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

Cai, Hong; Bai, Wei; Yan, Yonghong; Zhang, Ling; Mi, Wen-Fang; Li, Yuchen; Liu, Huanzhong; Du, Xiangdong; Zeng, Zhen-Tao; Lu, Chang-Mou; Zhang, Lan; Feng, Ke-Xin; Ding, Yan-Hong; Yang, Juanjuan; Jackson, Todd; Cheung, Teris; An, Feng-Rong; Xiang, Yu‐Tao

doi:10.3389/fpsyt.2022.997593

Cited by 7 publications

(4 citation statements)

References 80 publications

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“…68 Compared to bridge symptoms with lower expected influence values, those with higher expected influence values were associated with a higher risk of contagion between different communities of symptoms. 69 Predictability of each node 70 and control of confounding effects in basic demographic data 71 , 72 in the network model were estimated using the R package “mgm”. The value of predictability is indicated as the linkage between its neighboring node.…”

Section: Methodsmentioning

confidence: 99%

“…84 In contrast, another study found that male gender was a risk factor for suicidal thoughts among the general population. 83 Therefore, to examine the inter-relationship between depressive symptoms and suicidality, it is important to minimize the confounding effects caused by basic demographic 72,85,86 the depressive symptoms and suicidality network models, with the structure indexes, were re-evaluated after controlling for age, marital status, gender, and education level (Supplemental Figure S2). Compared to the original network, the re-calculated network model did not find any significant structure change after controlling for the confounding variables (strength: r s = 0.77 [0.54; 0.95]).…”

Section: The Confounding Effects Of Basic Demographic Data On Depress...mentioning

confidence: 99%

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The Inter-Relationships Between Depressive Symptoms and Suicidality Among Macau Residents After the “Relatively Static Management” COVID-19 Strategy: A Perspective of Network Analysis

Lam,

Cai,

Chen

et al. 2024

NDT

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Background Suicidality is a global public health problem which has increased considerably during the coronavirus disease 2019 (COVID-19) pandemic. This study examined the inter-relationships between depressive symptoms and suicidality using network analysis among Macau residents after the “relatively static management” COVID-19 strategy. Methods An assessment of suicidal ideation (SI), suicide plan (SP), suicide attempt (SA) and depressive symptoms was conducted with the use of individual binary response items (yes/no) and Patient Health Questionnaire (PHQ-9). In the network analysis, central and bridge symptoms were identified in the network through “Expected Influence” and “Bridge Expected Influence”, and specific symptoms that were directly associated with suicidality were identified via the flow function. Network Comparison Tests (NCT) were conducted to examine the gender differences in network characteristics. Results The study sample included a total of 1008 Macau residents. The prevalence of depressive symptoms and suicidality were 62.50% (95% CI = 59.4–65.5%) and 8.9% (95% CI = 7.2–10.9%), respectively. A network analysis of the sample identified SI (“Suicidal ideation”) as the most central symptom, followed by SP (“Suicide plan”) and PHQ4 (“Fatigue”). SI (“Suicidal ideation”) and PHQ6 (“Guilt”) were bridge nodes connecting depressive symptoms and suicidality. A flow network revealed that the strongest connection was between S (“Suicidality”) and PHQ6 (“Guilt”), followed by S (“Suicidality”) and PHQ 7 (“Concentration”), and S (“Suicidality”) and PHQ3 (“Sleep”). Conclusion The findings indicated that reduction of specific depressive symptoms and suicidal thoughts may be relevant in decreasing suicidality among adults. Further, suicide assessment and prevention measures should address the central and bridge symptoms identified in this study.

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Section: Methodsmentioning

confidence: 99%

Section: The Confounding Effects Of Basic Demographic Data On Depress...mentioning

confidence: 99%

The Inter-Relationships Between Depressive Symptoms and Suicidality Among Macau Residents After the “Relatively Static Management” COVID-19 Strategy: A Perspective of Network Analysis

Lam,

Cai,

Chen

et al. 2024

NDT

Self Cite

View full text Add to dashboard Cite

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“…This offers essential potential targets for relevant intervention measures ( 17 ). In recent years, network analysis has garnered widespread attention and application across various domains of psychology, such as depression ( 18 ), anxiety ( 19 ), acute stress reactions ( 20 ), eating disorders symptoms ( 21 ), and more. Additionally, some items in the Chinese version of the D-RFS may not be suitable for their factor assignments ( 22 ), suggesting the possibility of a better structural model.…”

Section: Introductionmentioning

confidence: 99%

Fear of disease in patients with epilepsy – a network analysis

Yin,

Niu,

et al. 2024

Front. Neurol.

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BackgroundDisease-related fear among patients with epilepsy has significantly impacted their quality of life. The Disease-Related Fear Scale (D-RFS), comprising three dimensions, serves as a relatively well-established tool for assessing fear in these patients. However, certain problems potentially exist within the D-RFS’s attribution of items, and its internal structure is still unclear. To establish an appropriate dimensional structure and gain deeper comprehension of its internal structure—particularly its core variables—is vital for developing more effective interventions aimed at alleviating disease-related fear among patients with epilepsy.MethodsThis study employed a cross-sectional survey involving 609 patients with epilepsy. All participants underwent assessment using the Chinese version of the D-RFS. We used exploratory network analysis to discover a new structure and network analysis to investigate the interrelationships among fear symptom domains. In addition to the regularized partial correlation network, we also estimated the node and bridge centrality index to identify the importance of each item within the network. Finally, it was applied to analyze the differences in network analysis outcomes among epilepsy patients with different seizure frequencies.ResultsThe research findings indicate that nodes within the network of disease-related fear symptoms are interconnected, and there are no isolated nodes. Nodes within groups 3 and 4 present the strongest centrality. Additionally, a tight interconnection exists among fear symptoms within each group. Moreover, the frequency of epileptic episodes does not significantly impact the network structure.ConclusionIn this study, a new 5-dimension structure was constructed for D-RFS, and the fear of disease in patients with epilepsy has been conceptualized through a network perspective. The goal is to identify potential targets for relevant interventions and gain insights for future research.

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“…Internet addiction can have severe detrimental effects on an individual’s social and physical well-being ( 7 ), including an increased risk of depression and anxiety ( 8 , 9 ), problematic behaviors ( 6 ), poorer academic performance ( 10 ), and severe sleep disorders ( 11 ), and so on. As a result, researchers have investigated various internal and external factors that influence internet addiction and have aimed to uncover its psychological mechanisms in order to develop effective interventions ( 7 , 12–14 ).…”

Section: Introductionmentioning

confidence: 99%

The impact of internet adaptability on internet addiction: the serial mediation effect of meaning in life and anxiety

Wang,

Ma,

Han

et al. 2023

Front. Psychiatry

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IntroductionPrevious research has demonstrated the significant role of individual characteristics in adolescent Internet addiction. In line with this, our previous research has introduced the concept of “Internet adaptability” as a potential factor that enables individuals to effectively cope with the negative consequences of Internet use. However, further investigation is required to understand the impact of Internet adaptability on problematic Internet use, including Internet addiction, as well as its associated internal psychological factors. To address this research gap, the present study aims to examine the impact of Internet adaptability on internet addiction and explore the mediating roles of meaning in life and anxiety within this relationship.MethodsA questionnaire was used to survey 2,144 adolescents from high schools in central China to investigate internet adaptability, meaning in life, anxiety, and internet addiction.ResultsThe results revealed a significant negative correlation between Internet adaptability and adolescent internet addiction (r = −0.199, p < 0.01). Furthermore, our results indicated that Internet adaptability negatively predicts internet addiction (β = −0.086, p < 0.001). Additionally, mediation analyses revealed that both meaning in life (β = −0.060, p < 0.001) and anxiety (β = −0.032, p < 0.01) mediate the relationship between Internet adaptability and internet addiction. Moreover, a serial mediation effect involving meaning in life and anxiety was observed between Internet adaptability and internet addiction (β = −0.027, p < 0.001).ConclusionThese findings suggest that Internet adaptability plays an important role in alleviating individual internet addiction. Our results indicate that increasing individuals’ sense of meaning in life can help reduce anxiety, thereby potentially reducing internet addiction.

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

Cited by 7 publications

References 80 publications

The Inter-Relationships Between Depressive Symptoms and Suicidality Among Macau Residents After the “Relatively Static Management” COVID-19 Strategy: A Perspective of Network Analysis

The Inter-Relationships Between Depressive Symptoms and Suicidality Among Macau Residents After the “Relatively Static Management” COVID-19 Strategy: A Perspective of Network Analysis

Fear of disease in patients with epilepsy – a network analysis

The impact of internet adaptability on internet addiction: the serial mediation effect of meaning in life and anxiety

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