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Technology Acceptance in Healthcare

Technology Acceptance in Healthcare
Technology Acceptance in Healthcare
Technology acceptance has traditionally been predicted on the basis of perceived ease-of-use and perceived usefulness: namely, characteristics of the technology. This may not be the case, though, for clinical interventions or healthcare apps. In this chapter, I report the findings of two empirical surveys to the general public and to members of the BigMedylitics (BML) consortium to establish what is important in healthcare apps specifically and in the integration of advanced, Artificial-Intelligence (AI) enabled technology. Whilst stakeholders like the BML consortium recognised that advanced technologies must be understood by all stakeholders and within a complex cultural and socio-technical ecosystem, the general public reported a willingness to engage with technology. The most influential factors affecting the acceptance of healthcare technologies include self-efficacy, disruptiveness, usability and trust. The results of the two surveys together suggest that users (patients) are sophisticated in how they use technology. They are therefore capable of having conversations about how advanced technologies should be developed and deployed along with other stakeholders in the complex ecosystem of healthcare.
Now Publishers Inc
Pickering, Brian
225088d0-729e-4f17-afe2-1ad1193ccae6
Pickering, Brian
225088d0-729e-4f17-afe2-1ad1193ccae6

Pickering, Brian (2023) Technology Acceptance in Healthcare. In, Handbook on Big Data for Healthcare - from theory to practice. Now Publishers Inc. (In Press)

Record type: Book Section

Abstract

Technology acceptance has traditionally been predicted on the basis of perceived ease-of-use and perceived usefulness: namely, characteristics of the technology. This may not be the case, though, for clinical interventions or healthcare apps. In this chapter, I report the findings of two empirical surveys to the general public and to members of the BigMedylitics (BML) consortium to establish what is important in healthcare apps specifically and in the integration of advanced, Artificial-Intelligence (AI) enabled technology. Whilst stakeholders like the BML consortium recognised that advanced technologies must be understood by all stakeholders and within a complex cultural and socio-technical ecosystem, the general public reported a willingness to engage with technology. The most influential factors affecting the acceptance of healthcare technologies include self-efficacy, disruptiveness, usability and trust. The results of the two surveys together suggest that users (patients) are sophisticated in how they use technology. They are therefore capable of having conversations about how advanced technologies should be developed and deployed along with other stakeholders in the complex ecosystem of healthcare.

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Accepted/In Press date: 2023

Identifiers

Local EPrints ID: 477827
URI: http://eprints.soton.ac.uk/id/eprint/477827
PURE UUID: 6feb0be6-b70b-4b51-bbf4-51e749c3a514
ORCID for Brian Pickering: ORCID iD orcid.org/0000-0002-6815-2938

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Date deposited: 15 Jun 2023 16:46
Last modified: 16 Jun 2023 01:41

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