Application of the extended technology acceptance model to explore clinician likelihood to use robotics in rehabilitation

Purpose Evidence suggests that patients with upper limb impairment following a stroke do not receive recommended amounts of motor practice. Robotics provide a potential solution to address this gap, but clinical adoption is low. The aim of this study was to utilize the technology acceptance model as a framework to identify factors influencing clinician adoption of robotic devices into practice. Materials and method Mixed methods including survey data and focus group discussions with allied health clinicians whose primary caseload was rehabilitation of the neurologically impaired upper limb. Surveys based on the technology acceptance measure were completed pre/post exposure to and use of a robotic device. Focus groups discussions based on the theory of planned behaviour were conducted at the conclusion of the study. Results A total of 34 rehabilitation clinicians completed the surveys with pre-implementation data indicating that rehabilitation clinicians perceive robotic devices as complex to use, which influenced intention to use such devices in practice. The focus groups found that lack of experience and time to learn influenced confidence to implement robotic devices into practice. Conclusion This study found that perceived usefulness and perceived ease of use of a robotic device in clinical rehabilitation can be improved through experience, training and embedded technological support. However, training and embedded support are not routinely offered, suggesting there is a discordance between current implementation and the learning needs of rehabilitation clinicians.

Automated summary

This study aimed to identify the factors influencing clinician adoption of robotic devices into practice by using the technology acceptance model as a framework. The results showed that rehabilitation clinicians perceived robotic devices as complex to use, which influenced their intention to use them. Lack of experience and time to learn also affected their confidence to implement robotic devices into practice. Therefore, improving perceived usefulness and ease of use through experience, training, and embedded technological support is necessary.