Longitudinal network relations between symptoms of problematic internet game use and internalizing and externalizing problems among Chinese early adolescents

The Longitudinal Effect of Psychological Distress on Internet Addiction Symptoms Among Chinese College Students: Cross-Lagged Panel Network Analysis

BACKGROUND

There is a growing amount of evidence suggesting high rates of co-occurring internet addiction (IA) symptoms and psychological distress in youth. However, the extent to which IA symptoms develop over time, how they interact with psychological distress symptoms dynamically, and how they predict one another remain unclear. Additionally, what specific types of distress, including depression, anxiety, and stress, are more closely associated with IA symptoms remains inconclusive.

OBJECTIVE

This longitudinal study aimed to explore the development of and changes in IA symptoms over time and the directional relationship between IA and various psychological distress symptoms.

METHODS

This study followed a sample of 2497 Chinese college students (mean age 19.14, SD 0.72 years) across 3 waves of a data collection span of 2 years. Their IA and psychological distress symptoms were assessed at baseline (T1), 12-month follow-up (T2), and 24-month follow-up (T3). We used network analysis to examine the network structure of IA symptoms at each wave and cross-lagged panel network (CLPN) analysis to investigate longitudinal associations between IA symptoms and psychological distress, including depressive, anxiety, and stress symptoms.

RESULTS

The cross-sectional networks of IA symptoms at 3 time points showed high similarity in terms of structure, existence of edges, and centrality indices. Nodes A2 (excessive use), A1 (salience), and A5 (lack of control) emerged as nodes with the highest expected influence (EI) centrality in the IA symptom networks across time (A2: EI=1.13 at T1, 1.15 at T2, 1.17 at T3; A1: EI=1.10 at T1, 1.13 at T2, 1.15 at T3; A5: EI=0.86 at T1, 0.88 at T2, 0.92 at T3). CLPN analysis revealed that psychological distress predicts IA symptoms but not the other way around. Depressive symptoms played a key role in predicting various IA-related problems (T1 to T2, edge weight=0.11; T2 to T3, edge weight=0.28; T1 to T3, edge weight=0.22) and served as bridge symptoms connecting IA and psychological distress (T1 to T2: bridge-expected influence [BEI]=0.15; T2 to T3: BEI=0.14; T1 to T3: BEI=0.19).

CONCLUSIONS

Findings revealed a relatively stable network structure of IA symptoms among college students and suggested that psychological distress, especially depressive symptoms, may play a central role in activating IA symptoms over time. These results provide evidence for understanding the directional relationship between the central characteristics of distress symptoms and IA. The study also underscores the importance of depressive symptoms in their co-occurrence with IA, indicating that the key and bridge symptoms identified in this study can be prioritized as targets for preventing and treating IA in Chinese youth. Through identification and early intervention of depressive symptoms, we may avoid the progression of co-occurring issues, leading to more effective treatment outcomes.

A cross-lagged panel network model on internet gaming disorder and depressive symptoms concerning preferences for game genres

BACKGROUND

Internet gaming disorder (IGD) is a prevalent behavioral addiction that co-occurs with depression. Little is known about how IGD and depression intercorrelate longitudinally at a symptom level. This study aimed to explore the directional relationships between IGD and depressive symptoms and identify the key symptoms in their comorbidity using cross-lagged panel network (CLPN) modeling.

METHODS

A sample of 601 young gamers (mean age = 23.76) in Hong Kong completed the Internet Gaming Disorder Scale - Short Form and Patient Health Questionnaire-9 semi-annually at two-time points. Autoregressive and cross-lagged effects between depressive and IGD symptoms were analyzed via CLPN while controlling gamers' preferences across five game genres in R.

RESULTS

The comorbidity was mainly driven from depressive symptoms to IGD symptoms, with a few weaker associations from IGD to depressive symptoms. 'Anhedonia' (out-/bridge-expected influence = 2.88; 0.03) and 'Motor problems' (out-/bridge-expected influence = 1.24; 0.03) from depression were the central and bridge symptoms to trigger the development of IGD symptoms, whereas 'continue gaming despite harm' (in-expected influence = 1.29) was the most consequent symptom. 'Anhedonia' (r = 0.17) and 'suicidal risk' (r = 0.15) to 'continuation despite harm' were the strongest paths connecting depression and IGD. Gamers who preferred First-Person Shooter games and Massively Multiplayer Online Role-Playing games were more vulnerable to depressive and IGD symptoms.

CONCLUSIONS

Our findings provide empirical support for the comorbidity between IGD and depression and clarify their directional relationships at a symptom level. We identify antecedent bridge symptoms as targets for preventing escalation of co-occurring issues.

Network Analysis of Core Symptoms of Internalizing and Externalizing Symptoms Among Children with Dyslexia in Saudi Arabia

Researches indicate that children with dyslexia are more likely to experience psychiatric symptoms throughout life compared to peers in the general population. Improving the classification of psychiatric symptoms in this population can be a valuable goal for strengthing therapeutic models. The current study aimed to evaluate the dynamic associations between internalizing and externalizing symptoms in children with dyslexia using network analysis. This cross-sectional study was conducted in Saudi Arabia from April to July 2024, involving 183 children aged 8-11 diagnosed with dyslexia, recruited through convenience sampling from local schools and clinics. The Child Behavior Checklist (CBCL) was utilized to assess a range of psychopathological symptoms, focusing on six clusters: affective problems, anxiety problems, somatic symptoms, ADHD symptoms, oppositional defiant problems, and conduct problems. Notably, "cries a lot" emerged as a central symptom in the affective network, while "dependent" was identified as the most pivotal symptom in the anxiety network. Centrality measures-betweenness, closeness, and strength-were employed to quantify the significance of each symptom. The findings suggest that these central symptoms may contribute to the development and persistence of psychiatric comorbidities in children with dyslexia. Interventions targeting these core symptoms could enhance psychological outcomes for this population. Overall, this study lays the groundwork for future research into tailored intervention strategies to address unique psychiatric comorbidities associated with dyslexia.

Characteristic Structure of the Relationships Among Depression, Maladaptive Cognition, and Internet Addiction and Its Temporal Evolution in University Students: A Network Analysis

This study explored the structure and temporal evolution of the relationship among depression, maladaptive cognition, and internet addiction (DMI) among university students by focusing on topological and dynamic properties in a network analysis. A 3-year longitudinal survey was conducted with 873 university students (Mage = 18.32, SD = 0.74). The results of network analysis showed "compulsive internet use and withdrawal symptoms" as part of internet addiction and "depressive emotions" as part of depression were the core characteristics in the DMI relational structure. Additionally, "compulsive internet use and withdrawal symptoms" was most pronounced for freshmen, whereas "depressive emotions" were most pronounced for sophomores and juniors. These findings suggest that interventions addressing DMI among university students should not only focus on the key aspects of "compulsive internet use and withdrawal symptoms" and "depressive emotions," but also consider differences between students at different years of study.

Examining the Psychometric Network Structure of Social Anxiety: A Scoping Review

The network approach offers a novel perspective for conceptualizing the psychopathology of social anxiety disorder (SAD). This scoping review aimed to map the existing literature on the psychometric network structures of social anxiety symptoms and identify future research directions. A total of 61 studies were identified through searches in PubMed, PsycINFO, ScienceDirect, Cochrane Library, ClinicalTrials.gov and the Open Science Framework databases, employing the keywords ('social anxiety disorder' OR 'social phobia' OR 'social anxiety') AND ('network analysis'). Of these, 10 studies examined the network structures of social anxiety symptoms in patients with SAD, 17 investigated such structures in individuals without an SAD diagnosis and 34 explored networks of other symptoms that included social anxiety symptoms. Most studies were conducted on Western and Chinese populations, underscoring the need for broader cross-cultural comparisons. The central symptoms in SAD networks were fear and anxiety related to performing and interacting with groups, engaging with strangers or unfamiliar individuals, participating in events and being the center of attention. However, the network structures of SAD and related symptoms remain underexplored, with existing studies offering only partial insights. This review emphasizes the need for future research to comprehensively assess social anxiety symptoms and adopt cross-cultural comparative designs to deepen the understanding of SAD psychopathology. These findings provide a foundation for future research on SAD utilizing network analysis.

The prospective associations between problematic gaming and phubbing among Chinese adolescents: Insights from a cross-lagged panel network model

BACKGROUND AND AIMS

Previous studies are limited in addressing the directionality of temporal relationships between problematic gaming and phubbing symptoms by exploring cross-sectional studies. Therefore, we estimated the longitudinal relationships between individual behavioral addictive symptoms including problematic gaming and phubbing in adolescence, and explored potential sex differences in these relationships.

METHODS

This study included 3296 participants in Shandong Province, China. Data were collected from November 2021 (mean [SD] age: 15.17 [1.44] years) to May 2023 (mean [SD] age: 17.50 [1.18] years), with females comprising 54.5 % of the sample. Problematic gaming and phubbing were assessed using validated scales at each wave. We construct cross-sectional networks and cross-lagged panel networks (CLPN) to explore the contemptuous and temporal relationships between problematic gaming and phubbing.

RESULTS

Contemporaneous networks revealed significant differences in problematic gaming and phubbing networks between males and females. Additionally, temporal network analyses indicated that among male adolescents, feeling anxious when unable to play games was the most influential predictor of subsequent behavioral addictive symptoms. For female adolescents, fantasizing about gaming had the most significant associations with future addictive behaviors. The strongest bridge symptom linking problematic gaming and phubbing for both sexes was focusing on phones rather than engaging in conversation.

DISCUSSION AND CONCLUSIONS

The study applied network modeling to panel data from a large, population-based cohort of adolescents, identifying unique longitudinal relationships between problematic gaming and phubbing across symptom domains. It provides valuable insights into the characterization of behavioral addictive symptoms among adolescents and the potential predictive relationships among these symptoms among different sexes, guiding sex-specific targeted interventions for adolescents.

A panel network approach of internalizing and externalizing problems in early childhood: Evidence from American and Chinese preschoolers

Internalizing and externalizing problems tend to co-occur beginning in early childhood. However, the dynamic interplay of symptom-level internalizing and externalizing problems that may drive their co-occurrence is poorly understood. Within the frameworks of the Network Approaches to Psychopathology and the Developmental Cascade Perspective, this study used a panel network approach to examine how symptoms of internalizing and externalizing problems are related in early childhood both concurrently and longitudinally and whether the pattern may differ in American (N = 1,202) and Chinese (N = 180) preschoolers. Internalizing and externalizing problems were rated by mothers in two waves. Results from cross-sectional networks showed that the bridge symptoms underlying the co-occurrence of internalizing and externalizing problems were largely consistent in American and Chinese preschoolers (e.g., withdrawal, aggressive behavior, anxiety and depressive moods). Results from cross-lagged panel networks further showed that the co-occurrence was manifested by unidirectional relations from internalizing to subsequent externalizing symptoms in both American and Chinese preschoolers. The findings contribute needed cross-cultural evidence to better understand the co-occurrence of internalizing and externalizing problems and highlight the temporal heterogeneity of the symptom networks of internalizing and externalizing problems in early childhood.

Maternal Depressive Symptoms and Offspring Internalizing Problems: A Cross-Lagged Panel Network Analysis in Late Childhood and Early Adolescence

The present study investigated the relations between maternal depressive symptoms and internalizing problems in offspring during late childhood and early adolescence, examining sex differences using symptom network analysis. A total of 885 Chinese youths in late childhood (n = 497, 38.6% girls; age = 9.58 years, SD = 0.24) and early adolescence (n = 388, 48.5% girls; age = 11.30 years, SD = 0.24) and their mothers (Mage = 37.34 years, SD = 5.42) were recruited. Cross-lagged panel network (CLPN) analysis was used to explore bridge symptoms (i.e., symptoms connecting two or more mental disorders) and identify transmission pathways between maternal depressive symptoms and offspring's internalizing problems at these two developmental stages. The CLPN results revealed that in late childhood, the bridge connections in the network model were boys feeling worried to mothers feeling distractible, and girls feeling worried to mothers feeling powerless. In early adolescence, the bridge connections were boys experiencing depressed mood to mothers feeling powerless, and mothers feeling bad to girls experiencing depressed mood. These findings highlight the network-level relations between maternal depressive symptoms and offspring internalizing problems. They provide insights into the developmental differences and similarities in symptoms during these periods and suggest ways to break the vicious cycle of psychopathology between mothers and their children.

Improving health and reducing health inequality: An innovation of digitalization?

RATIONALE

The association between digitalization and individual health has attracted increasing attention from both scholars and policymakers. Existing research, however, has not agreed on whether digitization can improve health or reduce health inequality.

OBJECTIVE

The purpose of this study is to clarify whether and how the development of digitalization may be related to health and health disparities.

METHODS

We rely on China Family Panel Studies (CFPS) surveys from 2012 to 2018 to obtain a sample of 82,471 observations to explore the impact of digitalization on self-rated health and health inequality and its transmission mechanisms. The hypotheses are tested by Ordinary Least Squares Modeling.

RESULTS

As expected, digitalization is significantly and positively correlated with self-rated health. Furthermore, the development of digitalization has led to a notable decrease in health inequality. The influencing mechanisms of digitalization include income, healthcare consumption and health behaviors. Both dimensions of digitalization-internet development and digital finance-generate significant effects and the effects of internet development are greater.

CONCLUSIONS

This study is the first to systematically investigate the impact of digitalization development on health and health inequality. Our findings provide evidence for the health promotion theory by clarifying the benefits of digitalization in improving residents' health and reducing health inequality. Therefore, utilizing the tools of digitalization efficiently could be a focus of policymakers aiming to accomplish the SDGs' health targets.

Uncovering the symptom relationship between anxiety, depression, and internet addiction among left-behind children: A large-scale purposive sampling network analysis

Facing long-term separation from their parents, left-behind children are at risk of the co-occurrence of internalizing and externalizing problems. Although previous research has gained substantial information examining the relationship between anxiety, depression, and internet addiction at the aggregate level of variables, little is known about the heterogeneity and interactions between these components at the symptom level with a large-scale purposive sample. Adopting the network approach, two network pathways, depression and anxiety, and associations between these variables and internet addiction were constructed. Our sample included 5367 left-behind children (Mage = 13.57; SDage = 1.37; 50.07% females). Relevant bridging, central symptoms, and network stability were identified. Two relatively stable networks were obtained. For the network of anxiety and depression, sleep problems and tachycardia were vital bridging symptoms. Central symptoms, including tachycardia, restlessness, fatigue, and emptiness, were symptoms of depression. For the network of symptoms of anxiety, depression, and internet addiction, the bridging symptoms remained the same, and the central symptoms included tachycardia, restlessness, loss of control, and emptiness. By identifying relevant bridging and central symptoms, those with higher levels of these symptoms could be regarded as intervention targets, providing a reference for the current issue of valuing diagnosis over prevention in left-behind children.