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.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Taherdoost, H.: A review of technology acceptance and adoption models and theories. Procedia Manuf. 22, 960–967 (2018)
Dube, T., Van Eck, R., Zuva, T.: Review of technology adoption models and theories to measure readiness and acceptable use of technology in a business organization. J. Inf. Technol. Digit. World 02(04), 207–212 (2020)
Martins, A., Pinheiro, J., Farias, B., Jutai, J.: Psychosocial impact of assistive technologies for mobility and their implications for active ageing. Technologies 4(3), 28 (2016)
Chaurasia, P., et al.: Modelling mobile-based technology adoption among people with dementia. Pers. Ubiquitous Comput. 26(2), 365–384 (2022)
Kamal, M., Subriadi, A.P.: UTAUT model of mobile application: literature review. In: Proceedings - IEIT 2021 1st International Conference on Electrical and Information Technology, pp. 120–125 (2021)
Chen, K., Lou, V.W.Q.: Measuring senior technology acceptance: development of a Brief, 14-Item Scale. Innov. Aging 4(3), 1–12 (2020)
Liu, Y., Lu, X., Zhao, G., Li, C., Shi, J.: Adoption of mobile health services using the unified theory of acceptance and use of technology model: self-efficacy and privacy concerns. Front. Psychol. 13, 944976 (2022). https://doi.org/10.3389/fpsyg.2022.944976. PMID: 36033004; PMCID: PMC9403893
Rouidi, M., Elouadi, A.E., Hamdoune, A., Choujtani, K., Chati, A.: TAM-UTAUT and the acceptance of remote healthcare technologies by healthcare professionals: a systematic review. Inform. Med. Unlocked 32, 101008 (2022)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
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
Download citation
DOI: https://doi.org/10.1007/978-3-031-48306-6_20
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-48305-9
Online ISBN: 978-3-031-48306-6
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)