The Relationship Between Nurse Autonomy and Job Satisfaction in Acute Care Environments

Posted: Oct 10, 2025

• Kenneth Diaz
• Kevin Butler
• Kimberly Bell

Abstract

This study investigates the complex relationship between nurse autonomy and job satisfaction in acute care environments through a novel computational modeling approach that combines agent-based simulation with organizational network analysis. Traditional research in this domain has relied primarily on survey-based methods and linear regression analyses, which often fail to capture the dynamic, multi-level interactions that characterize healthcare organizations. Our methodology introduces an innovative computational framework that models acute care units as complex adaptive systems, where nurses' autonomous decision-making, interprofessional collaboration, and organizational constraints interact in real-time. We developed a sophisticated simulation environment that incorporates 42 distinct autonomy dimensions across clinical, operational, and professional domains, tracking their impact on satisfaction metrics through emergent behavioral patterns. The model was validated using longitudinal data from three tertiary care hospitals, demonstrating unprecedented predictive accuracy for nurse retention outcomes. Our findings reveal several non-linear relationships previously undocumented in the literature, including threshold effects where autonomy beyond certain levels paradoxically decreases satisfaction due to increased cognitive load and accountability pressures. Additionally, we identified critical interaction effects between individual autonomy and team-level coordination patterns that significantly influence overall job satisfaction. This research contributes both methodologically through its computational approach and substantively by providing healthcare administrators with evidence-based strategies for optimizing autonomy structures to enhance nurse satisfaction and retention in high-pressure acute care settings.