Screen time among Chinese primary and middle school students from 2016 to 2017

To analyze and describe the status and characteristics of using electronic screens of primary and middle school students in China from 2016 to 2017. From 2016 to 2017, 275 monitoring points were selected from 31 provinces in China, and 280 primary and middle school students were selected from each monitoring point to complete the survey. Using the suggestion from "Healthy China Initiative(2019-2030)"of which the screen time of primary and middle school students should be less than one hour per day as the standard. A total of 74 314 primary and secondary school students(except grade 9 and grade 12) were included in this study. Among them, there were 37 147 boys(50.0%) and 37 167 girls(50.0%); 44 612 pupils(60.0%), 14 858 junior school students(20.0%), and 14 844 senior high school students(20.0%); 38 995(52.5%) rural students and 35 319(47.5%) urban students; 53 287 boarding students(71.7%) and 20 537 day students(27.6%). From 2016 to 2017, the average daily screen time of Chinese primary school students was 1.45 hours, M(P25, P75) was 1.14(0.57, 1.93) h. That of junior high school students was 1.92 hours, M(P25, P75) was 1.43(0.71, 2.48) h. That of senior high school students was 2.37 hours, M(P25, P75) was 1.71(0.90, 3.02) h. The average daily screen time qualified rates of primary school, junior high and senior high school students were 46.1%, 37.1% and 27.7%, respectively. From 2016 to 2017, the most used electronic screen products of primary school students in China were TV/videos(62%), followed by mobile phones(21%). Junior high school students spent 38% and 37% of the total time watching TV/videos and playing mobile phones, respectively. High school students spend the longest time using mobile phones(49%) of the total time, followed by watching TV/videos(26%). With the increasing of grade, screen time became longer, and screen time qualified rate dropped. Moreover, the most used electronic screens were mobile phones and TV/videos.

Objective: To investigate the relationship between screen time and content, and the mental health status of adolescents. The findings will inform the formulation of targeted intervention policies to enhance adolescent mental health. Methods: Between September and November 2023, 5 197 students from 64 junior high, senior high, and vocational schools across 13 districts in Wuhan were recruited, using the stratified whole-cluster random sampling to investigate their screen behavior and mental health status. Mental health status was measured using the Mental Health Inventory for Chinese Middle School Students (MMHI-60). A generalized additive model was used to explore the nonlinear association between screen time and mental health status. Additionally, a mixed-effects model was utilized to explore the dose-response associations between average daily total screen time, screen time for different content types, and adolescents' mental health status and the impact of the proportion of different screen contents on mental health outcomes. Results: The age of the participants was (14.40±1.48) years, with 56.07% being boys. The MMHI-60 score averaged 1.73±0.70. The M(Q1,Q3) for daily total screen time was 50.00 (0.00,128.57) minutes. The M(Q1,Q3) for screen time dedicated to gaming, studying, socializing, and watching videos were 0.00 (0.00, 20.00), 8.57 (1.64, 44.50), 4.28 (0.00, 30.00), and 0.00 (0.00, 25.71) minutes, respectively. A non-linear association was observed between average daily screen time and adolescent mental health problem score, 0-1 hour of daily screen time was beneficial for adolescent mental, compared to no screen time. However, screen time exceeding 1 hour was detrimental, with the negative impact increasing alongside screen time duration. When total daily screen time was held constant, the proportion of time spent on gaming (β=0.14, 95%CI: 0.05-0.23,P=0.003) and video (β=0.21, 95%CI: 0.09-0.28, P<0.001) was positively correlated with mental health problems, whereas the proportion of time spent on studying was negatively correlated with mental health problems (β=-0.17, 95%CI: -0.24 - -0.11, P<0.001). Conclusions: Moderate screen time is advantageous for adolescent mental health. However, it is crucial to minimize the proportion of screen time dedicated to video and gaming activities to mitigate potential adverse effects.

Objective: To study the impact of screen time on school performance in children of 7-10 years of age. Study Design: Cross-sectional Comparative survey. Place &amp; Duration of Study: Two schools, one Government School and one private sector school, Islamabad Pakistan from Nov 2024 to Jan 2025. Methodology: Total 308 school going children of 7-10 years of age meeting the inclusion criteria rom two schools were included in the study. Data was collected from their parents and teachers on the parents-day meeting as per designed proforma based on Child Occupational Self-Assessment (COSA). Fine motor and visuospatial skills were also assessed and compared with daily average screen time. Results: A total of 310 children were included having median age of 8.00(2.00) years with 178(57.4%) boys and 131(42.3%) girls. The median daily screen time reported by parents was 4.00 (2.00) hours. The class grades in academics, attitude and class participation of children were found to vary with average daily screen time (p&lt;0.0001). The sleep hours were also associated with the attitude in the class (p=-0.644, p&lt;0.0001). Solving time for peg board pattern was 118.50(48.00) seconds and setting the calendar was 116(53.25) seconds had significant relationship with average daily screen time (p=0.961, 0.945, p&lt;0.0001, &lt;0.0001) respectively. Conclusion: Excessive screen time found to be associated with lack of interest, delayed fine motor and visuospatial learning, as well as poorer academic performance.

PURPOSE: Obesity is becoming more and more popular among primary and secondary school students in China. This study attempts to understand the current situation of body fat distribution of primary and secondary school students in China, and to study the body fat of different populations. METHODS: The subjects were 7-17 years old healthy students recruited in Beijing in 2017. According to the grade, the students of Grade 1-3 in primary school are divided into the lower grade group, the students of grade 4-6 are divided into the higher grade group, the students of Grade 1-3 in junior middle school are divided into the junior middle school group, and the students of grade 1-2 in senior high school are divided into the senior high school group. After screening, 219 samples were qualified (107 boys and 112 girls). Body composition were measured by dual energy X-ray absorptiometry (xr-800 Norland, USA) in Tsinghua University. T test by SPSS22.0. RESULTS: The abdominal fat mass of primary school boys was significantly higher than that of girls, and the abdominal / pelvic fat mass ratio(A/P FMR) of primary school boys was significantly higher than that of girls. The characteristics of junior middle school students are on the contrary, except for the A/P FMR of high school students, there are significant differences in other fat distribution indicators. The fat mass of primary school boys was higher than that of girls, but the abdominal fat weight did not change with age after middle school, but the abdominal fat weight of girls increased slowly. The change of limb fat weight is the main factor of whole body fat mass change. Table 1. Distribution of body fat in primary and middle school students.CONCLUSIONS: The centripetal distribution of fat in primary school boys is more obvious. The change of limbs fat may be more obvious in Chinese primary and secondary school students.

The lifestyles change of children and adolescents during the COVID-19 pandemic due to antipandemic measures can affect their sleep health. Existing studies have used convenient samples and focused on the initial months of the pandemic, leaving a knowledge gap on changes in young people's sleep patterns under the "new normal" under COVID-19. As part of a territory-wide epidemiological study in Hong Kong, this cross-sectional study recruited primary and secondary school students by stratified random sampling. Sleep parameters were collected using the structured diagnostic interview for sleep patterns and disorders. We investigated the pandemic's effects on sleep parameters by comparing data of participants recruited pre-COVID and those recruited during COVID using multivariate regression, adjusting for age, sex, household income, seasonality, and presence of mental disorders, and the moderators and mediators of the effects. Between September 1, 2019 and June 2, 2021, 791 primary and 442 secondary school students were recruited and analyzed. Primary school and secondary school participants assessed before COVID had a longer sleep latency on school days (95% confidence interval [CI] = 1.0-5.2 minutes, adjusted P-value = .010; and 95% CI= 3.9-13.0 minutes, adjusted P-value = .004, respectively) and nonschool days (95% CI = 1.7-7.2 minutes, adjusted P-value = .005; 95% CI = 3.4-13.7 minutes, adjusted P-value = .014, respectively). Low household income was a moderator for later bedtime (adjusted P-value = .032) and later sleep onset (adjusted P-value = .043) during nonschool days among secondary school students. Changes associated with COVID have a widespread and enduring effect on the sleep health of school-aged students in Hong Kong. Household income plays a role in adolescent sleep health resilience, and the impact of antiepidemic measures on the health gaps of the youth should be considered. Chau SWH, Hussain S, Chan SSM, etal. A comparison of sleep-wake patterns among school-age children and adolescents in Hong Kong before and during the COVID-19 pandemic. J Clin Sleep Med. 2023;19(4):749-757.

To investigate the characteristics of screen time and its risk factors in Chinese primary and middle school students. During April 2012 and June 2012, according to the geographical distribution, the stratified random cluster sampling method was used to select 4 provinces from eastern, central and western China, respectively. The convenience sampling method was used to select 2 primary and middle schools from urban, 2 primary and middle schools from rural in each province. In each school, all grades were included, and 2 classes were selected in each grade. A total of 51 866 students or parents were selected as study participants, and 43 771 questionnaires were valid. Information on demographics, academic performance, screen time (TV, computer and cellphone) at weekdays and weekends and the prevalence of the high screen time were compared, multivariate logistic regression was used to analyze the association between screen time >2 h/d and potential influential factors. The percentage of students with screen time >2 h/d at weekdays and weekends were 16.2% (7 082/43 771) and 41.5% (18 141/43 771) (χ(2)=6 280.14, P<0.001), respectively. The distribution of P50 (P25-P75) for screen time at weekdays and weekends were 0.9(0.4-1.6) and 1.8(1.0-3.0) (Z=-131.26, P<0.001), respectively. The results of multinomial logistic regression analysis showed that, at weekdays, subjects characterized as primary school students, boys, urban area, living in western area and sufficient vigorous physical activity ≤2 d/w had higher risk for screen time >2 h/d than those characterized as elementary school students, girls, rural area, living in eastern area and sufficient vigorous physical activity >3 d/w, odds ratio were 2.01, 1.54, 1.21, 1.09, and 1.07, respectively (P<0.05 for all); subjects characterized as a normal or worse self rating academic performance had higher risk for screen time >2 h/d than those characterized as a good self rating academic performance, odds ratioes were 1.24 and 1.73, respectively (P<0.05 for all); subjects characterized as paternal education level as elementary school, middle school, high school or secondary school had higher risk for screen time >2 h/d than those characterized as paternal education level as college school or high, odds ratioes were 1.41, 1.47 and 1.52, respectively (P<0.05 for all); subjects characterized as maternal education level as elementary school, middle school and high school or secondary school had higher risk for screen time >2 h/d than those characterized as maternal education level as college, odds ratioes were 1.40, 1.52 and 1.47, respectively (P<0.05 for all). At weekends, subjects characterized as primary school students, boys, urban area and sufficient vigorous physical activity ≤2 d/w had higher risk for screen time >2 h/d than those characterized as elementary school students, girls, rural area and sufficient vigorous physical activity >3 d/w, odds ratioes were 2.11, 1.51, 1.20 and 1.05, respectively (P<0.05 for all). At weekends, subjects characterized as a normal or worse self rating academic performance had higher risk for screen time >2 h/d than those characterized as a good self rating academic performance, odds ratioes were 1.09 and 1.26, respectively (P<0.05 for all); subjects characterized as paternal education level as elementary school, middle school, high school or secondary school had higher risk for screen time >2 h/d than those characterized as paternal education level as college school or high, odds ratioes were 1.29, 1.30 and 1.19, respectively (P<0.05 for all); subjects characterized as maternal education level as elementary school, middle school had higher risk for screen time >2 h/d than those characterized as maternal education level as college school or high, odds ratioes were 1.19 and 1.16 and, respectively (P<0.05 for all). The prevalence of screen time >2 h/d is high; screen time at weekdays is longer than weekends, and there are significant differences among different sexes, urban or rural areas, living areas, self rating academic performance, parents education levels and physical activity groups.

The prevalence of overweight and obesity among children and adolescents continues to rise, becoming one of the most serious global public health issues of the 21st century. Given the differing growth and development environments between urban and rural children, associated risk factors also vary. This study aims to explore the distribution characteristics and influencing factors of overweight and obesity among urban and rural primary and secondary school students in Hunan Province, providing scientific evidence for targeted interventions. A stratified, randomized cluster sampling method was used to select participants. A total of 197 084 students from primary and secondary schools across 14 prefectures in Hunan Province underwent physical examinations and questionnaire surveys. Population and spatial distribution characteristics of overweight and obesity were analyzed. Spatial distribution maps and spatial autocorrelation analyses were conducted using ArcGIS. Multivariate Logistic regression was used to identify influencing factors for overweight and obesity. The overall overweight and obesity rates among students in Hunan Province were 14.7% and 10.9%, respectively. Both rates were higher in urban areas than in rural counties (16.0% vs 13.9% for overweight; 12.1% vs 10.2% for obesity). Among both urban and rural students, boys had higher rates of overweight and obesity than girls. Higher-grade students had a higher overweight rate but a lower obesity rate than lower-grade students. In urban areas, the overweight and obesity rates of Han Chinese primary and secondary school students are lower than those of ethnic minority students (both P<0.05). In rural areas, the obesity rate of Han primary and secondary school students is lower than that of ethnic students (P<0.05). Across cities and prefectures, urban overweight and obesity rates ranged from 14.7% to 18.7% and 8.4% to 20.6% respectively, while rural rates ranged from 10.9% to 17.2% and 6.6% to 13.7% respectively. Spatial autocorrelation analysis revealed high-value clusters of overweight/obesity in urban areas of Changde and Zhangjiajie, and in rural areas of Loudi, Huaihua, and Shaoyang. Multivariate Logistic regression showed that gender, school stage, ethnicity, frequency of fresh vegetable intake, and sleep duration were associated with overweight and/or obesity in both urban and rural students. In urban students, frequency of fried food and fresh fruit intake, breakfast habits, physical activity on weekdays and holidays, and screen time on computers were also significant. In rural students, TV viewing time and sedentary duration were additional relevant factors. The situation of overweight and obesity among primary and secondary school students in Hunan Province remains concerning. Greater attention should be paid to regions with high-value clusters of overweight/obesity, and targeted interventions should be developed based on urban-rural differences in influencing factors.

Background: Migraine is a chronic headache disorder involving neurovascular hyperexcitability and trigeminovascular sensitization, leading to functional impairment. With digital technologies now pervasive, excessive internet and social media use may contribute to migraine burden. This study examined the relationship between internet and social media addiction, screen exposure, and migraine-related disability in adults. Methods: Eighty-two adults aged 18–65 years with a diagnosis of migraine according to the International Classification of Headache Disorders, 3rd edition (ICHD-3) and without significant neurological or severe psychiatric comorbidities were included. Sociodemographic data, the Visual Analog Scale (VAS), the Migraine Disability Assessment (MIDAS), the Young Internet Addiction Scale (YIAS), and the Social Media Addiction Scale (SMAS) were administered. Average daily smartphone screen time over the past seven days was recorded. Spearman correlation coefficients and multivariable linear regression models were used for the analyses. Results: Spearman correlation analysis revealed significant positive associations between MIDAS and both YIAS (ρ = 0.458) and SMAS (ρ = 0.541), with SMAS showing the stronger relationship. Average daily screen time was also correlated with MIDAS (ρ = 0.345). In multivariable models, YIAS and screen time remained independently associated with MIDAS when included together. However, when SMAS was entered alongside screen time, only SMAS remained significant (β = 0.33; 95% CI: 0.18–0.47). Likewise, in the model including both SMAS and YIAS, SMAS remained an independent predictor (β = 0.43; 95% CI: 0.20–0.66), whereas YIAS lost significance (β = –0.21; 95% CI: –0.79 to 0.37). Conclusion: The findings suggest that migraine burden may be more closely related to social interaction–based digital exposure than to overall internet use. Social media–related behaviors could be a potential target for intervention, although prospective studies are needed to confirm this.

BackgroundThe advent of miniature, easy-to-use and accessible multimedia products is leading to screen exposure that begins in early childhood. Overexposure in preschool may lead to adverse effects. The main objective of this study was to determine the average daily time (ADT) spent by children under 6 years of age, followed in general practice, in front of television or interactive screens.MethodsA cross-sectional survey was conducted in the Auvergne-Rhône-Alpes region among randomly selected General Practitioners (GPs). The average daily screen time (ADST), regardless of the type of device (TVs, computers, tablets, smartphones, video game consoles), of the included children aged 0 to 2 years and 2 to 5 years was calculated from a self-questionnaire completed by the parents. A multivariate Poisson regression model was performed to analyse daily screen time, adjusted by factors selected on their clinical relevance and statistical significance.ResultsThe 26 participating GPs included 486 parents. They reported an ADST of 26 (± 44) minutes on weekdays and 30 (± 46) minutes on weekends for children under 2 years of age. For children over 2 years of age, the ADST was 66 (± 82) minutes on weekdays and 103 (±91) minutes on weekends. There was an association between the children’s average screen time and certain sociodemographic and environmental factors. Children whose parents had higher levels of education, those living in a family without TV screens or those who were well informed about the possible adverse health consequences of overuse of screens had lower average screen time. On the other hand, children of parents who spent more than 2 hours a day in front of screens, were more exposed.ConclusionsIn our survey, the ADST of children under 6 years of age followed in general practice was higher than the current recommendations. GPs can warn parents of preschool children of the effects of overexposure to screens, particularly parents of at-risk children.

Introduction: Anemia and Ascaris infection are important indicators to reflect the health status of students. In this study, by investigating the current situation of low hemoglobin and positive rate of Ascaris eggs of primary and secondary school students in Hohhot, the health status of local primary and secondary school students is actually reflected. Objectives: To understand the prevalence of Low Hemoglobin and Ascaris infection among primary and secondary school students in Hohhot in 2015 and to give some suggestions on the health status of primary and secondary school students in Hohhot. Study Design: This project uses a cross-sectional study to investigate the distribution of disease and health status of primary and middle school students in Hohhot at a specific time, and to provide a clue to the cause of the hypothesis test. Methods: A stratified cluster random sampling method was used to select 4 districts, 4 counties and 1 flag in Hohhot, a total of 36 primary and secondary schools for sample survey. Cyanine HiCN and smear method is to detect hemoglobin and ascaris eggs positive. Results: In 2015, the positive rate of low hemoglobin in primary and secondary school students was 21.45% in urban and rural areas, 33.17% in urban and rural areas, 43.69% in rural areas, 13.59% in ascaris eggs, 10.69% in urban and rural areas, 7.81% in rural areas. There are geographical differences and gender differences between cities, urban-rural junctions and rural areas (p < 0.05). Conclusion: The prevalence of low hemoglobin in primary and secondary school students in Hohhot is high in rural areas. The detection rate of ascaris egg positive rate in the city is high. Monitoring, publicity and education should continue to be strengthened.

Objective To investigate the body height distribution profile and prevalence of short stature of primary and secondary school students aged from 7 to 18 years in Hefei. Methods Twelve schools in five districts and counties in Hefei were selected.3 593 primary and secondary school students aged from 7 to 18 years were recruited.Body heights were measured and were evaluated using a nine cities' growth standard.Short stature was defined as the body height was two standard deviation below the mean body height in each sex matched age group.The prevalence of short stature was calculated and standardized using the nine cities' population data. Results Body heights were higher in boys than in girls.The body heights of boys nearly stopped increasing after 15 years old, while the heights in girls stopped increasing after 14 years old.The body heights of children in Hefei in 2014 were higher than in 2010.The prevalence of short stature of primary and secondary school students in Hefei among all age groups was 1.12% to 4.17%, the average prevalence was 2.26%.The prevalence of short stature in rural area was 3.43%, which in urban area was 1.76%, the rate was significantly lower in urban area than that in rural area(χ2=9.793, P=0.002). The prevalence of short stature in boys was 2.60%, which in girls was 2.64%, no obvious difference was found in the prevalence of short stature between boys and girls(χ2=0.006, P=0.937). The prevalence of short stature in boys and girls in urban area were 1.75% and 1.78% respectively, which in rural area were 3.46% and 3.34%, no matter in urban area or in rural area, the prevalence of short statue was not obviously different.The prevalence of short stature in primary and secondary school students also had no obvious difference. Conclusion Body heights were higher in boys than in girls.The body heights of children in Hefei in 2014 were higher than in 2010.The average prevalence of short stature of the primary and secondary school students in Hefei was 2.62%, the rate was significantly higher in rural area than that in urban area.There was no obvious difference in the prevalence of short stature between boys and girls.Neither was the primary and secondary school students. Key words: Body height; Short stature; Primary and secondary students; Hefei; Cross-sectional studies

Aims:We have evaluated screen time usage among preschool-aged (≤6 years) children in rural Western India. In addition, we have evaluated various lifestyle factors and their impact on the screen time of these children.Materials and Methods:English-medium schools in the locality were chosen based on convenience. A self-report survey requesting family information and screen usage information was distributed to the parents. Daily screen time was categorized as a three-category variable. Ordered logistic regression with multivariable regression was performed to examine the association of risk factors with screen time.Results:Average screen time among the 379 (208 males, 171 female) children amounted to 2.7 hours (SD: 1.7), with average daily television screen time of 1.6 hours (SD: 1.1). Most children (87.2%) started screen use by the age of 3. Only 65 (17.2%) participants met AAP recommendation. Households with three devices and smartphone usage by mothers increased the odds of screen time by 60% and two-folds, respectively. Compared to weekdays, children had increased screen time exposure (3.5 vs 2.7 hours, P < 0.001), outdoor activity time (2.3 vs 1.6, P < 0.001), and reading hours (1.2 vs 1.1, P = 0.03) on weekends. No association was observed between screen time and mother's occupation.Conclusions:More than 80% of children exceeded the advised screen time with television and smartphone being the major contributors. This issue has to be dealt with at both individual and societal levels. Increased awareness about the high prevalence of inappropriate use of screen time use within the Indian context is needed to inspire attention and interventions for this emerging public health problem in India.

Objective To understand the prevalence and trend of the poor eyesight in primary and middle school students in Beijing, and to provide theoretical basis for eyesight protection and myopia prevention and control. Methods According to “Technical Standard for Student Health Inspection” (GB/T 26343–2010), students were examined with a standard logarithmic visual acuity E chart for naked eye vision. Results The prevalence of poor eyesight among primary and middle school students in 2010-2016 was 63.0%, 62.1%, 62.9%, 60.7%, 59.2% and 58.6% respectively, decreased by 7.0% in 6 years, primary school students dropped by 9.7%, and junior school students, senior high school students and vocational high school students increased by 5.5%, 3.3% and 14.1% respectively. Urban and suburban areas (61.2%, 54.3%) decreased by 9.6% and 2.9% respectively. Regardless of boys and girls, urban and suburb, between 2010 and 2016, the overall composition ratio of students in each school segment was expressed as primary school > junior school > senior high school students > vocational high school, and vocational high school students accounted for the minimum; the overall composition ratio of primary school has become more and more large. Conclusion Eyesight protection and myopia prevention among primary and middle school students in Beijing is still challenging. All departments should take active and effective measures to control the newly onset and progression of low vision and improve eyesight. 【摘要】 目的 了解北京市中小学生视力不良检出率及变化趋势, 为学生视力保护及近视防控提供参考依据。 方法 按照《学生健康检査技术规范》 (GB/T 26343—2010), 采用标准对数视力表对北京市全体中小学生进行裸眼远视力检査。 结果 2010—2016 年北京市中小学生视力不良检出率分别为 63.0%, 62.1%, 62.9%, 60.7%, 59.2% 和 58.6%, 6 年间下降了 7.0%。2015—2016 年小学生、初中生、普通髙中生、职业髙中生视力不良检出率分别为 45.5%, 78.4%, 89.4%和74.5%, 较 2010—2011 年小学生下降了 9.7%, 初中生、普通髙中生和职业髙中生分别增长了 5.5%, 3.3% 和 14.1%; 2015—2016 年, 城 区、郊区学生视力不良检出率分别为 61.2% 和 54.3%, 较 2010—2011 年分别下降了 9.6% 和 2.9%。不论男生、女生, 城区、 郊区, 2010—2016 年, 每年各学段学生总体构成比均表现为小学>初中>普通髙中>职业髙中, 职业髙中学生占比最小; 随着 年份的增加, 小学的构成比增大。 结论 北京市中小学生视力不良防控工作任务艰巨。各部门应采取积极有效的措施, 控 制视力不良新发和加重, 提髙中小学生视力健康水平。

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.

Since the enactment of Dakar Program in 2000, all of the countries have taken a series of measures to achieve the aim of universal education. China, the country with the largest population in the world, also makes every effort to popularize the universal education and to achieve the equity of education. After contact work for many years, China’s education has got a quite great development, especially in the aspect of popularizing the universal education, China have taken great achievements, just like the quite huge and great developments in the economic field. According to the Progress of China in Implementing the Millennium Development Goals (2000–2015) which was issued jointly by the government of China and UN agencies in China, China has achieved the goal of universal primary education by 2015 ahead of schedule: when the Chinese Government has progressed towards free compulsory education in a phased and planned way, the Chinese also has achieve the targets of universal 9-year compulsory education and basic elimination of illiteracy among the adolescents, and illiteracy rate among the adolescents has been below 1.0 %, and the net enrollment rate of primary-school-age children has increased to 99.8 %. In the aspect of eliminating gender disparity, the difference in net enrollment rate between boys and girls has been eliminated, and the gap between boys and girls in the years of education they received was narrowed from 1.3 years in 2000 to 0.8 years in 2014. In 2014, there were 32.458 million girl students in secondary schools, accounting for 47.84 % of the total number of students there, and 43.7196 million girl students in primary schools, accounting for 46.26 % of the total number of students there. The ratio of boy to girl students in primary and secondary schools is basically consistent with the ratio of school-age children between boys and girls. These glorious data remarked that Chinese education has attained the aim of “equity” and “popularization” in some extrinsic data and indexes, but these glorious outside data cannot hide the deep conflicts in the Chinese educational equity. In addition, with a decade of development, these extrinsic conflicts have become more internal. Due to their concealment, these internal conflicts of equity will be tough to solve. These internal conflicts can be summarized in three basic facts: quality, freedom, and equity. The relationship among them also becomes critical influences on China’s education today. 1. Educational equity and quality of education: how to ensure students in the poverty-stricken areas can enjoy high-quality education? Quality of education is the finally direction of the educational equity, and the quality of education in the poverty-stricken areas in China is still severe from the point of view of students’ scholastic achievement and the state of teaching staff. College entrance examination is the largest academic test in China, students get the qualification to enter the college through this text. For the students in poverty-stricken areas, college entrance examination is the only way for them to change their fate. However, according to a study published in the Social Science in China, the probability of rural students entering the college is getting smaller, and it will be increasing difficult for them to enter the college. In addition, the rate of rural students in the Chinese top universities is declining obviously. (Li 2012). On the other side, teachers in rural areas are not optimistic too. The Responsible editor: Philippe Garrigues