Finding the sweet spot: a qualitative study exploring patients' acceptability of chatbots in genetic service delivery.

Journal: Human genetics
Published Date: Mar 1, 2023

Abstract

Chatbots, web-based artificial intelligence tools that simulate human conversation, are increasingly in use to support many areas of genomic medicine. However, patient preferences towards using chatbots across the range of clinical settings are unknown. We conducted a qualitative study with individuals who underwent genetic testing for themselves or their child. Participants were asked about their preferences for using a chatbot within the genetic testing journey. Thematic analysis employing interpretive description was used. We interviewed 30 participants (67% female, 50% 50 + years). Participants considered chatbots to be inefficient for very simple tasks (e.g., answering FAQs) or very complex tasks (e.g., explaining results). Chatbots were acceptable for moderately complex tasks where participants perceived a favorable return on their investment of time and energy. In addition to achieving this "sweet spot," participants anticipated that their comfort with chatbots would increase if the chatbot was used as a complement to but not a replacement for usual care. Participants wanted a "safety net" (i.e., access to a clinician) for needs not addressed by the chatbot. This study provides timely insights into patients' comfort with and perceived limitations of chatbots for genomic medicine and can inform their implementation in practice.

Authors

  • Stephanie Luca
    Program in Child Health Evaluative Sciences, The Hospital for Sick Children, Toronto, ON, Canada.
  • Marc Clausen
    Genomics Health Services Research Program, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada.
  • Angela Shaw
    Genomics Health Services Research Program, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada.
  • Whiwon Lee
    Program in Child Health Evaluative Sciences, The Hospital for Sick Children, Toronto, ON, Canada.
  • Suvetha Krishnapillai
    Genomics Health Services Research Program, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada.
  • Ella Adi-Wauran
    Genomics Health Services Research Program, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada.
  • Hanna Faghfoury
    Fred A. Litwin Family Centre in Genetic Medicine, University Health Network and Sinai Health System, Toronto, ON, Canada.
  • Gregory Costain
    Division of Clinical and Metabolic Genetics, The Hospital for Sick Children, Toronto, ON, Canada.
  • Rebekah Jobling
    Division of Clinical and Metabolic Genetics, The Hospital for Sick Children, Toronto, ON, Canada.
  • Melyssa Aronson
    Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada.
  • Eriskay Liston
    Division of Clinical and Metabolic Genetics, The Hospital for Sick Children, Toronto, ON, Canada.
  • Josh Silver
    Fred A. Litwin Family Centre in Genetic Medicine, University Health Network and Sinai Health System, Toronto, ON, Canada.
  • Cheryl Shuman
    Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada.
  • Lauren Chad
    Division of Clinical and Metabolic Genetics, The Hospital for Sick Children, Toronto, ON, Canada.
  • Robin Z Hayeems
    Program in Child Health Evaluative Sciences, The Hospital for Sick Children, Toronto, ON, Canada.
  • Yvonne Bombard
    Genomics Health Services Research Program, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada. Yvonne.Bombard@utoronto.ca.

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