Robot use self-efficacy in healthcare work (RUSH): development and validation of a new measure
The aim of this study was to develop and validate a measure of robot use self-efficacy in healthcare work (RUSH) based on social cognitive theory and the theory of planned behavior. This article provides a briefing on technology-specific self-efficacy and discusses the development, validation, and implementation of an instrument that measures care workers’ self-efficacy in working with robots. The validity evaluation of the Finnish-language measure was based on representative survey samples gathered in 2016. The respondents included practical and registered nurses, homecare workers, and physiotherapists. A majority of the respondents were female. The full instrument consists of a set of six task-specific self-efficacy items concerning general views of technological skills, confidence in learning robot use, and confidence in guiding others in robot use. Three items were chosen for the shorter version of the measure. The face validity, construct validity, and reliability were established to validate the instruments. Both 3-item and 6-item measures were found to be highly consistent in structure. Respondents with high levels of RUSH also reported more general self-efficacy and interest in technology, on average. A very brief instrument of three items is convenient to include in repeated employee surveys.
KeywordsCare work Nurse Service robot Task-specific self-efficacy Technology
We thank Dr Teo Keipi from the University of Turku for refining the item translations.
Compliance with ethical standards
This research is part of the project Robots and the Future of Welfare Services (2015–2020), which is funded by the Academy of Finland’s Strategic Research Council.
The authors report no financial conflicts related to this study.
Conflict of interest
The authors report no conflicts of interest.
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