This article presents results from a study of occupational stress in Australian university staff. The authors report data on psychological strain and job satisfaction from nearly 9,000 respondents at 17 universities. Academic staff were generally worse off than general staff, and staff in newer universities were worse off than those in older universities. At the aggregate level, selfreport measures of psychological well-being were highly correlated with objective measures of university well-being (investment income, student-staff ratios, and recent cuts in staffing levels and in government operating grants).

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A longitudinal test of the Job Demands-Resources (JD-R) model of work stress and engagement Demerouti et al., 2001) was conducted in a sample of Australian university academics (N = 296). The aim was to extend the JD-R model by (1) determining how well job demands (work pressure, academic workload) and job resources (procedural fairness, job autonomy) would predict psychological strain and organisational commitment over a three-year period, and (2) incorporating longitudinal tests of reversed causation. The results of SEM analyses showed that Time 1 resources directly predicted Time 2 strain and organisational commitment, but that Time 1 demands predicted Time 2 strain only indirectly via job resources. We did not find evidence for reversed causation. We discuss possible mediators of the relationships between working conditions and work stress outcomes, and the practical implications of the results.

Two unique stressors associated with human service work are emotional dissonance, particularly the need to hide negative emotions (emotion work), and client/customer‐related social stressors. The latter may involve disproportionate or ambiguous client/customer expectations and/or verbally aggressive customers. These stressors affect all human service workers, even though they may vary in the extent to which their work involves lasting relationships with clients/customers, and in the amount of training they have received to deal with client/customer‐related social stressors. For example, health professionals typically develop long‐lasting relationships with their clients whereas call centre workers may have only a single brief interaction. In accordance with contemporary theories of work stress (conservation of resources, effort‐reward imbalance, demand‐control‐support), we argue that social support and training designed to develop “role separation” are crucial resources needed to help human service workers cope with the unique stressors of their jobs.

PurposeThe central aim of this study is to incorporate two core personality factors (neuroticism and extroversion) in the job demands‐resources (JD‐R) model.Design/methodology/approachIt was hypothesized that neuroticism would be most strongly related to the health impairment process, and that extroversion would be most strongly related to the motivational process. The hypotheses were tested in a sample of 3,753 Australian academics, who filled out a questionnaire including job demands and resources, personality, health indicators, and commitment.FindingsResults were generally in line with predictions. Structural equation modeling analyses showed that job demands predicted health impairment, while job resources predicted organizational commitment. Also, neuroticism predicted health impairment, both directly and indirectly through its effect on job demands, while extroversion predicted organizational commitment, both directly and indirectly through its effect on job resources.Research limitations/implicationsThese findings demonstrate the capacity of the JD‐R model to integrate work environment and individual perspectives within a single model of occupational wellbeing.Practical implicationsThe study shows that working conditions are related to health and commitment, also after controlling for personality. This suggests that workplace interventions can be used to take care of employee wellbeing.Originality/valueThe paper contributes to the literature by integrating personality in the JD‐R model, and shows how an expanded model explains employee wellbeing.