Intelligent robot-assisted care in critical care nursing: a concept analysis using Walker and Avant’s method

Abstract

Abstract Background Robotic applications in critical care vary in capability, purpose and clinical integration, making their nursing-specific meaning difficult to compare. This study aimed to clarify the meaning, defining attributes and practice boundaries of intelligent robot-assisted care in critical care nursing. Methods Walker and Avant’s concept analysis was informed by a structured search of nine English- and Chinese-language databases from inception to 3 June 2026, supplemented by reference searching. Identification and screening were presented in a PRISMA 2020-style flow diagram. Fourteen topic-related reports informed concept development; methodological, ethical and. background literature supported interpretation. Results Four complementary defining attributes were identified: an embodied robotic system; intelligent sensing and task execution; integration into critical care nursing practice; and clinician-governed augmentation of care. Antecedents encompassed clinical need, task suitability, system compatibility, trained clinicians, organisational support and pre-established safeguards. Reported findings included task feasibility, increased mobilisation dose and a functional improvement signal in a selected neurocritical-care population. Preparation and coordination demands remained, and patient and staffing effects varied across studies. Four attribute-linked empirical referent domains identify a specified application; patient, clinician, workflow, technical, safety, ethical and relational measures separately evaluate consequences and implementation quality. Conclusions Intelligent robot-assisted care in critical care nursing uses an embodied robotic system with intelligent sensing and task-execution capability to augment direct or indirect nursing activities in intensive care units or critical care-related settings under retained clinician authority. The definition distinguishes the practice from software-only AI, passive devices and applications lacking nursing-practice integration or clinician governance. It supports consistent identification, reporting and task-specific evaluation, with safety, ethical and relational safeguards guiding implementation.