Evidence map›Paper›PMID 36629921›Full record

ArticleHuman genetics2023

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

Stephanie Luca, Marc Clausen, Angela Shaw, Whiwon Lee, Suvetha Krishnapillai, Ella Adi-Wauran, Hanna Faghfoury, Gregory Costain, Rebekah Jobling, Melyssa Aronson and 7 more

Open access · bronzeAbstract read
In one paragraph

Article in Human genetics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
5.5field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

19 citing papers in PubMed, 31 citations in OpenAlex.

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  8. What patients want from healthcare chatbots: insights from a mixed-methods study.Journal of the American Medical Informatics Association : JAMIA · 2025
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  18. Using a chat-based informed consent tool in large-scale genomic research.Journal of the American Medical Informatics Association : JAMIA · 2024
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

17 authors at 4 institutions in 1 country.

Stephanie LucaProgram in Child Health Evaluative Sciences, The Hospital for Sick Children, Toronto, ON, Canada.
Marc ClausenGenomics Health Services Research Program, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada.
Angela ShawGenomics Health Services Research Program, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada.
Whiwon LeeProgram in Child Health Evaluative Sciences, The Hospital for Sick Children, Toronto, ON, Canada.
Suvetha KrishnapillaiGenomics Health Services Research Program, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada.
Ella Adi-WauranGenomics Health Services Research Program, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada.
Hanna FaghfouryFred A. Litwin Family Centre in Genetic Medicine, University Health Network and Sinai Health System, Toronto, ON, Canada.
Gregory CostainDivision of Clinical and Metabolic Genetics, The Hospital for Sick Children, Toronto, ON, Canada.
Rebekah JoblingDivision of Clinical and Metabolic Genetics, The Hospital for Sick Children, Toronto, ON, Canada.
Melyssa AronsonDepartment of Molecular Genetics, University of Toronto, Toronto, ON, Canada.
Eriskay ListonDivision of Clinical and Metabolic Genetics, The Hospital for Sick Children, Toronto, ON, Canada.
Josh SilverFred A. Litwin Family Centre in Genetic Medicine, University Health Network and Sinai Health System, Toronto, ON, Canada.
Cheryl ShumanDepartment of Molecular Genetics, University of Toronto, Toronto, ON, Canada.
Lauren ChadDivision of Clinical and Metabolic Genetics, The Hospital for Sick Children, Toronto, ON, Canada.
Robin Z HayeemsProgram in Child Health Evaluative Sciences, The Hospital for Sick Children, Toronto, ON, Canada.
Yvonne BombardGenomics Health Services Research Program, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada. Yvonne.Bombard@utoronto.ca.ORCID http://orcid.org/0000-0002-9516-4539
Genetics Navigator Study Team
University of Toronto · CASt. Michael's Hospital · CAHospital for Sick Children · CAUniversity Health Network · CA

Funding

CIHR PMJ 175409CIHR PNN 177934
6 · The paper itself

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.

Indexed as

Artificial IntelligenceGenetic ServicesChildFemaleGenetic TestingHumansMalePatient PreferenceSoftware

Identifiers

PMID36629921
PMCPMC9838385
OpenAlexW4315619135

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.