The present study explores psychosocial needs among university employees and the extent to which these needs influence employee perceptions of how work positively or negatively affects their health. Structural equation modeling (SEM) analyses among Norwegian faculty members (N = 11,533) suggest that needs differ in importance to the two work-related health outcomes. Multi-group analyses suggest gender differences in the level of these needs and in their degree of relationship with positive/negative work-related health. Among women, the strongest predictors of positive and negative work-related health are work engagement and autonomy, respectively. Among men, the strongest predictors of positive and negative work-related health are meaning and social community, respectively. Although significant differences were found in the level of the psychosocial needs across different university groups (faculty, PhD students, administrative/technical staff), their predictive value for how work affects their health positively or negatively is basically equivalent across groups. Study findings raise two implications: (1) the mechanisms and characteristics of the work environment that promote versus detract from health in the university setting do not appear to be two sides of the same coin and suggest different sets of interventions for improving employee health, and (2) gender differences should be taken into account in designing interventions to improve health and well-being in universities.
COVID-19 continues to take a large toll on the mental health of the not working population, particularly of those who were unable to work. This study, using the Household Pulse Survey, estimated the association between reasons for not working and major depression and anxiety symptoms (MDAS). The lowest MDAS was reported by retirees. Individuals who were unable to work because of transportation problems, layoffs, COVID-19 concerns, and sickness or disability reported the highest MDAS. Mediation analysis showed that the direct and indirect effects of reasons for not working were much higher for those individuals who were unable to work than for individuals who were working or decided not to work.