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The intersection of big data and healthcare innovation: millennial perspectives on precision medicine technology

Authors :
Nicholas Tan
Md Irfanuzzaman Khan
Md Abu Saleh
Source :
Journal of Open Innovation: Technology, Market and Complexity, Vol 10, Iss 4, Pp 100376- (2024)
Publication Year :
2024
Publisher :
Elsevier, 2024.

Abstract

Precision medicine (PM) is an approach to healthcare that customizes treatment and prevention strategies based on individual characteristics such as genetics, environment, and lifestyle. By utilizing detailed data from diverse populations, precision medicine aims to provide accurate and effective medical care tailored to each person’s unique profile. This approach relies on the diversity of local populations which is increasingly captured through large-scale data sets, often referred to as Big Data. Due to the underrepresentation of non-European individuals in human genetic studies, many countries with diverse and underrepresented populations must build their own reference database due to a lack of holistic global perspective. This research investigated a population sub-group to better understand the factors shaping their attitudes of PM adoption in an Asian developed context. This research was based on the millennial generation in Singapore (born between 1981 and 1996). The study employed a quantitative online survey, based on the TAM theoretical framework. A total of 377 valid responses were received and the results were analysed using the structural equation modelling (SEM) technique. Results showed that perceived data security, subjective technical knowledge, trust in government, subjective norm and perceived usefulness influenced the attitude of millennials towards precision medicine and provided relevant insights for the successful implementation of PM approach in the future.

Details

Language :
English
ISSN :
21998531
Volume :
10
Issue :
4
Database :
Directory of Open Access Journals
Journal :
Journal of Open Innovation: Technology, Market and Complexity
Publication Type :
Academic Journal
Accession number :
edsdoj.bde09503e386494b84f9421240ab0f5c
Document Type :
article
Full Text :
https://doi.org/10.1016/j.joitmc.2024.100376