The relations between emotion regulation, depression and anxiety among medical staff during the late stage of COVID-19 pandemic: a network analysis

Liang, Shuyi; Liu, Chang; Rotaru, Kristian; Li, Kuiliang; Wei, Xinyi; Yuan, Shangqing; Yang, Qun; Ren, Lei; Liu, Xufeng

doi:10.1016/j.psychres.2022.114863

Cited by 42 publications

(24 citation statements)

References 55 publications

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“…In the present study, we addressed this gap by showing specific associations between dimensions of empathy and symptoms of depression via network analysis. The findings add to the literature by showing that the related protective and risk factors differed considerably for symptoms of depression (49)(50)(51)(52)(53)(54)(55). Further, we calculated the bridge expected influence to detect influential nodes connecting dimensions of empathy and symptoms of depression.…”

Section: Discussionsupporting

confidence: 54%

“…Fourth, non-probability sampling strategies were used in this study; probability sampling strategies are recommended in the future to yield an unbiased sample representative of the target population. Fifth, like other existing studies that examine how external field factors may act directly upon symptom networks (e.g., emotion regulation and intolerance of uncertainty) ( 17 , 23 , 26 , 52 , 53 ), we focused on one particular construct of the external field (i.e., empathy). Future research could add potential covariates (e.g., age, exercise, smoking, and chronic diseases) ( 50 ) into the model to further improve its validity.…”

Section: Discussionmentioning

confidence: 99%

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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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Section: Discussionsupporting

confidence: 54%

Section: Discussionmentioning

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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Section: Introductionmentioning

confidence: 99%

“…Network analysis can be adopted to detect the symptomto-symptom relationships, and the network model is useful to assess the importance of each symptom in a disorder (12)(13)(14). Currently, it is widely used to study the association between depression and anxiety in different populations during COVID-19 epidemic (13)(14)(15)(16)(17). As far as we know, few studies have adopted network analysis to explore the relationship between depression and anxiety symptoms in COVID-19 patients, especially when the number of asymptomatic patients is increased.…”

Section: Introductionmentioning

confidence: 99%

Adjusting intervention strategies for mental health of COVID-19 patients: A network analysis based on a survey in Omicron-infected patients

Luo

Zhan

et al. 2022

Front. Public Health

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BackgroundThe COVID-19 pandemic had a major impact on people's mental health. As the SAS-Cov-2 evolves to become less virulent, the number of asymptomatic patients increases. It remains unclear if the mild symptoms are associated with mild perceived stress and mental illness, and the interventions to improve the mental health of the patients are rarely reported.MethodsThis cross-sectional study investigated the level of depression, anxiety and perceived stress of 1,305 COVID-19 patients who received treatment in the Fangcang shelter hospitals in Shanghai, China. Network analysis was used to explore the relationship among depression, anxiety and perceived stress.ResultsThe prevalence of depression, anxiety and perceived stress in the patients with Omicron infection were 9.03, 4.60, and 17.03%, respectively, lower than the prevalence reported during the initial outbreak of COVID-19. “Restlessness (A5),” “Uncontrollable worry (A2),” “Trouble relaxing (A4)” and “Fatigue (D4)” had the highest expected influence values. “Irritability (A6)” and “Uncontrollable (S1)” were bridge symptoms in the network. Comparative analysis of the network identified differences in the network structures between symptomatic and asymptomatic patients.ConclusionThis study investigated the prevalence of depression, anxiety and perceived stress and the correlation among them in Omicron-infected patients in Fangcang shelter hospital, in Shanghai, China. The core symptoms identified in the study provide insight into targeted clinical prevention and intervention of mental health in non-severe Omicron-infected patients.

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“…As a regulation strategy focusing on antecedents, cognitive reappraisal is often an effort to regulate emotional experiences before they arise and change one's perception of things (Koval et al, 2015;Lazarus & Alfert, 1964). As an adaptive emotion regulation strategy, cognitive reappraisal has been shown to offer protection against the development of psychopathologies (Brown et al, 2022;Liang et al, 2022;Su et al, 2022). Thus, when faced with stressors from PCOS, cognitive reappraisal may enable women with PCOS to reconstruct these situations in a way that successfully alters the emotional experience, increasing self-efficacy in stress reduction and stress relief as well as further reducing anxiety and depressive symptoms, body image distress, and further improving subjective well-being by reinterpreting emotional events.…”

Section: Discussionmentioning

confidence: 99%

Mental health latent profiles and emotion regulation in women with polycystic ovary syndrome: a cross-sectional study

Wang

Liu

Lei

2023

Preprint

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Introduction: Psychopathological disorders such as anxiety, depression and body image distress are common in women with PCOS and negatively impact their mental health. It is important to identify mental health latent subgroups of PCOS females and provide tailored measures to reduce psychopathological distress and improve their subjective well-being. Methods: LPA was conducted in Mplus version 8.3 to identify mental health latent profiles in women with PCOS based on the dual-factor approach. Differences in demographic and anthropometric variables, cognitive reappraisal, expressive suppression, and social support across mental health profiles were examined through multinomial logistic regression. Results: The current study identified three distinct mental health profiles within women with PCOS: Symptomatic but Content Profile Complete Mental Health Profile and Troubled Profile, with group proportions of 52.3%, 35.7%, and 11.1 %, respectively. The results of the multinomial regression analysis revealed that cognitive reappraisal and social support as predictors of positive mental health adjustment and expression suppression is an indicator of negative barriers in women with PCOS. Conclusion: This study identified three distinct mental health profiles in women with PCOS, which provides evidence for more precisely targeted interventions to address PCOS women’s diverse needs of psychopathological symptoms and subjective well-being.

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The relations between emotion regulation, depression and anxiety among medical staff during the late stage of COVID-19 pandemic: a network analysis

Cited by 42 publications

References 55 publications

The relationship between dimensions of empathy and symptoms of depression among university students 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

Adjusting intervention strategies for mental health of COVID-19 patients: A network analysis based on a survey in Omicron-infected patients

Mental health latent profiles and emotion regulation in women with polycystic ovary syndrome: a cross-sectional study

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