Screen time and depression risk: A meta-analysis of cohort studies.

Background: The impact of screen time on mental health, including depression, has attracted increasing attention from not only children and adolescents but also the elderly. Thus, we conducted a meta-analysis of cohort studies to evaluate the association between screen time and depression risk. Methods: The PubMed, Embase, Web of Science, and China National Knowledge Infrastructure databases were searched for cohort studies up to May 2022, and the reference lists of the included studies were also retrieved. A random-effect model was used to estimate the combined effect size. Heterogeneity was assessed with the I 2 statistic. Potential publication bias was evaluated using a funnel plot and Begg's and Egger's tests. Results: The final analysis included 18 cohort studies with a combined total of 241,398 participants. The pooled risk ratio (RR) was 1.10 (95% confidence interval: 1.05-1.14), with significant heterogeneity (I 2 = 82.7%, P < 0.001). The results of subgroup analyses showed that the pooled RRs varied according to geographic locations, gender, age group, screen time in the control group, depression at the baseline, and whether the study was conducted during the COVID-19 pandemic. No obvious evidence of publication bias was found. Conclusion: This study indicates that screen time is a predictor of depressive symptoms. The effects of screen time on depression risk may vary based on the participant's age, gender, location, and screen time duration. The findings could have important implications for the prevention of depression.

Configurations for positive public behaviors in response to the COVID-19 pandemic: a fuzzy set qualitative comparative analysis.

BACKGROUND: The COVID-19 crisis poses considerable threats to public health, and exploring the key configuration conditions of the public behavior response is very important for emergency risk management. OBJECTIVE: This study attempts to reveal differences in the conditional configuration and mechanism of public behavior based on the proposed framework, further make up for the deficiencies of existing research in explaining such issues as "How to promote the public's protective behavior or reduce the public's excessive behavior?" and finally provide new evidence and ideas for the government to improve the emergency management system. METHODS: A total of 735 valid cases were obtained using an online survey and revealed the conditional configuration and mechanism of public behavior differences through a fuzzy set qualitative comparative analysis based on the proposed public behavioral framework. RESULTS: The results show that critical factors including risk communication, trust, risk perception, and negative emotions alone did not constitute a necessary condition for public protective or excessive behavior. The different configurations of influencing factors reveal the complexity of public behavioral risk management, and taking adequate measures to increase public trust and reduce negative public emotions constitute the core path of risk management to enhance positive public behavior. CONCLUSIONS: The configurations of various influencing factors reveal the complexity of public behavioral risk management. For behavioral risk management, governments should focus on adapting to multiple conditions according to their situations and, under the "overall perspective," formulate policies based on local conditions and further form a differentiated risk management path. Practically speaking, for the government, taking adequate measures to increase public trust and reduce negative public emotions is the core path of risk management to enhance positive public behavior.

Analyzing Risk Communication, Trust, Risk Perception, Negative Emotions, and Behavioral Coping Strategies During the COVID-19 Pandemic in China Using a Structural Equation Model.

Objective: Risk communication and the degree of trust are major factors that affect the public's behavioral coping strategies and play an important role in emergency risk management. However, the internal formation mechanism involved in the public's psychological behavior remains unclear. This study aimed to investigate the association among risk communication, trust, risk perception, negative emotions, and behavioral coping strategies during the coronavirus disease 2019 (COVID-19) pandemic, and to identify and quantify the factors that influence public behavior. Methods: We launched an online survey through social media from April to July 2020 in China. Relevant data were elicited using a self-designed questionnaire that mainly examined respondent characteristics, risk communication, trust, risk perception, negative emotions, protective coping behavior, and excessive coping behavior in the context of the COVID-19 pandemic. A total of 735 valid responses were obtained. A structural equation model was then used to explore relationship pathways among the components. Results: The higher the degree of risk communication (ß = -0.10, p < 0.05) and trust (ß = -0.22, p < 0.001), the lower the public risk perception. Risk communication and trust had a direct effect on public behavioral coping strategies during the COVID-19 pandemic. The higher the level of risk communication (ß = 0.14, p < 0.001) or trust (ß = 0.48, p < 0.001), the more likely it was that this would encourage the public to adopt protective coping behaviors, while the public was less likely to engage in excessive coping behaviors as the degree of trust increased (ß = -0.12, p < 0.01). Risk perception influenced by poor risk communication and trust generated negative emotions (ß = 0.31, p < 0.001), and such negative emotions further positively influenced public behavioral coping strategies (whether protective [ß = 0.09, p < 0.05] or excessive [ß = 0.24, p < 0.001] behaviors). Conclusion: Risk communication, trust, risk perception, and negative emotions were significantly directly or indirectly related to public behavior. The findings provide useful information for emergency risk management and a theoretical basis for follow-up research on public coping behavior during the COVID-19 pandemic.

The impact of social factors, especially psychological worries on anxiety and depression in patients with epilepsy.

BACKGROUND: Social factors are believed to affect mental health in patients with epilepsy (PWE). However, there is still a lack of sufficient manifest proof, given the difficulty of exposing PWE to relatively consistent natural social environments with a low or high level of social interaction to study their significant role. METHODS: This single-center, longitudinal study was conducted via online questionnaires during the coronavirus disease 2019. PWE were recruited from downtown Wuhan and surrounding areas. The Patient Health Questionnaire-9 and Generalized Anxiety Disorder-7 were used to assess psychological status. RESULTS: We analyzed 588 questionnaires completed by 294 PWE who participated in the dual survey. Under lockdown and reopening, the prevalence of anxiety was 13.6%/22.5%, and the prevalence of depression was 19.4%/34.0%. Raising children and seizure-related characteristics, including uncontrolled seizures, seizure exacerbation, seizure frequency ≥ 2/m, and changes in drug regimen, were risk factors in the first and second surveys. A high education level (OR = 1.946, 95% CI = 1.191-3.182), low life satisfaction (OR = 1.940, 95% CI = 1.007-3.737), worry about unanticipated seizures (OR = 2.147, 95% CI = 1.049-4.309), and worry about purchasing medication outside (OR = 2.063, 95% CI = 1.060-4.016) were risk factors for higher scores after reopening. Worry about unanticipated seizures (OR = 3.012, 95% CI = 1.302-6.965) and in-person medical consultation (OR = 2.319, 95% CI = 1.262-4.261) were related to newly diagnosed patients with psychological disorder after reopening. CONCLUSIONS: We identified an association between social variables and epileptic psychiatric comorbidities.

COVID-19 outbreak: The impact of stress on seizures in patients with epilepsy.

OBJECTIVE: Stress is a known trigger for seizures in patients with epilepsy (PWE). However, the association between stress and seizures has not been thoroughly investigated. In December 2019, an outbreak of coronavirus disease (COVID-19) occurred in Wuhan, Hubei province, China, causing tremendous collateral stress. This study was designed to evaluate the influence of the COVID-19 outbreak on seizures in PWE in the most severely affected area, Wuhan, and its surrounding cities. METHODS: In this single-center, cross-sectional study, PWE were surveyed via online questionnaires between February 23 and March 5, 2020. Collected data included demographic information, epilepsy-related characteristics (seizure type, frequency, antiepileptic drugs [AEDs], and medication management), direct and perceived threat of COVID-19, and changes in seizures during the outbreak. Psychological comorbidities were evaluated by the Patient Health Questionnaire-9, Generalized Anxiety Disorder-7 items, and Insomnia Severity Index (ISI). Multivariate logistic regression was used to identify precipitants for seizure exacerbation. RESULTS: We received 362 completed questionnaires after excluding 12 duplicates (response rate = 63.51%). A total of 31 (8.56%) patients had increased seizures during the outbreak. Exposure history to COVID-19 (P = .001), uncontrolled seizure after AED therapy (P = .020), seizure frequency of two or more times per month before the outbreak (P = .005), change of AED regimen during the outbreak (AED reduction, withdrawal, replacement, skipping altogether; P = .002), and worry about the adverse effect of the outbreak on overall seizure-related issues (severity = moderate to critical; P = .038) were risk factors for increased seizures. SIGNIFICANCE: A minority of PWE experienced seizure exacerbation during the outbreak of COVID-19. Stress, uncontrolled seizures, and inappropriate change in AED regimen were associated with increased seizures. Based on these findings, stress might be an independent precipitant for triggering seizures in some PWE.