The Association Between Internet Addiction and Anxiety in Nursing Students: A Network Analysis

Exploring the association between internet addiction and time management among undergraduate nursing students

BACKGROUND

Modern undergraduate nursing students face unique challenges as digital natives balancing internet activities with the substantial academic demands of nursing studies. Given the detrimental effects of internet addiction on students' academic performance and well-being, having time management skills is crucial.

AIMS

To assess the prevalence and levels of internet addiction and time management and their association among undergraduate nursing students.

DESIGN

A cross-sectional, survey-based research design was used.

SETTING

The Faculty of Nursing at Alexandria University in Egypt.

SUBJECTS

A stratified random sample consisting of 825 undergraduate nursing students.

TOOLS

The internet addiction test and time management questionnaire were utilized to collect data.

FINDINGS

Internet addiction was prevalent among 98.8% of students, with 56.0% exhibiting mild levels, 40.0% showing moderate levels, and 2.8% having severe levels. A statistically significant negative correlation was found between students' internet addiction and overall time management (r= - 0.387, p < 0.001).

CONCLUSION

A considerable level of internet addiction was revealed among the great majority of undergraduate nursing students; however, many students also demonstrated strong time management skills. Furthermore, internet addiction and overall time management were negatively associated, indicating that students with higher levels of internet addiction tend to have poorer time management abilities.

RECOMMENDATIONS

Individual counseling and educational training programs should be developed to teach nursing students how to manage time and effectively plan internet usage.

Understanding the relationships among adolescents' internet dependence, reward, cognitive control processing, and learning burnout: a network perspective in China

Alterations in the reward and cognitive control systems are commonly observed among adolescents with internet dependence (ID), and this impairment is often accompanied by social dysfunctions, such as academic burnout. However, the intercorrelations among ID, reward, cognitive control processing, and learning burnout remain unclear. We recruited 1074 Chinese adolescents to investigate the complex interrelationships among these variables using network analysis. The resulting network revealed patterns that connected ID to the behavioral inhibition/activation system (BIS/BAS), self-control, and learning burnout; these results exhibited reasonable stability and test-retest consistency. Throughout the network, the node of BAS-drive was the critical influencing factor, and the node of self-control was the protection factor. In addition, several symptoms of learning burnout and ID were positively associated with sensitivity to punishment. As revealed by the network comparison test, the network constructed among internet dependent (ID) group differed from the network constructed among internet nondependent (IND) group not only in the edges between BIS and learning burnout but also in terms of the edges associated with learning burnout. In conclusion, this study provides insights into the complex mechanisms underlying ID among adolescents from the perspective of the network relationships between core influencing factors and negative consequences. It validates the dual-system model of risky behavior among adolescents and offers a foundation for early warning and interventions for ID in this context.

Does internet addiction affect the level of emotional intelligence among nursing students? A cross-sectional study

AIM

To examine the effect of internet addiction on emotional intelligence among nursing students. Internet addiction, especially among nursing students, is an ongoing and urgent issue globally. Despite studies acknowledging its negative effects, the specific impact on the emotional intelligence of college students is not completely explored and needs more investigation.

DESIGN

A correlational cross-sectional descriptive study.

METHODS

Participants included 180 nursing students from Mansoura University, Egypt. They completed the Socio-demographic sheet, Internet Addiction Test, and Schutte Self-Report Emotional Intelligence. Descriptive statistics, Pearson correlation, and regression analysis were conducted to analyze the data.

RESULTS

Nursing students experience a moderate level of internet addiction and a neutral level of emotional intelligence. A significant negative relationship was established between internet addiction among students and their emotional intelligence (r = - 0.53, p < 0.001) and its four facets: perception of emotion, managing own emotions, managing others' emotions, and utilization of emotion. Regression analysis showed that internet addiction had a negative effect on emotional intelligence among nursing students (β = - 0.553, p < 0.001) and explained 30.5% of the variance of emotional intelligence among nursing students.

CONCLUSIONS

The study findings suggest that internet addiction negatively impacts the emotional intelligence of nursing students, which is crucial for effective interpersonal relations and professional competence in nursing.

IMPLICATIONS

The study underscores the need for educational programs to raise awareness about the hazards of excessive internet use and to promote activities that mitigate internet addiction.

A network analysis of the interrelationships between depression, anxiety, insomnia and quality of life among fire service recruits

Background

Research on the mental health and quality of life (hereafter QOL) among fire service recruits after the end of the COVID-19 restrictions is lacking. This study explored the network structure of depression, anxiety and insomnia, and their interconnections with QOL among fire service recruits in the post-COVID-19 era.

Methods

This cross-sectional study used a consecutive sampling of fire service recruits across China. We measured the severity of depression, anxiety and insomnia symptoms, and overall QOL using the nine-item Patient Health Questionnaire (PHQ-9), seven-item Generalized Anxiety Disorder scale (GAD-7), Insomnia Severity Index (ISI) questionnaire, and World Health Organization Quality of Life-brief version (WHOQOL-BREF), respectively. We estimated the most central symptoms using the centrality index of expected influence (EI), and the symptoms connecting depression, anxiety and insomnia symptoms using bridge EI.

Results

In total, 1,560 fire service recruits participated in the study. The prevalence of depression (PHQ-9 ≥ 5) was 15.2% (95% CI: 13.5-17.1%), while the prevalence of anxiety (GAD-7 ≥ 5) was 11.2% (95% CI: 9.6-12.8%). GAD4 ("Trouble relaxing") had the highest EI in the whole network model, followed by ISI5 ("Interference with daytime functioning") and GAD6 ("Irritability"). In contrast, PHQ4 ("Fatigue") had the highest bridge EI values in the network, followed by GAD4 ("Trouble relaxing") and ISI5 ("Interference with daytime functioning"). Additionally, ISI4 "Sleep dissatisfaction" (average edge weight = -1.335), which was the central symptom with the highest intensity value, had the strongest negative correlation with QOL.

Conclusion

Depression and anxiety were important mental health issues to address among fire service recruits in the post-COVID-19 era in China. Targeting central and bridge symptoms identified in network analysis could help address depression and anxiety among fire service recruits in the post-COVID-19 era.

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.

Core and bridge symptoms of demoralization in Chinese female cancer patients: a network analysis

Objective

In this study, we explore the core and bridge symptoms of demoralization in female cancer patients in China, and provide a basis for precise psychological intervention among female cancer patients.

Methods

This study used a cross-sectional survey. Participants were recruited from three third-class hospitals in Jiangsu Province from June 2022 to June 2023 using the convenience sampling method. The severity of each symptom of demoralization was investigated in female cancer patients using the Demoralization Scale (DS). Network analysis was performed using the R language to identify core and bridge symptoms in the network and further explore some characteristic edge connections in the network.

Results

The network structure model of demoralization had strong accuracy and stability. In the network, the symptoms with the highest strength centrality were "Discouragement" (C3, strength=2.19), "No self-worth" (A3, strength=1.21), "Don't want to live" (A5, strength=1.20), "Hopeless" (D4, strength=0.81), and "Vulnerability" (B3, strength=0.74), respectively. The bridge strength analysis identified "Hopeless" (D4, bridge strength=0.92), "Discouragement" (C3, bridge strength=0.85), "No self-worth" (A3, bridge strength=0.75), "Poor spirits" (E2, bridge strength=0.71), and "Vulnerability" (B3, bridge strength=0.69) as the bridge symptoms. The strongest edge connections of all dimensions were "No self-worth" and "Worthless" (A3-E6, edge weighting=0.27), "Poor spirits" and "Loss of emotional control" (E2-D1, edge weighting=0.22), "Discouragement" and "Vulnerability" (C3-B3, edge weighting=0.14), and "Hopeless" and "No meaning of survival" (D4-A4, edge weighting=0.12).

Conclusion

"Discouragement (C3)", "No self-worth (A3)", "Hopeless (D4)", and "Vulnerability (B3)" are both core symptoms and bridge symptoms. These symptoms can not only trigger a patient's demoralization but also stimulate more severe symptom clusters through interactions. The early recognition of and intervention regarding these symptoms could be important for the prevention and treatment of demoralization among female cancer patients.

Internet Addiction and Emotional Intelligence in university nursing students: A cross-sectional study

Background

The appearance of the Internet has allowed for improved communications and the technological development of society, but it has also led to problematic use, generating addictive behaviors in some university students. Emotional Intelligence helps to improve emotional skills, increase social skills, and act as a protective factor against technological addictions.

Objectives

to describe and analyze the relationship between Internet Addiction, Emotional Intelligence, and sociodemographic characteristics in Nursing students.

Methods

A multicenter cross-sectional study was conducted. Participants belonged to three different campuses of two Universities. 532 nursing students were included in the study. A self-administered questionnaire was used collecting sociodemographic variables and the TMMS-24 and IAT instruments were employed to measure Emotional Intelligence and Internet Addiction, respectively.

Results

11.1% of the students presented Internet Addiction. Higher Internet Addiction scores were obtained by those who were younger, had a lower academic year, and were more involved in leisure activities. Adequate levels of Emotional Intelligence were found, women showed higher values of Attention and men of Repair. Students aged 24 or over reported higher Clarity and Repair values. There was an inverse relationship between Clarity and Repair with Internet Addiction values.

Conclusions

The ability to understand and regulate emotional states is related to lower Internet Addiction values. The group of Internet addicts revealed greater Attention and less Clarity. Internet Addiction values increased as the number of hours of Internet use increases. The development of programs which improve Emotional Intelligence could be essential to facilitate the emotional management of Internet Addiction.

Network structure of mobile phone addiction and anxiety symptoms among rural Chinese adolescents

BACKGROUND

The incidence of mobile phone addiction among adolescents in rural areas of China is increasing year by year, and has already exceeded that of some cities. And phone addiction increases the risk of anxiety and poor sleep. Therefore, this study used network analysis to investigate the relationship between mobile phone addiction and anxiety symptoms, and the predictability to sleep quality.

METHODS

From September 2021 to March 2022, a total of 1920 rural adolescents in Xuzhou, China were included. The survey included information on phone addiction, anxiety symptoms, and sleep quality. Network analysis was used to estimate the network structure of adolescents' mobile phone addiction and anxiety symptoms. LOWESS curve and linear regression were used to test the predictive ability of node-centrality on sleep quality.

RESULTS

In the network of mobile phone addiction-anxiety symptoms, the most influential symptoms were Failure to cut down the time, Anxiety if not used for some time, and Alleviate loneliness. Irritability was the most prominent bridging symptom. Gender difference had no effect on network structure. Nodes in the network are not predictive of sleep quality.

CONCLUSION

Failure to cut down the time is the most important symptom, suggesting that measures should be taken to reduce the amount of time spent on mobile phones. For example, increase outdoor exercise, increase the real company of friends and family, in order to reduce the occurrence of mobile phone addiction and anxiety.

The Impact of Long-Term Online Learning on Internet Addiction Symptoms among Depressed Secondary School Students: Insights from a Cross-Panel Network Analysis

BACKGROUND

The COVID-19 pandemic and the shift to online learning have increased the risk of Internet addiction (IA) among adolescents, especially those who are depressed. This study aims to identify the core symptoms of IA among depressed adolescents using a cross-lagged panel network framework, offering a fresh perspective on understanding the interconnectedness of IA symptoms.

METHODS

Participants completed the Internet addiction test and the Patient Health Questionnaire-9. A total of 2415 students were initially included, and after matching, only 342 students (a cutoff score of 8) were retained for the final data analysis. A cross-lagged panel network analysis was conducted to examine the autoregressive and cross-lagged trajectories of IA symptoms over time.

RESULTS

The incidence rate of depression rose remarkably from 14.16% (N = 342) to 17.64% (N = 426) after the four-month online learning. The symptom of "Anticipation" exhibited the highest out-expected influence within the IA network, followed by "Stay online longer" and "Job performance or productivity suffer". Regarding the symptom network of depression, "Job performance or productivity suffer" had the highest in-expected influence, followed by "Life boring and empty", "Snap or act annoyed if bothered", "Check email/SNS before doing things", and "School grades suffer". No significant differences were found in global network strength and network structure between waves 1 and 2.

CONCLUSION

These findings prove the negative effects of online learning on secondary students' mental health and have important implications for developing more effective interventions and policies to mitigate IA levels among depressed adolescents undergoing online learning.

Network connectivity between anxiety, depressive symptoms and psychological capital in Chinese university students during the COVID-19 campus closure

BACKGROUND

In the context of the outbreak of COVID-19 within mainland China, to understand the mental health status of university students during campus closure, this study analyzes the relationship between anxiety, depressive symptoms, and psychological capital and to reveals their central symptoms.

METHODS

A total of 12,945 university students were included in this study from April 10 to 19, 2022. Anxiety and depressive symptoms were measured by the seven-item Generalized Anxiety Disorder Scale (GAD-7) and two-item Patient Health Questionnaires (PHQ-2). Psychological capital was measured using the Psychological Capital Questionnaire (PCQ-24). The centrality and bridge centrality indexes were used to identify central and bridge symptoms, respectively. Network Comparison Test (NCT) was also administered to check whether network traits differed by gender and place of residence.

RESULTS

The most influential node in this study was Trouble relaxing (GAD4), followed by Uncontrollable worry (GAD2) and Excessive worry (GAD3). The main bridging symptoms were Depressed mood (PHQ2), Psychological capital. There are no differences in the network structure of students by place of residence, while there are more significant differences in the network structure of students by gender.

CONCLUSION

Central and bridging symptoms may be the core symptoms that trigger or maintain the development of anxiety and depression among university students during the COVID-19 campus closure. Timely and reasonable interventions targeting these symptoms may help reduce depression and anxiety in this population. In addition, improving university students' psychological capital may likewise contribute to the development of their good mental health.

Symptom relationships between internet addiction and anxiety across primary and middle school students during the Omicron lockdown

During the Omicron pandemic, students in Shenzhen took classes at home via the internet, which could lead to internet addiction (IA) symptoms, and anxiety is often considered an important risk factor for IA. There are several different developmental stages within adolescence. However, no studies have explored the interaction between IA and anxiety at the symptom level using a longitudinal design stratified by age. A total of 2744 students completed the questionnaire 50 days after starting the online classes (T1) and 50 days after they returned to school (T2). A cross-lagged panel network model was used to describe the structure of the comorbidity network. With the help of bootstrapping, the Mann-Whitney U test was used to examine the differences between primary school students' and middle school students' networks. The results found that there is a bidirectional interaction between IA and anxiety, and anxiety plays a dominant role. Feeling afraid is the bridge symptom between IA and anxiety. IA did not show developmental stage differences, but anxiety did. These findings extend the model of compensatory internet use and suggest that, when alleviating IA symptoms in adolescents, attention should be given to their possible comorbid anxiety symptoms, especially in middle school students.

Six addiction components of problematic social media use in relation to depression, anxiety, and stress symptoms: a latent profile analysis and network analysis

BACKGROUNDS

Components of addiction (salience, tolerance, mood modification, relapse, withdrawal, and conflict) is the most cited theoretical framework for problematic social media use (PSMU). However, studies criticized its ability to distinguish problematic users from engaged users. We aimed to assess the association of the six criteria with depression, anxiety, and stress at a symptom level.

METHODS

Ten thousand six hundred sixty-eight participants were recruited. Bergen Social Media Addiction Scale (BSMAS) was used to detect six addiction components in PSMU. We applied the depression-anxiety-stress scale to assess mental distress. Latent profile analysis (LPA) was conducted based on BSMAS items. Network analysis (NA) was performed to determine the symptom-symptom interaction of PSMU and mental distress.

RESULTS

(1) Social media users were divided into five subgroups including occasional users (10.6%, n = 1127), regular users (31.0%, n = 3309), high engagement low risk users (10.4%, n = 1115), at-risk users (38.1%, n = 4070), and problematic users (9.8%, n = 1047); (2) PSMU and mental distress varied markedly across subgroups. Problematic users had the most severe PSMU, depression, anxiety, and stress symptoms. High engagement users scored high on tolerance and salience criteria of PSMU but displayed little mental distress; (3) NA showed conflict and mood modification was the bridge symptoms across the network, while salience and tolerance exhibited weak association with mental distress.

CONCLUSIONS

Salience and tolerance might not distinguish engaged users from problematic users. New frameworks and assessment tools focusing on the negative consequences of social media usage are needed.

Factors associated with test anxiety among adolescents in Shenzhen, China

BACKGROUND

Test anxiety is prevalent among adolescents and may have long-term negative consequences on their physical and mental health. The aim of this study was to assess the prevalence of test anxiety and its related attributing factors among adolescents in Shenzhen, China.

METHODS

A cross-sectional study was conducted from November 18, 2020 to January 12, 2021 in Shenzhen, China. Test anxiety symptoms were measured by using the Test Anxiety Scale. Descriptive statistics and multivariate logistic regression were used to assess test anxiety and risk factors.

RESULTS

In total, 7047 students aged 10 to 19 were included for this survey. The prevalence of test anxiety was found to be 46.7 %. In multivariate analysis, gender, age, frequency of feeling lonely, parents' marital status, family functioning, emotional abuse, physical abuse, sexual abuse, academic performance level, relationship with classmates, school bullying and Internet addiction were positive related to test anxiety.

LIMITATIONS

This cross-sectional design limits the establishment of causal relationships. Reporting bias and recalling bias may be possible.

CONCLUSIONS

Our study suggested that a significant number of adolescents in Shenzhen had test anxiety symptoms. Also, we found some risk factors, which might help to provide new guidance of psychological interventions to promote adolescents' mental health.

Anxiety predicts internet addiction, which predicts depression among male college students: A cross-lagged comparison by sex

Objectives

Internet addiction has become an increasingly serious public health issue, putting young people at particular risk of psychological harm. This study aimed to analyze the interactions between college students' depression, anxiety, and Internet addiction and explore how these interactions differ between men and women.

Methods

A 6-month follow-up study was conducted on 234 college students using the Self-Rating Depression Scale, Self-rating Anxiety Scale, and Revised Chen Internet Addiction Scale.

Results

Depression, anxiety, and Internet addiction were positively correlated (p < 0.01). Anxiety can predict Internet addiction and that Internet addiction can predict depression. Moreover, anxiety had a significant predictive effect on Internet addiction among men.

Conclusion

Anxiety predicts Internet addiction, and Internet addiction predicts depression among male college students. These findings may better inform future Internet addiction intervention strategies. Particularly, interventions may better address Internet addiction by focusing on the role of anxiety, especially among men.

The Relationship of Internet Abusive Use with Academic Burnout and Academic Performance in Nursing Students

Materials and Methods

A total of 184 nursing students were recruited by simple random sampling. Data collection tools included a demographic information form, the Internet Abusive Use Questionnaire and Maslach Burnout Inventory-Student Survey. Data were analyzed by the SPSS-18 software using descriptive and inferential statistics.

Results

The abusive use of the Internet in nursing students was lower than the average level. There was a positive correlation between Internet abusive use and academic burnout (r = 0.305, p < 0.001), but there was a negative correlation between Internet abusive use and academic performance (r = −0.478, p < 0.001). The results of multiple regression analysis showed that Internet abusive use could predict the variance of academic burnout and academic performance.

Conclusions

Internet abusive use was correlated with increased academic burnout and decreased academic performance in nursing students. Educational interventions are required to increase students' awareness of the consequences of Internet abusive use.

Internet Addiction and Its Associated Factors Among African High School and University Students: Systematic Review and Meta-Analysis

Introduction

Internet addiction is characterized by excessive and uncontrolled use of the internet affecting everyday life. Adolescents are the primary risk group for internet addiction. Data on internet addiction is lacking in Africa. Thus, this review aimed to determine the pooled prevalence of internet addiction and its associated factors among high school and university students in Africa.

Methods

A comprehensive literature search was conducted using electronic databases (PubMed/MEDLINE, Web of science, Hinari, and Google scholar) to locate potential studies. Heterogeneity between studies was checked using Cochrane Q test statistics and I2 test statistics and small-study effects were checked using Egger's statistical test at a 5% significance level. A sensitivity analysis was performed. A random-effects model was employed to estimate the pooled prevalence and associated factors of internet addiction among students. The primary outcome of measure of this review was the prevalence of internet addiction and the secondary outcome of measures are the factors associated with internet addiction.

Results

A total of 5,562 studies were identified among the five databases. Of these, 28 studies from 10 countries with 14,946 high school and university students were included in this review. The overall pooled prevalence of internet addiction among the students was 34.53% [95% Confidence Interval (CI): 26.83, 42.23, I2 = 99.20%]. Male sex [Pooled Odds Ratio (POR) = 1.92, 95% CI:1.43, 2.57 I2 = 0.00], urban residence (POR = 2.32, 95% CI:1.19, 4.53, I2 = 59.39%), and duration of daily internet use for more than 4 h (POR = 2.25, 95% CI:1.20, 4.21, I2 = 0.00%, were significantly associated with internet addiction among adolescents.

Conclusion

Almost one-third of university and high school students in Africa are addicted to the internet. Male students, those from urban areas, and those who use the internet for more than 4 h per day have higher odds of internet addiction. Thus, we recommend that health planners and policymakers pay attention to the use of the internet and internet addiction in Africa.

Network connectivity between benevolent childhood experiences and uncertainty stress among Chinese university students

BACKGROUND

The purpose of this study was to explore the association between benevolent childhood experiences (BCEs) and uncertainty stress among Chinese university students by network analysis.

METHODS

A total of 1,830 university students from three Chinese cities were recruited. Respondents' BCEs and uncertainty stress were self-reported using online questionnaire. The structure of the BCEs-uncertainty stress and related centrality indicators were examined for this sample.

RESULTS

The overall network model showed that "no ways to suit the important changes in life" was the most influential, followed by "all things are not going well," "feel that there is nothing to do," and "worry about the future." And in this network, the most influential bridge symptom was "having a positive self-concept."

CONCLUSION

The central symptoms of the BCEs-uncertainty stress network should be prioritized as targets in interventions and prevention efforts to reduce uncertainty stress among Chinese university students. Improving university students' positive self-concept is important to alleviate the level of uncertainty stress among Chinese university students.

The association between family relationships and depressive symptoms among pregnant women: A network analysis

BACKGROUND

Depression of pregnant women has been a growing concern in recent years, and previous research has found that family relationships are strongly associated with depression. From a network perspective, family relationships and depression can be conceptualized as the result of interactions between individual symptoms. This research approach can elucidate the structure and mechanisms of the relationship between individual symptoms within the two groups.

METHODS

A total of 990 participants were recruited from the obstetrics outpatient clinic of Maternal and Child Health Hospital in Huai'an through a randomized whole-group sampling. Respondents' depressive symptoms and family relationships were self-reported using questionnaire, and the structure of the family relationship-depressive symptoms network and related centrality indicators were examined for this sample.

RESULTS

The results of the network analysis suggested that the most influential symptoms in the network of family relationship-depressive symptoms were worry, feeling worthless, equal status with husband and couple relationship. And equal status with husband was the most prominent bridging symptoms in this study. The whole network was robust in both stability and accuracy tests.

LIMITATIONS

Information was obtained from subjects' self-reports, which may be subject to information bias. As a cross-sectional study, no causal link between family relationships and depressive symptoms can be established.

CONCLUSION

Worry, feeling worthless, equal status with husband and couple relationship are central symptoms of the family relationship-depressive symptoms network structure in pregnant women. Timely and systematic multilevel interventions targeting the central symptoms may be effective in alleviating the onset of depressive symptoms in women during this period.

Mapping network connectivity between internet addiction and residual depressive symptoms in patients with depression

BACKGROUND AND AIMS

Depression often triggers addictive behaviors such as Internet addiction. In this network analysis study, we assessed the association between Internet addiction and residual depressive symptoms in patients suffering from clinically stable recurrent depressive disorder (depression hereafter).

MATERIALS AND METHODS

In total, 1,267 depressed patients were included. Internet addiction and residual depressive symptoms were measured using the Internet Addiction Test (IAT) and the two-item Patient Health Questionnaire (PHQ-2), respectively. Central symptoms and bridge symptoms were identified via centrality indices. Network stability was examined using the case-dropping procedure.

RESULTS

The prevalence of IA within this sample was 27.2% (95% CI: 24.7-29.6%) based on the IAT cutoff of 50. IAT15 ("Preoccupation with the Internet"), IAT13 ("Snap or act annoyed if bothered without being online") and IAT2 ("Neglect chores to spend more time online") were the most central nodes in the network model. Additionally, bridge symptoms included the node PHQ1 ("Anhedonia"), followed by PHQ2 ("Sad mood") and IAT3 ("Prefer the excitement online to the time with others"). There was no gender difference in the network structure.

CONCLUSION

Both key central and bridge symptoms found in the network analysis could be potentially targeted in prevention and treatment for depressed patients with comorbid Internet addiction and residual depressive symptoms.