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Using the job demands-resources (JD-R) model as a theoretical framework, the purpose of this paper is to investigate how job demands and job resources affect older employees’ desired retirement age, through an energy-depletion and a motivational process. Furthermore, the importance of gain and loss cycles (i.e. recursive effects) for the desired retirement age was investigated.

A two wave full panel design with 2,897 older employees ( > 50) served to test the hypotheses. Confirmatory factor analysis and structural equation modeling were used to test the measurement and research model. Cross-lagged analyses tested the presence of gain and loss cycles.

Results from cross-lagged analyses based on two waves over a one-year period indicated the presence of both a gain and a loss cycle that affected the desired retirement age.

This is the first longitudinal study applying the JD-R model to a retirement context. Limitations relate to employing only two waves for establishing mediation, and using self-reports.

Because work conditions can create a cycle of motivation as well as a cycle of depletion, organizations should pay special attention to the job resources and demands of older workers. The findings can inspire organizations when developing active aging policies, and contribute to interventions aimed at maintaining older employees within the workforce until – or even beyond – their official retirement age in a motivated and healthy way.

This is the first longitudinal study applying the JD-R model to a retirement context and finding evidence for gain and loss cycles.

The purpose of this paper is to identify job characteristics that determine young employees' wellbeing, health, and performance, and to compare educational groups.

Using the job demands‐resources (JD‐R) model and 2‐wave longitudinal data (n=1,284), the paper compares employees with a lower educational level with employees with a high educational level.

Young employees with lower educational level reported fewer job resources (autonomy and social support), more physical demands, less dedication, more emotional exhaustion, and poorer health and performance compared with the highly educated group. Differences were also found between educational groups in the relationships in the JD‐R model, most notably a reciprocal association between dedication and performance, and between emotional exhaustion and performance in the group with lower levels of education.

The results support the main processes of the JD‐R model, supporting its generalizability. However, differences were found between educational groups, implying that the motivational and health impairment processes differ across educational levels.

HR consultants and career counselors may focus especially on increasing job resources and motivation for young employees with lower educational level. Performing well is also important for these young workers to become more dedicated and less exhausted.

It is important to recognize and intervene on unique characteristics of different educational groups with regard to wellbeing, health, and performance in order to maintain a healthy and productive young workforce.

For the first time, predictions of the JD‐R model are tested among young employees with different educational backgrounds.