Background Comorbidity between depressive and anxiety disorders is common. From network perspective, mental disorders arise from direct interactions between symptoms and comorbidity is due to direct interactions between depression and anxiety symptoms. The current study investigates the network structure of depression and anxiety symptoms in Chinese female nursing students and identifies the central and bridge symptoms as well as how other symptoms in present network are related to depression symptom “thoughts of death”. Methods To understand the full spectrum of depression and anxiety, we recruited 776 Chinese female nursing students with symptoms of depression and anxiety that span the full range of normal to abnormal. Depression symptoms were measured by Patient Health Questionnaire-9 while anxiety symptoms were measured by Generalized Anxiety Disorder 7-Item Questionnaire. Network analysis was used to construct networks. Specifically, we computed the predictability, expected influence and bridge expected influence for each symptom and showed a flow network of “thoughts of death”. Results Nine strongest edges existed in network were from the same disorder. Four were between depression symptoms, like “sleep difficulties” and “fatigue”, and “anhedonia” and “fatigue”. Five were between anxiety symptoms, like “nervousness or anxiety” and “worry too much”, and “restlessness” and “afraid something will happen”. The symptom “fatigue”, “feeling of worthlessness” and “irritable” had the highest expected influence centrality. Results also revealed two bridge symptoms: “depressed or sad mood” and “irritable”. As to “thoughts of death”, the direct relations between it and “psychomotor agitation/retardation” and “feeling of worthlessness” were the strongest direct relations. Conclusions The current study highlighted critical central symptoms “fatigue”, “feeling of worthlessness” and “irritable” and critical bridge symptoms “depressed or sad mood” and “irritable”. Particularly, “psychomotor agitation/retardation” and “feeling of worthlessness” were identified as key priorities due to their strongest associations with suicide ideation. Implications for clinical prevention and intervention based on these symptoms are discussed.

Background Intolerance of uncertainty (IU) is considered as a specific risk factor in the development and maintenance of generalized anxiety disorder (GAD). Yet, researches have investigated the relations between IU and GAD (or worry) using total scores on self-report measures. This ignores that there are different components exist in IU and the heterogeneity of GAD symptoms. In the present study, we explored the relations among different components of IU and symptoms of GAD. Methods A dimensional approach which take individual differences into consideration in different components of IU along a full range of normal to abnormal symptom severity levels of GAD were used in this study. Components of IU were measured by 12-item Intolerance of Uncertainty Scale and symptoms of GAD were measured by Generalized Anxiety Disorder 7-Item Questionnaire. Regularized partial-correlation network was estimated using cross-sectional data from 624 university students. Results Four strongest edges are between components of IU, like “Unforeseen events upset me greatly” and “It frustrates me not having all the information I need”. Two strongest edges are between symptoms of GAD, like “Being so restless that it is hard to sit still” and “Feeling afraid as if something awful might happen”. Symptom “Worrying too much about different things” and component “It frustrates me not having all the information I need” have the highest expected influences in the present network. In the community of IU, component “It frustrates me not having all the information I need” has the highest bridge expected influence. And in the community of GAD, symptoms “Worrying too much about different things” and “Not being able to stop or control worrying” have the highest bridge expected influence. Conclusions This study reveals potential pathways between different components of IU and various symptoms of GAD. Understanding how putative risk factors such as different components of IU are related to symptoms of GAD may provide some references for related preventions and interventions, such as targeting component “It frustrates me not having all the information I need” may be more effective at reducing symptoms of GAD than targeting other components of IU.

Objective This study aimed to explore the relationship between systemic inflammation markers and clinical activity, respiratory failure, and prognosis in patients with myasthenia gravis (MG). Methods One hundred and seventeen MG patients and 120 controls were enrolled in this study. Differences in the four immune‐related markers of two groups based on blood cell counts: neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), lymphocyte to monocyte ratio (LMR), and systemic immune‐inflammation index (SII) were measured. The stability of the associations between systemic inflammation markers and respiratory failure in MG patients was confirmed by adjusted logistic regression analysis. Moreover, Kaplan–Meier curve and multivariate COX regression models were applied to assess the factors affecting the outcome of MG. Results NLR, PLR, and SII were higher in MG patients than those in controls and were positively associated with MGFA classification, but not LMR. Adjusted logistic regression analysis showed that PLR was an independent predictor of MG with respiratory failure. The ROC curve demonstrated that PLR showed good sensitivity and specificity for the diagnosis of MG with respiratory failure. Kaplan–Meier curve showed that GMG, positive AchR‐Ab, respiratory failure, high NLR, PLR, SII, and IVIg exposure correlated with the risk for poor outcomes in MG patients. The multivariate COX regression models indicated that GMG and high SII was a risk factor for poor outcome of MG. Interpretation The systemic inflammation markers expressed abnormally in MG patients, in which PLR may be an independent predictor of respiratory failure, and high SII and GMG were predictive risk factors for poor outcomes in MG patients.

BackgroundAlthough poor mental well-being (MW) has been documented among individuals experiencing burnout during the coronavirus-19 (COVID-19) pandemic, little is known about the complex interrelationship between different components of MW and burnout. This study investigates this relationship among medical staff during the COVID-19 pandemic through network analysis.MethodsA total of 420 medical staff were recruited for this study. Components of MW were measured by the 14-item Warwick-Edinburgh Mental Well-being Scale (WEMWBS), and components of burnout were measured by a 15-item Maslach Burnout Inventory-General Survey (MBI-GS) Questionnaire. Network structure was constructed via network analysis. Bridge variables were identified via the bridge centrality index.ResultsThe edges across two communities (i.e., MW community and burnout community) are almost negative, such as edge MW2 (“Useful”) – B14 (“Worthwhile”) and edge MW1 (“Optimistic about future”) – B13 (“Happy”). The edges within each community are nearly positive. In the MW community, components MW1 (“Optimistic about future”) and MW6 (“Dealing with problems”) have the lowest bridge centrality. And in the community of burnout, components B13 (“Happy”) and B14 (“Worthwhile”) have the lowest bridge expected influence.ConclusionWe present the first study to apply the network approach to model the potential pathways between distinct components of MW and burnout. Our findings suggest that promoting optimistic attitudes and problem-solving skills may help reduce burnout among medical staff during the pandemic.

No abstract

Previous research has shown that meaning in life is closely related to well-being, a relationship that has been receiving increasing scholarly attention. We explored the mechanism by which people with a high level of meaning in life show enhanced subjective well-being, with a focus on the mediating role of self-efficacy in this link. Participants in this study were 245 undergraduates at three Chinese universities. Data were collected by using the Satisfaction with Life Scale, the Generalized Self-Efficacy Scale, the Positive and Negative Affect Schedule, and the Meaning in Life Questionnaire. Structural equation modeling results show that self-efficacy partially mediated the relationship between meaning in life and subjective well-being. Moreover, the results of a bootstrapping analysis show there were both indirect and direct significant links between meaning in life and subjective well-being through self-efficacy. These findings are useful for those working in public health services to enhance the subjective well-being of individuals by addressing their sense of meaninglessness in life and inspiring confidence.

No abstract

No abstract