Pathways from self-disclosure to medical coping strategy among adolescents with moderate and major depression during the COVID-19 pandemic: A mediation of self-efficacy

Background The prevalence of adolescent depression in China during the COVID-19 pandemic is increasing. Self-disclosing depressive emotions could help release stress. Self-disclosure, which is a prerequisite for self-efficacy, can directly contribute to people’s psychological health, and depression and the choice of coping strategy are determined by the level of self-efficacy perceived. Purpose We aimed to discuss the relationship between self-efficacy, self-disclosure, and medical coping strategy. Further, we explore the mediation effect of self-efficacy on the influence of self-disclosure on medical coping strategies in adolescents with depression. Methods A total of 585 patients aged 11–24 years with moderate and major depression were recruited. All the assessments were completed on the second day after admission, including the General Self-Efficacy Scale (GSE), Distress Disclosure Index (DDI), and Medical Coping Modes Questionnaire (MCMQ). Pearson correlation was performed to explore the relationships of these variables. The bootstrap analysis was used to conduct to assess the mediation effects. Results Both direct and indirect effects of self-disclosure on medical coping strategy were found. As predicted, self-efficacy partially mediated the relationship between self-disclosure and medical coping strategy (b = 0.0385, 95% CI: 0.0244–0.0538 for Confrontation;b = –0.0466, 95%CI: –0.0651 to –0.0296 for Resignation), respectively. The effect size for Confrontation and Resignation was 0.2659 and 0.2485, respectively. Conclusion Self-efficacy played a partial mediating role in the effect of self-disclosure on medical coping strategies for adolescent depression during the COVID-19 pandemic, and the use of a positive self-disclosure mechanism may be anticipated to promote improved self-efficacy and the use of active coping strategies.

Multi-chain Fudan-CCDC model for COVID-19-a revisit to Singapore's case.

BACKGROUND: COVID-19 has been impacting on the whole world critically and constantly since late December 2019. Rapidly increasing infections has raised intense worldwide attention. How to model the evolution of COVID-19 effectively and efficiently is of great significance for prevention and control. METHODS: We propose the multi-chain Fudan-CCDC model based on the original single-chain model in [Shao et al. 2020] to describe the evolution of COVID-19 in Singapore. Multi-chains can be considered as the superposition of several single chains with different characteristics. We identify the parameters of models by minimizing the penalty function. RESULTS: The numerical simulation results exhibit the multi-chain model performs well on data fitting. Though unsteady the increments are, they could still fall within the range of _30% fluctuation from simulation results. CONCLUSION: The multi-chain Fudan-CCDC model provides an effective way to early detect the appearance of imported infectors and super spreaders and forecast a second outbreak. It can also explain the data from those countries where the single-chain model shows deviation from the data.