Dataset Information

Internet addiction and residual depressive symptoms among clinically stable adolescents with major psychiatric disorders during the COVID-19 pandemic: a network analysis perspective.

ABSTRACT: To assess the inter-relationships between residual depressive symptoms (RDS) and Internet addiction (IA) using network analysis among clinically stable adolescents with major psychiatric disorders during the COVID-19 pandemic. RDS and IA were assessed using the Patient Health Questionnaire-9 (PHQ-9) and the Internet Addiction Test (IAT), respectively. Central symptoms and bridge symptoms in the network model were examined. A total of 1,454 adolescents met the study criteria and were included in the analyses. The prevalence of IA was 31.2% (95% CI: 28.8%-33.6%). In the network analysis, the nodes IAT15 ("Preoccupation with the Internet"), PHQ2 ("Sad mood"), and PHQ1 ("Anhedonia") were the most central symptoms in the IA-RDS network model. Bridge symptoms included IAT10 ("Sooth disturbing about your Internet use"), PHQ9 ("Suicide ideation"), and IAT3 ("Prefer the excitement online to the time with others"). Additionally, PHQ2 ("Sad mood") was the main node linking "Anhedonia" to other IA clusters. Internet addiction was common among clinically stable adolescents with major psychiatric disorders during the COVID-19 pandemic. Core and bridge symptoms identified in this study could be prioritized as targets for the prevention and treatment of IA in this population.

SUBMITTER: Cai H

PROVIDER: S-EPMC10238780 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Internet addiction and residual depressive symptoms among clinically stable adolescents with major psychiatric disorders during the COVID-19 pandemic: a network analysis perspective.

Cai Hong H Zhao Yan-Jie YJ He Fan F Li Shu-Ying SY Li Zong-Lei ZL Zhang Wu-Yang WY Zhang Yao Y Cheung Teris T Ng Chee H CH Sha Sha S Xiang Yu-Tao YT

Translational psychiatry 20230603 1

To assess the inter-relationships between residual depressive symptoms (RDS) and Internet addiction (IA) using network analysis among clinically stable adolescents with major psychiatric disorders during the COVID-19 pandemic. RDS and IA were assessed using the Patient Health Questionnaire-9 (PHQ-9) and the Internet Addiction Test (IAT), respectively. Central symptoms and bridge symptoms in the network model were examined. A total of 1,454 adolescents met the study criteria and were included in ...[more]

PMID: 37270593

Similar Datasets

Project description:ObjectiveThis study examined the prevalence of cyberbullying and its relationship with residual depressive symptoms in this patient population during the COVID-19 outbreak using network analysis.MethodsThis was a multicenter, cross-sectional study. Adolescent patients attending maintenance treatment at outpatient departments of three major psychiatric hospitals were included. Experience of cyberbullying was measured with a standard question, while the severity of Internet addiction and depressive symptoms were measured using the Internet Addiction Test and the Patient Health Questionnaire-9, respectively. The network structure of depression and cyberbully were characterized and indices of "Expected Influence" was used to identify symptoms central to the network. To identify particular symptoms that were directly associated with cyberbully, the flow function was used.ResultsAltogether 1,265 patients completed the assessments. The overall prevalence of cyberbullying was 92.3% (95% confidence interval (CI): 90.8-93.7%). Multiple logistic regression analysis revealed that male gender (p = 0.04, OR = 1.72, 95%CI: 1.04-2.85) was significantly associated with higher risk of cyberbullying, while a relapse of illness during the COVID-19 pandemic was significantly associated with a lower risk of cyberbullying (p = 0.03, OR = 0.50, 95%CI: 0.27-0.93). In the network of depression and cyberbully, "Sad mood," "Anhedonia" and "Energy" were the most central (influential) symptoms. Furthermore, "Suicidal ideation" had the strongest negative association with cyberbully followed by "Guilt".ConclusionDuring the COVID-19 pandemic, the experience of cyberbullying was highly prevalent among clinically stable adolescent psychiatric patients, particularly male patients. This finding should raise awareness of this issue emphasizing the need for regular screening and interventions for adolescent patients. Central symptoms (e.g., "Sad mood," "Anhedonia" and "Energy") identified in this study should be targeted in interventions and preventive measures.

Project description:BackgroundChildren's lives are increasingly mediated by digital technologies, yet evidence regarding the associations between internet use and depression is far from comprehensive and remains unclear.ObjectiveThis study aimed to investigate the dose-response association between internet use, including use time and addiction behaviors, and depressive symptoms among children and adolescents in Zhejiang Province.MethodsData were collected from a school-based health survey China Common Disease and Risk Factor Surveillance Among Students, encompassing 21,336 students in Zhejiang Province. The daily internet use time, internet addiction (IA) behaviors, and depressive symptoms were assessed with questionnaires. Logistic regression models were used to explore the associations of internet use time and IA behaviors with depressive symptoms among children and adolescents. Restricted cubic spline curves were used to determine the dose-response associations.ResultsA total of 6225 (29.2%) students had depressive symptoms. Compared to those reporting no internet use, boys using the internet for >2 hours/day (odds ratio [OR] 1.53, 95% CI 1.34-1.74) and girls using internet for 1.1-2 hours/day (OR 1.22, 95% CI 1.06-1.39) and >2 hours/day (OR 1.70, 95% CI 1.50-1.93) were at higher risks of depressive symptoms. A significant J-shaped association was identified between internet use time and depressive symptoms among children and adolescents, especially in boys and primary school students (nonlinear P values were .006, .003, and <.001, respectively). Increased IA behaviors were associated with a higher odd of depressive symptoms (1 IA behavior: OR 2.01, 95% CI 1.83-2.21; 2 IA behaviors: 2.91, 95% CI 2.57-3.29; and ≥3 IA behaviors: 4.72, 95% CI 4.26-5.22). A positive nonlinear association between the number of IA behaviors and depressive symptoms was found in total population, girls, and primary school students (nonlinear P values were .02, .002, .007, respectively).ConclusionsFindings suggested that excessive internet use time and IA behaviors were significantly associated with an increased risk of depressive symptoms, highlighting the importance of interventions to regulate and educate about adequate internet use during childhood and adolescence.

Project description:Background: Sleep quality plays a principal role in the protection of health. There is an increasing number of studies in the literature demonstrating that internet addiction and smartphone addiction impair sleep quality. However, the number of studies on Turkish adolescents is very limited. Therefore, this study examined the effects of internet addiction and smartphone addiction on sleep quality among Turkish adolescents. Methods: Participants in this cross-sectional study were 910 adolescents aged 13-18 years. Data were collected with the Short Internet Addiction Test, Smartphone Addiction Scale, and Pittsburgh Sleep Quality Index. In addition, a questionnaire was used to gather information about the demographic, socioeconomic, and health-related characteristics. Pearson's Chi-square test, Chi-square test for trend, Mann-Whitney U test, logistic regression analysis, and Spearman's correlation analysis were used in the analysis. Results: The sleep quality of 58.7% of the adolescents was poor. Additionally, girls and adolescents ≥16 years old had poor sleep quality. Sleep quality deteriorated as perceived health status and perceived economic status of family deteriorated. Compared to participants with normal internet addiction scores, poor sleep quality was 1.83 (95% CI [1.22-2.74]) times higher in those with problematic internet addiction and 1.99 (95% CI [1.23-3.87]) times higher in those with pathological internet addiction. One point increase in Smartphone Addiction Scale total score increased poor sleep quality 1.01 (95% CI [1.00-1.02]) times. Sleep quality scale were positively correlated with the smartphone addiction and internet addiction. However, there was no positive correlation between habitual sleep efficiency subcomponent of sleep quality and smartphone addiction and internet addiction. Conclusions: Internet addiction and smartphone addiction were associated with poor sleep quality in adolescents. Older adolescents (≥16 years), gender (female), poor health perception, and perception of moderate economic status of the family were other factors associated with poor sleep quality.

Dataset Information

Internet addiction and residual depressive symptoms among clinically stable adolescents with major psychiatric disorders during the COVID-19 pandemic: a network analysis perspective.

Publications

Internet addiction and residual depressive symptoms among clinically stable adolescents with major psychiatric disorders during the COVID-19 pandemic: a network analysis perspective.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets