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Original Research

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

, , , , , , , & ORCID Icon show all
Pages 52-59 | Received 20 Nov 2021, Accepted 26 Mar 2022, Published online: 09 Apr 2022
 

Abstract

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.

    IMPLICATIONS FOR REHABILITATION

  • Patients do not receive adequate amounts of upper limb motor practice following a stroke, and although robotic devices have the potential to address this gap, clinical adoption is low.

  • The technology acceptance model identified that clinicians perceive robotic devices to be complex to use with current implementation efforts failing to consider their training needs.

  • Implementation adoption of robotic devices in rehabilitation should be supported with adequate training and technological support if sustainable practice change is to be achieved.

Disclosure statement

In accordance with Taylor & Francis policy and my ethical obligation as a researcher, I am reporting that JF, VC, YG and DO are co-inventors of the EMU rehabilitation device used in this study and have financial interests in commercialisation of the device by Fourier Intelligence (Shanghai, China).

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