-SF), Smartphone Addiction Scale - Short Version (SAS-SV), the Pittsburgh Sleep Quality Index (PSQI), and the Depression, Anxiety, and Stress Scale - 21 items (DASS-21), were completed by the participants. Statistical analysis techniques, such as the Chi-square test, student's t-test, and logistic regression, were employed to examine the relationship between smartphone addiction, physical activity, sleep quality, depression, anxiety, and stress.ResultsThe findings indicated a prevalence of smartphone addiction among medical students at 21.7%, with rates of 22.9% among males and 21.1% among females. Females exhibited significantly higher scores on the SAS-SV scale compared to males (p = 0.032). Univariate logistic regression analysis revealed significant associations between smartphone addiction and spending over 4 h daily on smartphones (OR = 2.39; p < 0.001), poor sleep quality (OR = 1.65; p = 0,005), as well as elevated levels of stress (OR = 1.75; p = 0.003), anxiety (OR = 2.04; p < 0.001), and depression (OR = 2.29; p < 0.001). Multivariate regression analysis identified spending more than 4 h daily on smartphones (OR = 2.39; p < 0.001) and increased levels of depression (OR = 2.51; p < 0.001) as independent significant factors associated with smartphone addiction.ConclusionThis study sheds light on the prevalence of smartphone addiction among medical students, with spending excessive time on smartphones and higher levels of depression standing out as significant factors. Future research should delve into the underlying mechanisms and causal relationships between smartphone addiction and these psychosocial factors. Understanding these connections will aid in developing effective interventions and strategies to tackle this growing public health concern.
| S-EPMC10512032 | biostudies-literature
Project description:ObjectivesWe aimed to assess sleep quality of Tunisian medical students during home confinement due to the COVID-19 pandemic, and to analyze the relationship between sleep quality and sociodemographic, clinical, confinement-related and psychological variables.MethodsA correlational cross-sectional study was conducted from April 11th to May 3rd 2020. Medical students who have been in home confinement and who accepted to participate in an online survey were targeted. Sociodemographic data, clinical variables, and data related to home confinement were collected. Participants also completed Pittsburgh Sleep Quality Index, Depression, Anxiety and Stress Scale and Beck Hopelessness Scale.ResultsResults showed a high prevalence of poor sleepers among medical students (72.5%) with poor subjective sleep quality, increased sleep latency, sleep disturbances and daytime dysfunction. Multiple regression analysis revealed that family history of suicide attempts, tobacco use, perception of home confinement and reduced physical activity during home confinement significantly contributed to poor sleep quality. Among the psychological variables, anxiety and hopelessness significantly contributed to poor sleep quality in medical students during home confinement.ConclusionsResults revealed a high prevalence of poor sleep quality in medical students who have been in home confinement due to the COVID-19 pandemic. Except family history of suicide attempts, factors that significantly contributed to poor sleep quality were modifiable factors. Sleep quality and sleep parameters need to be assessed in this particular population and adequate measures aiming to promote quality of sleep need to be enhanced, given the crucial regenerative, homeostatic and psychological roles of sleep.
| S-EPMC8828364 | biostudies-literature
Project description:BackgroundUnderstanding the developmental trajectories of outdoor time, screen time and sleep is necessary to inform early interventions that promote healthy behaviours. This study aimed to describe concurrent trajectories of outdoor time, screen time and sleep across the early childhood period and their maternal predictors.MethodsData across five time points at child age 4, 9, 19, 42 and 60 months from the INFANT intervention were analysed. Mothers reported their child's usual outdoor time, screen time and sleep duration, in addition to a range of maternal beliefs, attitudes, expectations and behaviours. Group-based multi-trajectory modelling was used to model concurrent trajectories of children's behaviours. Multinomial logistic regression models determined the associations of maternal predictors with trajectory groups, adjusting for child sex and baseline age, intervention allocation, and clustering by recruitment.ResultsOf the 542 children recruited, 528 had data for outdoor time, screen time and sleep at one or more time points and were included in trajectory analyses Four trajectories were identified: 'unstable sleep, increasing outdoor time, low screen' (~ 22% of sample), 'high outdoor time, low screen, high sleep' (~ 24%), 'high sleep, increasing outdoor time, low screen' (~ 45%), 'high screen, increasing outdoor time, high sleep' (~ 10%). The 'high sleep, increasing outdoor time, low screen' group, comprising the largest percentage of the sample, demonstrated the healthiest behaviours. Predictors of group membership included: views of physically active children, screen time knowledge, screen time use, self-efficacy, physical activity optimism, future expectations for children's physical activity and screen time, perceptions of floor play safety, and maternal physical activity, screen time, and sleep quality.ConclusionsFour distinct trajectories of outdoor time, screen time and sleep were identified, with the most common (and healthiest) characterized by high levels of sleep. Maternal beliefs, attitudes, expectations and behaviours are important in the development of movement behaviour trajectories across early childhood. Future interventions and public policy may benefit from targeting these factors to support healthy movement behaviours from a young age.
| S-EPMC9798690 | biostudies-literature