TY - JOUR
T1 - Parental attitudes toward artificial intelligence-driven precision medicine technologies in pediatric healthcare
AU - Sisk, Bryan A.
AU - Antes, Alison L.
AU - Burrous, Sara
AU - Dubois, James M.
N1 - Funding Information:
Funding: This research was funded by National Center for Advancing Translational Sciences of the National Institutes of Health (UL1 TR002345) and National Human Genome Research Institute (K01HG008990).
Publisher Copyright:
© 2020 by the authors. Licensee MDPI, Basel, Switzerland.
PY - 2020/9
Y1 - 2020/9
N2 - Precision medicine relies upon artificial intelligence (AI)-driven technologies that raise ethical and practical concerns. In this study, we developed and validated a measure of parental openness and concerns with AI-driven technologies in their child’s healthcare. In this cross-sectional survey, we enrolled parents of children <18 years in 2 rounds for exploratory (n = 418) and confirmatory (n = 386) factor analysis. We developed a 12-item measure of parental openness to AI-driven technologies, and a 33-item measure identifying concerns that parents found important when considering these technologies. We also evaluated associations between openness and attitudes, beliefs, personality traits, and demographics. Parents (N = 804) reported mean openness to AI-driven technologies of M = 3.4/5, SD = 0.9. We identified seven concerns that parents considered important when evaluating these technologies: quality/accuracy, privacy, shared decision making, convenience, cost, human element of care, and social justice. In multivariable linear regression, parental openness was positively associated with quality (beta = 0.23), convenience (beta = 0.16), and cost (beta = 0.11), as well as faith in technology (beta = 0.23) and trust in health information systems (beta = 0.12). Parental openness was negatively associated with the perceived importance of shared decision making (beta = −0.16) and being female (beta = −0.12). Developers might support parental openness by addressing these concerns during the development and implementation of novel AI-driven technologies.
AB - Precision medicine relies upon artificial intelligence (AI)-driven technologies that raise ethical and practical concerns. In this study, we developed and validated a measure of parental openness and concerns with AI-driven technologies in their child’s healthcare. In this cross-sectional survey, we enrolled parents of children <18 years in 2 rounds for exploratory (n = 418) and confirmatory (n = 386) factor analysis. We developed a 12-item measure of parental openness to AI-driven technologies, and a 33-item measure identifying concerns that parents found important when considering these technologies. We also evaluated associations between openness and attitudes, beliefs, personality traits, and demographics. Parents (N = 804) reported mean openness to AI-driven technologies of M = 3.4/5, SD = 0.9. We identified seven concerns that parents considered important when evaluating these technologies: quality/accuracy, privacy, shared decision making, convenience, cost, human element of care, and social justice. In multivariable linear regression, parental openness was positively associated with quality (beta = 0.23), convenience (beta = 0.16), and cost (beta = 0.11), as well as faith in technology (beta = 0.23) and trust in health information systems (beta = 0.12). Parental openness was negatively associated with the perceived importance of shared decision making (beta = −0.16) and being female (beta = −0.12). Developers might support parental openness by addressing these concerns during the development and implementation of novel AI-driven technologies.
KW - Artificial intelligence
KW - Biomedical technology
KW - Child health
KW - Ethics
KW - Machine learning
KW - Pediatrics
KW - Personalized medicine
KW - Precision medicine
UR - http://www.scopus.com/inward/record.url?scp=85116306277&partnerID=8YFLogxK
U2 - 10.3390/children7090145
DO - 10.3390/children7090145
M3 - Article
C2 - 32962204
AN - SCOPUS:85116306277
SN - 2227-9067
VL - 7
JO - Children
JF - Children
IS - 9
M1 - 145
ER -