The Association of Abuse and Depression With Suicidal Ideation in Chinese Adolescents: A Network Analysis

Li, Kuiliang; Zhan, Xiaowei; Ren, Lei; Liu, Nan; Zhang, Lei; Li, Ling; Chen, Ting; Feng, Zhanchun; Luo, Xi

doi:10.3389/fpsyt.2022.853951

Cited by 11 publications

(8 citation statements)

References 76 publications

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“…Previous studies (Li et al, 2022) utilized an extended Bayesian information criterion (EBIC) graphical least absolute shrinkage and selection operator (LASSO) model (Epskamp et al, 2018) to estimate the network. In this network, each node represents a unique symptom, with edges indicating the correlation between pairs of symptoms.…”

Section: Methodsmentioning

confidence: 99%

“…Network analysis has more practical utility in psychotherapy, because this approach can locate core symptoms (Marchetti, 2019) and highlight how symptom clusters are connected (Garabiles et al, 2019), which helps us grasp the detailed symptom structure (van Bork et al, 2021). The network approach has been used in several studies to examine the connection between anxiety‐depression symptoms (Sánchez Hernández et al, 2021; Tao, Hou, Niu, et al, 2023) and suicidal ideation (Li et al, 2022). According to a network analysis of depression and anxiety, “sad mood” was the core symptom and was related significantly to suicidal ideation in a psychiatric sample (Beard et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

“…As people become more aware of COVID‐19 pandemic and governments' prevention policies change, the psychological impact on people will also change accordingly. Second, these studies may not distinguish the symptom network between the groups with and without suicidal ideation (Beard et al, 2016; Cai et al, 2022; Li et al, 2022). Although suicidal ideation is closely related to depression and anxiety, not all individuals with depression and anxiety symptoms have suicidal ideation (Oquendo & Baca‐Garcia, 2014).…”

Section: Introductionmentioning

confidence: 99%

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Centrality depression–anxiety symptoms linked to suicidal ideation among depressed college students––A network approach

et al. 2023

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The long‐term effects of the COVID‐19 pandemic have caused severe mental health problems among college students, which can eventually cause suicidal ideation. Therefore, through network analysis, this study aims to explore the new characteristics of the depression–anxiety symptom network that arose during the long‐term lockdown of the COVID‐19 pandemic and to identify the most influential symptoms linked to suicidal ideation. We used a Patient Health Questionnaire (PHQ‐9) score above 10 as the cutoff and screened 622 participants with an inclination toward depressive disorders from 7976 college students, and then divided the sample into suicidal and nonsuicidal groups based on the presence or absence of suicidal ideation. The General Anxiety Disorder scale (GAD‐7) was also used. Network analysis was used to identify the network structure of anxiety–depression and which symptoms were directly related to suicidal ideation in the network. The prevalence of depression and anxiety among Chinese college students in the late stage of the COVID‐19 pandemic was 7.8% and 17.8%, respectively. The most central symptoms in the nonsuicidal group were “excessive worry,” “uncontrollable worry,” and “nervousness,” and in the suicidal group they were “excessive worry,” “motor function,” and “irritability.” The network of the suicidal group was denser than that of the nonsuicidal group. The most influential symptom directly related to suicidal ideation was “guilt.” The most influential central symptom of depression–anxiety comorbidity characteristics of Chinese adolescents showed a tendency to shift from depression‐oriented (i.e., sad mood) to anxiety‐oriented (i.e., excessive worry) with the continuation of the COVID‐19 pandemic. Treatments or interventions focused on these critical symptoms could be useful in preventing college students from suicide risk.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Centrality depression–anxiety symptoms linked to suicidal ideation among depressed college students––A network approach

et al. 2023

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“…Specifically, depression is a heterogeneous syndrome consisting of various symptoms (e.g., fatigue, sad mood, and appetite changes), which differ from each other in important domains [e.g., predisposing factors, (13, 14)]. Individual depression symptoms have shown different connections with insomnia (15), internet addictions (16), traumatic stress (17), abuse (18), negative life events (19), and emotion regulation difficulties (20,21). Similarly, the heterogeneity of components that constitute IU has been observed in previous studies (22,23).…”

Section: Introductionmentioning

confidence: 99%

The relations between different components of intolerance of uncertainty and symptoms of depression during the COVID-19 pandemic: A network analysis

et al. 2022

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BackgroundThe relations between depression and intolerance of uncertainty (IU) have been extensively investigated during the COVID-19 pandemic. However, there is a lack of understanding on how each component of IU may differentially affect depression symptoms and vice versa. The current study used a network approach to reveal the component-to-symptom interplay between IU and depression and identify intervention targets for depression during the COVID-19 pandemic.MethodsA total of 624 college students participated in the current study. An IU-Depression network was estimated using items from the 12-item Intolerance of Uncertainty Scale and the Patient Health Questionnaire-9. We examined the network structure, node centrality, and node bridge centrality to identify component-to-symptom pathways, central nodes, and bridge nodes within the IU-Depression network.ResultsSeveral distinct pathways (e.g., “Frustration when facing uncertainty” and “Feelings of worthlessness”) emerged between IU and Depression. “Fatigue” and “Frustration when facing uncertainty” were identified as the central nodes in the estimated network. “Frustration when facing uncertainty,” “Psychomotor agitation/retardation,” and “Depressed or sad mood” were identified as bridging nodes between the IU and Depression communities.ConclusionBy delineating specific pathways between IU and depression and highlighting the influential role of “Frustration when facing uncertainty” in maintaining the IU-Depression co-occurrence, current findings may inform targeted prevention and interventions for depression during the COVID-19 pandemic.

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“…Depression is a heterogeneous syndrome characterized by various cognitive, affective, and somatic symptoms (16). Emerging studies have demonstrated that predisposing variables are related differently to co-occurring symptoms (17)(18)(19)(20). Thus, it is plausible to assume that different dimensions of empathy may have unique symptom pathways to co-occurring symptoms of depression.…”

Section: Introductionmentioning

confidence: 99%

The relationship between dimensions of empathy and symptoms of depression among university students during the COVID-19 pandemic: A network analysis

Liu

Wulandari

et al. 2022

Front. Public Health

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BackgroundThe relationship between different dimensions of empathy and individual symptoms of depression during the COVID-19 pandemic remains unclear, despite the established link between empathy and depression. The network analysis offers a novel framework for visualizing the association between empathy and depression as a complex system consisting of interacting nodes. In this study, we investigated the nuanced associations between different dimensions of empathy and individual symptoms of depression using a network model during the pandemic.Methods1,177 students completed the Chinese version of the Interpersonal Reactivity Index (IRI), measuring dimensions of empathy, and the Chinese version of the Patient Health Questionnaire-9 (PHQ-9), measuring symptoms of depression. First, we investigated the nuanced associations between different dimensions of empathy and individual depressive symptoms. Then, we calculated the bridge expected influence to examine how different dimensions of empathy may activate or deactivate the symptoms of depression cluster. Finally, we conducted a network comparison test to explore whether network characteristics such as empathy-depression edges and bridge nodes differed between genders.ResultsFirst, our findings showed that personal distress was positively linked to symptoms of depression. These symptoms involved psychomotor agitation or retardation (edge weight = 0.18), sad mood (edge weight = 0.12), trouble with concentrating (edge weight = 0.11), and guilt (edge weight = 0.10). Perspective-taking was found to be negatively correlated with trouble with concentrating (edge weight = −0.11). Empathic concern was negatively associated with suicidal thoughts (edge weight = −0.10) and psychomotor agitation or retardation (edge weight = −0.08). Fantasy was not connected with any symptoms of depression. Second, personal distress and empathic concern were the most positive and negative influential nodes that bridged empathy and depression (values of bridge expected influence were 0.51 and −0.19 and values of predictability were 0.24 and 0.24, respectively). The estimates of the bridge expected influence on the nodes were adequately stable (correlation stability coefficient = 0.75). Finally, no sex differences in the studied network characteristics were observed.ConclusionsThis study applied network analysis to reveal potential pathways between different dimensions of empathy and individual symptoms of depression. The findings supported the existing theoretical system and contribute to the theoretical mechanism. We have also made efforts to suggest interventions and preventions based on personal distress and empathic concern, the two most important dimensions of empathy for depressive symptoms. These efforts may help Chinese university students to adopt better practical methods to overcome symptoms of depression during the COVID-19 pandemic.

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The Association of Abuse and Depression With Suicidal Ideation in Chinese Adolescents: A Network Analysis

Cited by 11 publications

References 76 publications

Centrality depression–anxiety symptoms linked to suicidal ideation among depressed college students––A network approach

Centrality depression–anxiety symptoms linked to suicidal ideation among depressed college students––A network approach

The relations between different components of intolerance of uncertainty and symptoms of depression during the COVID-19 pandemic: A network analysis

The relationship between dimensions of empathy and symptoms of depression among university students during the COVID-19 pandemic: A network analysis

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