Despite growing attention to the phenomenon of intensified job demand in the workplace, empirical research investigating the underlying behavioral mechanisms that link work intensification to workplace well-being is limited. In particular, a study on whether these behavioral mechanisms are dependent on certain type of individual difference is absent. Using data collected from 356 Chinese health care professionals, this study utilized a dual-path moderated mediation model to investigate the mediating role of job crafting behavior between work intensification and workplace well-being, and the moderating role of work addiction on this indirect path. The results demonstrated that although work intensification was negatively associated with workplace well-being, this effect was more likely to take place for non-workaholics. Specifically, compared with non-workaholics, workaholics were more prone to engage in job crafting behavior in terms of seeking resources and crafting towards strengths, and therefore less likely to have reduced well-being experience. Results are discussed in terms of their implications for research and practice.

Background: Lockdown policies were widely adopted during the coronavirus disease 2019 (COVID-19) pandemic to control the spread of the virus before vaccines became available. These policies had significant economic impacts and caused social disruptions. Early re-opening is preferable, but it introduces the risk of a resurgence of the epidemic. Although the World Health Organization has outlined criteria for re-opening, decisions on re-opening are mainly based on epidemiologic criteria. To date, the effectiveness of re-opening policies remains unclear. Methods: A system dynamics COVID-19 model, SEIHR(Q), was constructed by integrating infection prevention and control measures implemented in Wuhan into the classic SEIR epidemiological model and was validated with real-world data. The input data were obtained from official websites and the published literature. Results: The simulation results showed that track-and-trace measures had significant effects on the level of risk associated with re-opening. In the case of Wuhan, where comprehensive contact tracing was implemented, there would have been almost no risk associated with re-opening. With partial contact tracing, re-opening would have led to a minor second wave of the epidemic. However, if only limited contact tracing had been implemented, a more severe second outbreak of the epidemic would have occurred, overwhelming the available medical resources. If the ability to implement a track-trace-quarantine policy is fixed, the epidemiological criteria need to be further taken into account. The model simulation revealed different levels of risk associated with re-opening under different levels of track-and-trace ability and various epidemiological criteria. A matrix was developed to evaluate the effectiveness of the re-opening policies. Conclusions: The SEIHR(Q) model designed in this study can quantify the impact of various re-opening policies on the spread of COVID-19. Integrating epidemiologic criteria, the contact tracing policy, and medical resources, the model simulation predicts whether the re-opening policy is likely to lead to a further outbreak of the epidemic and provides evidence-based support for decisions regarding safe re-opening during an ongoing epidemic. Keyords: COVID-19; Risk of re-opening; Effectiveness of re-opening policies; IPC measures; SD modelling.