Digital Fatigue, Cognitive Overload, and Interface Complexity in Electronic Health Record Systems: The Mediating Role of Technostress and the Moderating Role of Digital Health Literacy on Clinical Decision Agility
Keywords:
Clinical Decision Agility, Digital Fatigue, Digital Health Literacy, Electronic Health Record, Technostress, PLS-SEM.Abstract
Hospital adoption of Electronic Health Record (EHR) systems improves documentation, but it also exposes healthcare professionals to digital fatigue, information overload, and complex interfaces that may strain clinical work. Drawing on Cognitive Load Theory and the Job Demands–Resources model, this study examines whether digital fatigue, cognitive overload, and interface complexity are associated with healthcare professionals’ self-perceived clinical decision agility through technostress, and whether digital health literacy buffers these associations. A cross-sectional survey was conducted in hospitals that have implemented EHR systems. Using purposive sampling, data were obtained from 201 healthcare professionals (nurses, physicians, and other clinical staff) who actively use EHRs, and were analysed using PLS-SEM with bootstrapping and Importance-Performance Map Analysis (IPMA). Digital fatigue was strongly and positively associated with technostress, and technostress was negatively associated with clinical decision agility. Digital fatigue showed a significant negative indirect association with clinical decision agility through technostress (β = −0.824) but a significant positive direct association (β = 0.801), yielding a near-zero total effect (−0.023), a pattern consistent with inconsistent (competitive) mediation. Because technostress was almost entirely explained by the predictors (R² = 0.953), these opposing coefficients should be interpreted with caution. Cognitive overload and interface complexity were not significantly associated with technostress, and digital health literacy weakened only the digital fatigue–technostress association. The model explained very little variance in clinical decision agility (R² = 0.062; Q²predict = −0.050), indicating that most of its variation arises from factors outside the model. The findings identify technostress as a relevant correlate of perceived decision agility in EHR-intensive work and call for multi-site, longitudinal studies using objective decision outcomes.
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