I‐Chen Lee

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About

I-Chen Lee is a leading scholar in nursing workforce dynamics and healthcare technology integration, with a particular focus on how automation reshapes clinical environments. Her most-cited work, a two-wave study on how robots impact nurses’ time pressure and turnover intention (2022, 23 citations), reveals a critical paradox: while robots are intended to reduce workload, they often introduce new demands—termed “effort ensuring robots’ smooth operation” (EERSO)—that paradoxically heighten time pressure, missed care, and turnover intent. Lee’s research demonstrates that robot performance moderates these effects, showing that poorly functioning automation can exacerbate nurse burnout rather than alleviate it. This contribution is pivotal for healthcare administrators and technology designers, highlighting the need for human-centered robotic implementation. Her work bridges industrial-organizational psychology and nursing science, offering evidence-based strategies to sustain the nursing workforce amid rapid digitalization. Lee’s findings have informed policy discussions on technology adoption in hospitals and are widely cited in studies on healthcare worker well-being and human-robot interaction.