The current study investigates the mental health condition of Mainland Chinese in Canada and identifies the associated sociodemographic and COVID-19-related predictors. A sample of 471 Mainland Chinese aged 18 or older completed an online survey that collected information on demographics, experience, cognition, and behaviours related to the COVID-19 pandemic and mental health condition. Mental health condition was assessed with the Depression, Anxiety, and Stress Scale-21 (DASS-21) for the depression, anxiety, and stress levels of Mainland Chinese during the pandemic. Moderate to severe depression, anxiety, and stress levels were respectively reported by 11.30%, 10.83%, and 5.10% of respondents. Univariate analysis of variance models (ANOVAs) were conducted to assess mental health condition variance as stratified by independent sociodemographic- or COVID-19-related explanatory variables, to identify possible predictors to be entered into the subsequent regression models. The regression models identified age, income level, health status, and perceived discrimination as significant sociodemographic predictors (absolute value of βs = 1.19–7.11, ps < 0.05), whereas self-infection worry, attitude towards Canadian measures, information confusion, food/goods stocking, and room cleaning/sanitizing were identified as significant COVID-19-reltaed predictors (absolute value of βs = 1.33–3.45, ps < 0.05) for mental health outcomes. The results shed light on our understanding of the major factors associated with the mental health condition of Mainland Chinese in Canada during the COVID-19 pandemic.

This large, international dataset contains survey responses from N = 12,570 students from 100 universities in 35 countries, collected in 21 languages. We measured anxieties (statistics, mathematics, test, trait, social interaction, performance, creativity, intolerance of uncertainty, and fear of negative evaluation), self-efficacy, persistence, and the cognitive reflection test, and collected demographics, previous mathematics grades, self-reported and official statistics grades, and statistics module details. Data reuse potential is broad, including testing links between anxieties and statistics/mathematics education factors, and examining instruments’ psychometric properties across different languages and contexts. Data and metadata are stored on the Open Science Framework website [https://osf.io/mhg94/].

The current study aimed to identify demographic and COVID experience predictors for COVID-19 risk perception among Chinese residents in Canada. A final sample of 653 participants aged 18 and up completed an online survey in simplified Chinese during the peak of the first wave of COVID-19 (25 April–10 June 2020). After removing those with missing data on demographic covariates, as missing data cannot be imputed, 444 were included in the structural equation model, and COVID-19 risk perception was indexed by three outcome variables: self-infection risk perception (i.e., likelihood of personal infection of COVID-19); threat perception (i.e., whether the pandemic is a real threat); and future infection rate prediction (i.e., a latent variable for community, Ontario, Canada, and World infection rate predictions). Predictors included demographic (i.e., income, gender, education, age, household size, employment status, and life satisfaction) and COVID experience variables (i.e., personal connection with confirmed or suspected COVID-19 cases, self-isolation experience, perceived anti-Chinese discrimination, and confusion over COVID-19 information). In the structural equation model, we found increased risk perception for the following demographic and COVID experience predictors; women, relatively higher education, living alone, working in a medical field, lower in life satisfaction, having personal connection with confirmed or suspected COVID-19 cases, with perceived anti-Chinese discrimination, or showing high confusion over COVID-19 information.

The ability to adaptively cope with the challenges of stressful events such as the COVID-19 pandemic is crucial for healthy aging. One effective coping strategy is social coping in which social networks are tapped for support. However, our review of the current literature on older adults’ coping abilities reveals two shortcomings: (1) a lack of consideration of a specific context and (2) an inadequate amount of attention paid to the different types of social networks in the cognitive appraisal process. As coping is a process in which older adults undergo the cognitive appraisal process to identify appropriate coping strategies, the shortcomings result in an incomplete understanding of older adults’ coping efforts and impair the development of effective community and intervention programs to improve older adults’ well-being. To fill this gap, drawing on the Transactional Model of Stress and Coping and the Social Capital Theory, we conducted 22 interviews with older adults who experienced lockdown measures during COVID-19. Our in-depth qualitative analysis shows the different roles played by bonding and bridging social capital in the cognitive appraisal process and illustrates the influence of a specific context on cognitive appraisals and subsequent coping efforts. Our findings provide significant contributions to theories regarding coping and social capital, as well as practices and policies for improving the well-being of older adults.