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Parental Attitudes toward Artificial Intelligence-Driven Precision Medicine Technologies in Pediatric Healthcare.
Sisk, Bryan A; Antes, Alison L; Burrous, Sara; DuBois, James M.
Afiliación
  • Sisk BA; Department of Pediatrics, Division of Hematology/Oncology, Washington University School of Medicine, St. Louis, MO 63110, USA.
  • Antes AL; Department of Medicine, Washington University School of Medicine, St. Louis, MO 63110, USA.
  • Burrous S; Brown School, Washington University, St. Louis, MO 63130, USA.
  • DuBois JM; Department of Medicine, Washington University School of Medicine, St. Louis, MO 63110, USA.
Children (Basel) ; 7(9)2020 Sep 20.
Article en En | MEDLINE | ID: mdl-32962204
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.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Aspecto: Equity_inequality / Ethics Idioma: En Revista: Children (Basel) Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Suiza

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Aspecto: Equity_inequality / Ethics Idioma: En Revista: Children (Basel) Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Suiza