Purpose: To examine the predictive capability of the demand-control-support (DCS) model, augmented by organizational justice variables, on attitudinal- and health-related outcomes for nurses caring for elderly patients. Design: The study is based on a cross-sectional survey design and involved 168 nurses working with elderly patients in facilities of a medium to large Australian organization. Method: Participants were asked to complete a questionnaire consisting of scales designed for measuring independent (e.g., demand, control, support, organizational justice) and dependent (e.g., job satisfaction, organizational commitment, wellbeing and psychological distress) variables. Multiple regression analyses were undertaken to identify significant predictors of the outcome variables. Findings: The DCS model explains the largest amount of variance across both the attitudinal and health outcomes with 27% of job satisfaction and 49% of organizational commitment, and 33% of psychological distress and 35% of wellbeing, respectively. Additional variance was explained by the justice variables for job satisfaction (5%), organizational commitment (4%), and psychological distress (23%). Conclusions: Using organizational justice variables to augment the DCS model was valuable in better understanding the work conditions experienced by nurses caring for elderly patients. Inclusion of curvilinear effects added clarity to the potentially artifactual nature of certain interaction variables. Clinical Relevance: The results indicated practical implications for managers of nurses caring for elderly patients in terms of developing and maintaining levels of job control, support, and fairness, as well as monitoring levels of job demands. The results particularly show the importance of nurses' immediate supervisors.