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Objective@#To analyze the status and correlation between screen time, screen behavior type, and anxiety, depression among children and adolescents in Jiangxi Province, so as to provide a basis for effective intervention measures.@*Methods@#Using the method of stratified random sampling, 8 851 primary and secondary school students in 11 districts of Jiangxi Province were investigated by questionnaire during September to December in 2020. Anxiety and depression status were investigated using the State Trait Anxiety Inventory (STAI) and the Center for Epidemiological Studies Depression Scale for Children(CES-DC), respectively. Single factor analysis using χ 2-test, t-test,analysis of variance,and multivariate analysis using generalized linear models.@*Results@#On school days and weekends, 4.7% and 20.4% of primary and secondary school students in Jiangxi Province had a total screen time of over 2 hours per day, respectively. The weighted scores of the total screen time (primary school students: 1.88± 0.68, junior middle school students: 1.96±0.71, high school students: 2.03±0.80) and time spent for playing video games (primary school students: 1.51±0.64, junior middle school students: 1.62±0.69, high school students: 1.68±0.75) daily showed an upward trend with the increase of educational stage ( F =31.48, 42.13), and with significantly higher in boys (1.97±0.74, 1.66± 0.72) than girls (1.93±0.72, 1.53±0.66)( t =2.48, 9.07)( P <0.05). The average scores of state anxiety and trait anxiety were (42.20±9.05) and (40.65±9.85), which showed an upward trend with the increase of educational stage ( F =168.12, 241.98 ), and were higher in girls than boys ( t =6.63, 8.48)( P <0.01). The average score of depression was (11.99±11.00), which was lower in elementary school students than middle school students and high school students ( F =136.42), with significantly higher in girls ( t =6.85)( P <0.01). On school days, with the increase of total screen time and time spent for playing video games daily, the risk of state anxiety, trait anxiety, and depression among primary and secondary school students significantly increased ( OR = 6.70- 818.98, P <0.01). On weekends, among primary and secondary school students, the total screen time of >1-2 hours daily reduced the risk of state anxiety ( OR =0.30). The risk of developing trait anxiety among students playing video games for more than 2 hours daily was 2.50 times higher than those without screen behavior ( OR =2.50). The risk of developing depression with a total screen time of more than 2 hours daily was 3.15 times higher those whithout screen behavior ( OR =3.15). The risk of developing depression among students playing video games >0-1, >1-2, >2 h daily was 2.14, 2.50, 4.90 times that of those without screen behaviors ( OR =2.14, 2.50, 4.90), and showed an upward trend with the increase of educational stage ( P <0.05).@*Conclusions@#Screen behaviors of primary and middle school students in Jiangxi Province are positively associated with the risk of anxiety and depression, but the total daily video time of >1-2 h on weekends was negatively associated with state anxiety. It is necessary to control the screen time as much as possible and reduce the risk of anxiety and depression.
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BACKGROUND: Postoperative brain edema is a common complication in patients with high-grade glioma after craniotomy. Both Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) are applied to diagnose brain edema. Usually, MRI is considered to be better than CT for identifying brain edema. However, MRI is not generally applied in diagnosing acute cerebral edema in the early postoperative stage. Whether CT is reliable in detecting postoperative brain edema in the early stage is unknown. OBJECTIVE: This study aimed at investigating the agreement and correlation between CT and MRI for measuring early postoperative brain edema. METHODS: Patients with high-grade glioma who underwent craniotomy in the Beijing Tiantan hospital from January 2017 to October 2018 were retrospectively analyzed. The region of interest and operative cavity were manually outlined, and the volume of postoperative brain edema was measured on CT and MRI. Pearson correlation testing and the Intraclass Correlation Coefficient (ICC) were used to evaluate the association and agreement between CT and MRI for detecting the volume of postoperative brain edema. RESULTS: Twenty patients were included in this study. The interrater agreement was perfect for detecting brain edema (CT: κ=1, ICC=0.977, P<0.001; MRI: κ=0.866, ICC=0.963, P<0.001). A significant positive correlation and excellent consistency between CT and MRI were found for measuring the volume of brain edema (rater 1: r=0.97, ICC=0.934, P<0.001; rater 2: r=0.97, ICC=0.957, P<0.001). CONCLUSION: Substantial comparability between CT and MRI is demonstrated for detecting postoperative brain edema. It is reliable to use CT for measuring brain edema volume in the early stage after surgery.
