Perceived Usefulness of Robotic Technology for Patient Fall Prevention

摘要

BACKGROUND: Technology has the potential to prevent patient falls in healthcare settings and to reduce work-related injuries among healthcare providers. However, the usefulness and acceptability of each technology requires careful evaluation. Framed by the Technology Acceptance Model (TAM) and using the Adaptive Robotic Nursing Assistant (ARNA) to assist with patient ambulation, the present study examined the perceived usefulness of robots in patients' fall prevention with implications for preventing associated work-related injuries among healthcare providers. METHODS: = 38) and one external subject (not a nursing student) who played the role of the patient. Procedures included subjects ambulating a simulated patient in three ways: (a) following the practice of a nurse assisting a patient to walk with the patient wearing a gait belt; (b) an ARNA-assisted process with the gait belt attached to ARNA; (c) an ARNA-assisted process with a subject walking a patient wearing a harness that is attached to ARNA. Block randomization was used with the following experimental scenarios: Gait Belt (human with a gait belt), "ARNA + Gait Belt" (a robot with a gait belt), and "ARNA + Harness" (a robot with a harness). Descriptive statistics and a multiple regression model were used to analyze the data and compare the outcome described as the Perceived Usefulness (PU) of a robot for patient walking versus a human "nurse assistant" without a robot. The independent variables included the experimental conditions of "Gait Belt," "ARNA + Gait Belt," and "ARNA + Harness," the subject's age, race, and previous videogame playing experience. FINDINGS: -value >.05). DISCUSSION: Results demonstrated that using robot technology to assist in walking patients was perceived by subjects as more useful in preventing falls than the gait belt. Patient fall prevention also has implications for preventing associated work-related injuries among healthcare providers. IMPLICATIONS: Understanding the effects of a subject's perceptions can guide further development of assistive robots in patient care. Robotic engineers and interdisciplinary teams can design robots to accommodate worker characteristics and individual differences to improve worker safety and reduce work injuries.