Abstract
Adoption of innovative solutions in healthcare remains a challenge and is a contributing factor to the barriers of their large scale uptake in both private and public healthcare settings. Traditionally, the study of technology adoption has been limited to considering the patient’s perspective, however, there is now an increasing appreciation that this should be expanded to consider adoption implications from a carer’s perspective in addition to healthcare professionals and indeed on a larger scale, from a healthcare service provider’s perspective. In this work we attempt to establish a proof of concept framework whereby technology adoption of innovative healthcare solutions can be built using generative AI. By considering established and validated clinical questionnaires for the purposes of assessing technology adoption for patients we have created a new suite of questionnaires that can be used for care givers. The approach was evaluated with a set of 28 patient focussed questions. All of the questions produced by the generative AI were deemed to be correct with an average Rouge-1 F1 score of 0.71.
This research has been partially funded by the ARC (Advanced Research and Engineering Centre) project, funded by PwC and Invest Northern Ireland and the AGAPE Project funded through the AAL-Active and Assisted Living Programme.
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Nugent, C. et al. (2023). Using Generative AI to Assist with Technology Adoption Assessment. In: Bravo, J., Urzáiz, G. (eds) Proceedings of the 15th International Conference on Ubiquitous Computing & Ambient Intelligence (UCAmI 2023). UCAmI 2023. Lecture Notes in Networks and Systems, vol 835. Springer, Cham. https://doi.org/10.1007/978-3-031-48306-6_20
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DOI: https://doi.org/10.1007/978-3-031-48306-6_20
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