Relations between anxiety sensitivity's cognitive concerns and anxiety severity: brooding and reflection as serial multiple mediators.

The outbreak of COVID-19 has caused a major impact on productivity and life functioning, and also led to adverse emotional reactions. In the face of this public health event, increased anxiety is one of the most common emotional reactions. Previous studies have shown that anxiety sensitivity, rumination and anxiety are closely related. Various dimensions of anxiety sensitivity have different effects on anxiety. Also, rumination can be divided into brooding and reflection. To explore the relationships among anxiety sensitivity's cognitive concerns, anxiety and different types of rumination, we conducted an online survey during the outbreak of coronavirus (February 17-25, 2020), using the Anxiety Sensitivity Scale-3 (ASI-3), Ruminative Responses Scale (RSS), and Depression Anxiety Stress Scale-21 (DASS-21). The results showed significant positive correlations among anxiety sensitivity's cognitive concerns, anxiety, brooding and reflection. Furthermore, brooding and reflection had a chain mediation effect between cognitive concerns and anxiety, and the mediation effect of reflection was even stronger. Results suggest that anxiety sensitivity's cognitive concerns may not only affect anxiety directly, but also affect anxiety through rumination, especially reflection.

Social Determinants of COVID-19 Vaccination Rates: A Time-Constrained Multiple Mediation Analysis.

Objective To estimate the multiple direct/indirect effects of social, environmental, and economic factors on COVID-19 vaccination rates (series complete) in the 3109 continental counties in the United States (U.S.). Study design  The dependent variable was the COVID-19 vaccination rates in the U.S. (April 15, 2022). Independent variables were collected from reliable secondary data sources, including the Census and CDC. Independent variables measured at two different time frames were utilized to predict vaccination rates. The number of vaccination sites in a given county was calculated using the geographic information system (GIS) packages as of April 9, 2022. The Internet Archive (Way Back Machine) was used to look up data for historical dates. Methods  A chain of temporally-constrained least absolute shrinkage and selection operator (LASSO) regressions was used to identify direct and indirect effects on vaccination rates. The first regression identified direct predictors of vaccination rates. Next, the direct predictors were set as response variables in subsequent regressions and regressed on variables that occurred before them. These regressions identified additional indirect predictors of vaccination. Finally, both direct and indirect variables were included in a network model. Results  Fifteen variables directly predicted vaccination rates and explained 43% of the variation in vaccination rates in April 2022. In addition, 11 variables indirectly affected vaccination rates, and their influence on vaccination was mediated by direct factors. For example, children in poverty rate mediated the effect of (a) median household income, (b) children in single-parent homes, and (c) income inequality. For another example, median household income mediated the effect of (a) the percentage of residents under the age of 18, (b) the percentage of residents who are Asian, (c) home ownership, and (d) traffic volume in the prior year. Our findings describe not only the direct but also the indirect effect of variables. Conclusions  A diverse set of demographics, social determinants, public health status, and provider characteristics predicted vaccination rates. Vaccination rates change systematically and are affected by the demographic composition and social determinants of illness within the county. One of the merits of our study is that it shows how the direct predictors of vaccination rates could be mediators of the effects of other variables.

Nurse managers' burnout and organizational support: The serial mediating role of leadership and resilience.

AIMS: To investigate the relationship between organizational support and nurse managers' burnout and the serial multiple mediating effects of leadership and resilience. BACKGROUND: Nurse managers are at a high risk of burnout, especially during the COVID-19 pandemic. However, no research has been done to examine the associations between nurse managers' organizational support, leadership, resilience and burnout. METHODS: This cross-sectional study recruited 458 nurse managers from 13 tertiary public hospitals in Jiangsu, China. They completed the Survey of Perceived Organizational Support, the Clinical Leadership Survey, the Resilience Scale and the Maslach Burnout Inventor-Human Service Survey. The serial mediating effect of individual leadership and resilience was estimated using the structural equation modelling method via Mplus 7.0. RESULTS: There were direct and indirect effects of organizational support on burnout, controlling for work variables. Leadership and resilience serially mediate the association between organizational support and burnout (ß = -.051, 95% confidence interval: -0.093 to -0.020). CONCLUSIONS: Among nurse managers, organizational support may be sequentially associated with improved leadership first and then resilience, which in turn is related to decreased burnout. IMPLICATIONS FOR NURSING MANAGEMENT: We recommend that hospital administrators incorporate leadership, resilience and burnout assessment in the routine psychological screening of nurse managers and creatively apply the organizational interventions to decrease nurse managers' burnout.

Cross-direct effects in settings with two mediators.

When multiple mediators are present, there are additional effects that may be of interest beyond the well-known natural (NDE) and controlled direct effects (CDE). These effects cross the type of control on the mediators, setting one to a constant level and one to its natural level, which differs across subjects. We introduce five such estimands for the cross-CDE and -NDE when two mediators are measured. We consider both the scenario where one mediator is influenced by the other, referred to as sequential mediators, and the scenario where the mediators do not influence each other. Such estimands may be of interest in immunology, as we discuss in relation to measured immunological responses to SARS-CoV-2 vaccination. We provide identifying expressions for the estimands in observational settings where there is no residual confounding, and where intervention, outcome, and mediators are of arbitrary type. We further provide tight symbolic bounds for the estimands in randomized settings where there may be residual confounding of the outcome and mediator relationship and all measured variables are binary.

The relationship between family functioning and non-suicidal self-injury in adolescents: A structural equation modeling analysis.

BACKGROUND: Previous research has suggested that depressive symptoms, emotional competence, and posttraumatic stress symptoms (PTSS) may mediate the association between family functioning and non-suicidal self-injury (NSSI). Therefore, this study aimed to evaluate the mediation effects of depressive symptoms, emotional competence, and COVID-related PTSS on the relationship between family functioning and NSSI in adolescents. METHOD: A sample of 5854 adolescents was recruited from June 16 to July 8, 2020. The data for family functioning, depressive symptoms, emotional competence, COVID-related PTSS, and NSSI behavior of adolescents were collected via self-reported questionnaires. A structural equation model was constructed to examine the relationship, and a bootstrap analysis was conducted to evaluate the mediation effects. RESULTS: The reporting rate of adolescent NSSI was 30.2%. The poor family functioning was positively associated with adolescent NSSI (ß = 0.130, 95% CI = 0.093-0.182), which was mediated by depression with effect size of 0.231 (95% CI = 0.201-0.257). The pathway coefficients between emotional competence and NSSI, and depression, COVID-related PTSS and NSSI, though statistically significant were unlikely to be clinically meaning with values of 0.057 and 0.015. There was no mediating effect by COVID-related PTSS. The pathways initially constructed between family functioning and COVID-related PTSS, emotional capacity and COVID-related PTSS were not been verified. LIMITATIONS: It was unclear whether this mediational effect would be supported in a longitudinal design. The application and extension of this model toward other regions and countries, and different ages need to be further explored. CONCLUSION: The interventions of adolescent NSSI should focus on both the family level and individual levels. Improving family environment, screening depressive symptoms, enhancing emotional competence and lessening COVID-related PTSS may reduce NSSI.

Problematic Internet Usage and Self-Esteem in Chinese Undergraduate Students: The Mediation Effects of Individual Affect and Relationship Satisfaction.

The aim of this cross-sectional study was to examine the mediating effects of individual affect and relationship satisfaction on the relationship between self-esteem and Problematic Internet Use (PIU). Affect was measured using the Positive and Negative Affect Schedule (PANAS), relationship satisfaction was assessed using a positive and negative semantic dimension scale, self-esteem was measured using the Rosenberg Self-Esteem Scale, and PIU was measured using the Problematic Internet Use scale with a sample of 507 Chinese university students (Mage = 20.41 years, SD = 2.49). The relationships between the variables were tested using structural equation modelling with a multiple mediation model. The results revealed that negative affect and the negative semantic dimensions of relationship satisfaction mediated the relationship between self-esteem and PIU. The implications of the results and the study's theoretical contributions are discussed.