The relationship of socio-demographic factors and patient attitudes to connected health technologies: a survey of stroke survivors.

Drake, Archie, Sassoon, Isabel, Balatsoukas, Panos , Porat, Talya, Ashworth, Mark, Wright, Ellen, Curcin, Vasa, Chapman, Martin, Kokciyan, Nadin, Sanjay, Modgil, Sklar, Elizabeth and Parsons, Simon (2022) The relationship of socio-demographic factors and patient attitudes to connected health technologies: a survey of stroke survivors. Health Informatics Journal . ISSN 1460-4582

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The relationship of socio-demographic factors and patient attitudes to connected health technologies: a survey of stroke survivors
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Item Type:Article
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Abstract

More evidence is needed on technology implementation for remote monitoring and self-management across the various settings relevant to chronic conditions. This paper describes the findings of a survey designed to explore the relevance of socio-demographic factors to attitudes towards connected health technologies in a community of patients. Stroke survivors living in the UK were invited to answer questions about themselves and about their attitudes to a prototype remote monitoring and self-management app developed around their preferences. Eighty (80) responses were received and analysed, with limitations and results presented in full. Socio-demographic factors were not found to be associated with variations in participants’ willingness to use the system and attitudes to data sharing. Individuals’ levels of interest in relevant technology was suggested as a more important determinant of attitudes. These observations run against the grain of most relevant literature to date, and tend to underline the importance of prioritising patient-centred participatory research in efforts to advance connected health technologies.

Keywords:Assistive technologies, decision-support systems, electronic health records, information and knowledge management, IT design and development methodologies, machine learning, mobile health
Subjects:G Mathematical and Computer Sciences > G400 Computer Science
Divisions:College of Science > School of Computer Science
ID Code:49216
Deposited On:10 May 2022 07:47

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