Symptom network analysis of anxiety and depression in epilepsy

Gauld, Christophe; Bartolomei, Fabricē; Micoulaud‐Franchi, Jean‐Arthur; McGonigal, Aileen

doi:10.1016/j.seizure.2021.09.013

Cited by 13 publications

(11 citation statements)

References 25 publications

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“…In addition, we also found that GAD1 "Nervousness or anxiety", GAD4 "Trouble relaxing", and GAD3 "Worry too much" were also high in EI and were thus established as central symptoms. These ndings are partially consistent with prior studies that have shown that "Trouble relaxing" (or "Unable to relax") and "Excessive worry" (or "Too much worry") had high centrality indices for the populations studied [28,57,59,60,64]. However, GAD1 "Nervousness or anxiety" was not found to be a central symptom in prior studies.…”

Section: Discussionsupporting

confidence: 89%

“…However, GAD1 "Nervousness or anxiety" was not found to be a central symptom in prior studies. This inconsistency may be the result of the use of different study samples, e.g., older adults with DM in our study versus a psychiatric sample in Beard et al's study [57], patients with epilepsy in Gauld et al's study [28], and patients with both depression and an anxiety disorder in Kaiser et al's study [64]. The characteristics of older adults with DM differ from those of individuals with neurological or psychiatric disorders.…”

Section: Discussionmentioning

confidence: 75%

“…Prior studies have used network analysis to explore the comorbidity of anxiety and depression in different populations, such as epilepsy patients [27,28], the functionally impaired elderly [29], nursing students [30,31], people with MDD [32], and people with anxiety disorder [33,34]. One study based on network analysis examined diabetes distress and depressive and anxiety symptoms in middle-aged Canadians [35].…”

Section: Introductionmentioning

confidence: 99%

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Network analysis of depressive and anxiety symptoms in older Chinese adults with diabetes mellitus

Zhang,

Cui,

et al. 2023

Preprint

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Background: The move away from investigating mental disorders as whole using sum scores to the analysis of symptom-level interactions using network analysis has provided new insights into comorbidity.The current study explored the dynamic interactions between depressive and anxiety symptoms in older Chinese adults with diabetes mellitus (DM) and identified central and bridge symptoms in the depression-anxiety network to provide targets for prevention and intervention into depression and anxiety. Methods: This study used a cross-sectional design with data from the 2017–2018 wave of the Chinese Longitudinal Healthy Longevity Survey (CLHLS). A regularized partial correlation network for depression and anxiety was estimated based on self-reported scales completed by 1685 older adults with DM aged 65 years or older. Expected influence (EI) and bridge expected influence(BEI) indices were calculated for each symptom. Results: The prevalences of depression and anxiety in our sample were 52.9% and 12.8%, respectively. The comorbidity rate of depression and anxiety was 11.5%. The six edges with the strongest regularized partial correlations were between symptoms from the same disorder. “Feeling blue/depressed”, “Nervousness or anxiety”, “Uncontrollable worry”, “Trouble relaxing”, and “Worry too much” had the highest EI values. “Nervousness or anxiety” and “Everything was an effort” exhibited the highest BEI values. Conclusion: Central and bridge symptoms were highlighted in this study. Targeting these symptoms may be effective in preventing the comorbidity of depressive and anxiety symptoms and facilitate interventions in older Chinese adults with DM who are at risk for or suffer from depressive and anxiety symptoms.

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Section: Discussionsupporting

confidence: 89%

Section: Discussionmentioning

confidence: 75%

Section: Introductionmentioning

confidence: 99%

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Network analysis of depressive and anxiety symptoms in older Chinese adults with diabetes mellitus

Zhang,

Cui,

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…To date, several studies have examined the network structure of anxiety and depression in a joint framework in different populations, including patients with major depressive disorder ( 40 ), patients with anxiety disorders ( 41 , 42 ), epilepsy patients ( 43 , 44 ), and nursing students ( 45 , 46 ). However, the anxiety and depression symptom interactions of functionally impaired elderly individuals have not been researched via network analysis.…”

Section: Introductionmentioning

confidence: 99%

Network analysis of anxiety and depression in the functionally impaired elderly

Yang

Guo

Cao

et al. 2022

Front. Public Health

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BackgroundEvidence from previous studies has confirmed that functionally impaired elderly individuals are susceptible to comorbid anxiety and depression. Network theory holds that the comorbidity emerges from interactions between anxiety and depression symptoms. This study aimed to investigate the fine-grained relationships among anxiety and depression symptoms in the functionally impaired elderly and identify central and bridge symptoms to provide potential targets for intervention of these two comorbid disorders.MethodsA total of 325 functionally impaired elderly individuals from five communities in Xi'an, China, were recruited for our investigation. The GAD-7 and PHQ-9 were used to measure anxiety and depression, respectively. SPSS 22.0 software was used for descriptive statistics, and R 4.1.1 software was used for network model construction, expected influence (EI) evaluation and bridge expected influence (BEI) evaluation.ResultsIn the network, there were 35 edges (indicating partial correlations between symptoms) across the communities of anxiety and depression, among which the strongest edge was A1 “Nervousness or anxiety”-D2 “Depressed or sad mood.” A2 “Uncontrollable worry” and D2 “Depressed or sad mood” had the highest EI values in the network, while A6 “Irritable” and D7 “Concentration difficulties” had the highest BEI values of their respective community. In the flow network, the strongest direct edge of D9 “Thoughts of death” was with D6 “Feeling of worthlessness.”ConclusionComplex fine-grained relationships exist between anxiety and depression in functionally impaired elderly individuals. “Uncontrollable worry,” “depressed or sad mood,” “irritable” and “concentration difficulties” are identified as the potential targets for intervention of anxiety and depression. Our study emphasizes the necessity of suicide prevention for functionally impaired elderly individuals, and the symptom “feeling of worthlessness” can be used as an effective target.

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“…Prior studies have used network analysis to explore comorbid symptom networks of anxiety and depression in different populations, such as people with epilepsy ( 26 , 27 ), older people with functional impairment ( 28 ), nursing students ( 29 , 30 ), people with MDD ( 31 ), and people with anxiety disorders ( 32 , 33 ). However, the results of those studies have been inconsistent.…”

Section: Introductionmentioning

confidence: 99%

Network analysis of depressive and anxiety symptoms in older Chinese adults with diabetes mellitus

Zhang,

Cui,

et al. 2024

Front. Psychiatry

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BackgroundThe move away from investigating mental disorders as whole using sum scores to the analysis of symptom-level interactions using network analysis has provided new insights into comorbidities. The current study explored the dynamic interactions between depressive and anxiety symptoms in older Chinese adults with diabetes mellitus (DM) and identified central and bridge symptoms in the depression-anxiety network to provide potential targets for prevention and intervention for depression and anxiety.MethodsThis study used a cross-sectional design with data from the 2017–2018 wave of the Chinese Longitudinal Healthy Longevity Survey (CLHLS). A regularized partial correlation network for depressive and anxiety symptoms was estimated based on self-reported scales completed by 1685 older adults with DM aged 65 years or older. Depressive and anxiety symptoms were assessed using the 10-item Center for Epidemiologic Studies Depression Scale (CESD-10) and the Seven-Item Generalized Anxiety Disorder Scale (GAD-7), respectively. Expected influence (EI) and bridge expected influence (BEI) indices were calculated for each symptom.ResultsAccording to cutoff scores indicating the presence of depression and anxiety, the prevalences of depression and anxiety in our sample were 52.9% and 12.8%, respectively. The comorbidity rate of depression and anxiety was 11.5%. The six edges with the strongest regularized partial correlations were between symptoms from the same disorder. “Feeling blue/depressed”, “Nervousness or anxiety”, “Uncontrollable worry”, “Trouble relaxing”, and “Worry too much” had the highest EI values. “Nervousness or anxiety” and “Everything was an effort” exhibited the highest BEI values.ConclusionCentral and bridge symptoms were highlighted in this study. Targeting these symptoms may be effective in preventing the comorbidity of depressive and anxiety symptoms and facilitate interventions in older Chinese adults with DM who are at risk for or currently have depressive and anxiety symptoms.

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Symptom network analysis of anxiety and depression in epilepsy

Cited by 13 publications

References 25 publications

Network analysis of depressive and anxiety symptoms in older Chinese adults with diabetes mellitus

Network analysis of depressive and anxiety symptoms in older Chinese adults with diabetes mellitus

Network analysis of anxiety and depression in the functionally impaired elderly

Network analysis of depressive and anxiety symptoms in older Chinese adults with diabetes mellitus

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