Background: Public participation in preventive efforts is crucial in preventing infection and reducing mortality attributed to infectious diseases. The health belief model (HBM) suggests that individuals will likely participate in these efforts when experiencing a personal threat or risk, but only if the benefits of acting outweigh the risk or perceived barriers. Methods: The current study explores the properties of the HBM as predictors of the public’s compliance with COVID-19 preventive behaviour. Quantitative data on HBM properties, COVID-19 preventive behaviour, socioeconomic (SES) and demographic characteristics were collected from a sample of 674 adults in Hamburg, Germany. Binary logistic regression was computed to examine the effect of the properties of HBM on COVID-19 vaccination. Multiple linear regression was calculated to investigate the impacts of HBM properties on the likelihood of participants’ face mask usage as a protective measure against COVID-19 infection. Results: The logistic regression model was statistically significant, X²(13) = 149.096, p < .001. The specificity and sensitivity for the model is 58.1% and 99.4%, respectively. Similarly, the multiple regression model results showed a good fit for the data. F (13, 650) = 17.093, p < .001, and adjusted R²= .240, suggesting that HBM properties predict face mask usage. Conclusion: This study’s findings provide robust evidence to recommend that the concerned public health professionals consider individuals’ health beliefs when designing an effective COVID-19 preventive programme. Public health messaging should consider highlighting the benefits of preventive actions and the potential lethality of COVID-19 to evoke an individual’s appropriate concern.

Objective: Mental health can be negatively affected if work and private life demands are not balanced. This study proposes exploring work-life balance (WLB) as a predictor of Generation Z's mental health outcomes. Methods: A cross-sectional online study was conducted to collect data on mental health outcomes and WLB from a sample of Generation Z (N = 134). Three regression models were calculated to examine the predictive effect of WLB on stress, anxiety, and depressive symptoms. Results: The results show a strong statistically significant association between all three mental health outcomes. The regression model suggests work-life balance as a predictor of stress (β =.−0.404 P = 0.001, R2 = 0.16) and anxiety (β = .−256 P = 0.001, R2 = 0.06). Conclusion: WLB must be considered a significant factor in mental health problems among Generation Z.

Despite the increasing interest in exploring microaggression in the humanitarian context, there remains uncertainty on its mechanism for affecting life outcomes. There is a lack of studies on ethnic and racial minorities in non-western countries. The current research explores dimensions and manifestations of microaggression and how they affect wellbeing in a multicultural setting. The study uses a qualitative approach with 15 focus group discussions (FGDs) and 66 participants conducted in 4 provinces of South Africa: Gauteng (k = 6), North-West (k = 3), KwaZulu-Natal (k = 3), and Western Cape (k = 3). The recorded FGDs were transcribed using the intelligent verbatim technique. The transcripts were then analysed using a phenomenological approach. Data analysis was done stepwise using the deductive coding technique. Results show that participants’ perception of the dimensions of microaggression varies depending on the manifestation as verbal, behavioural, or systemic. Furthermore, variations in patterns and reactions to dimensions of microaggression were linked with participants’ racial identity. It further confirms that experiencing discrimination is associated with poorer wellbeing. Connectedness to the ingroup provides stability and certainty in multi-group societies due to the group rivalry that pervades such societies.

Understanding socioeconomic status (SES) and social capital as predictors of life outcomes has remained central to humanitarian, health and social research. This current study explores how socioeconomic status and social capital (community solidarity, locus of control and generalised trust) predict happiness among a sample of South African adults. Possible gender differences were also considered. Cross-sectional data from (n = 1049) South Africans on SES, social capital, happiness and sociodemographic characteristics were collected using an online questionnaire between January 2021 and September 2021. A correlation matrix was calculated to explore bivariate associations between the variables. Hierarchical regression analysis was conducted to examine the predictive influence of SES and social capital indices on happiness and the gender differential in these relationships. SES and all social capital variables were significantly correlated with happiness. The model, including SES and social capital, accounted for 25% of the variance in happiness. Gender differences were found regarding the relationship between SES and all social capital variables (except locus of control) and happiness. The results confirm that efforts to facilitate individual social capital correspond to greater happiness among South Africans. Furthermore, it highlights the need for further empirical exploration of social predictors of life outcomes. The current analysis provides a framework for developing and implementing policies that promote happiness and other life outcomes.