Barriers and facilitators to engagement with artificial intelligence (AI)-based chatbots for sexual and reproductive health advice: a qualitative analysis
Tom Nadarzynski A * , Vannesa Puentes B , Izabela Pawlak A , Tania Mendes A , Ian Montgomery C , Jake Bayley D and Damien Ridge AA School of Social Sciences, University of Westminster, London, UK.
B Science, Engineering and Computing Faculty, Kingston University, London, UK.
C Positive East, London, UK.
D Barts NHS Trust, London, UK.
Sexual Health 18(5) 385-393 https://doi.org/10.1071/SH21123
Submitted: 12 March 2021 Accepted: 19 July 2021 Published: 16 November 2021
© 2021 The Author(s) (or their employer(s)). Published by CSIRO Publishing. This is an open access article distributed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND)
Abstract
Background: The emergence of artificial intelligence (AI) provides opportunities for demand management of sexual and reproductive health services. Conversational agents/chatbots are increasingly common, although little is known about how this technology could aid services. This study aimed to identify barriers and facilitators for engagement with sexual health chatbots to advise service developers and related health professionals.
Methods: In January–June 2020, we conducted face-to-face, semi-structured and online interviews to explore views on sexual health chatbots. Participants were asked to interact with a chatbot, offering advice on sexually transmitted infections (STIs) and relevant services. Participants were UK-based and recruited via social media. Data were recorded, transcribed verbatim and analysed thematically.
Results: Forty participants (aged 18–50 years; 64% women, 77% heterosexual, 58% white) took part. Many thought chatbots could aid sex education, providing useful information about STIs and sign-posting to sexual health services in a convenient, anonymous and non-judgemental way. Some compared chatbots to health professionals or Internet search engines and perceived this technology as inferior, offering constrained content and interactivity, limiting disclosure of personal information, trust and perceived accuracy of chatbot responses.
Conclusions: Despite mixed attitudes towards chatbots, this technology was seen as useful for anonymous sex education but less suitable for matters requiring empathy. Chatbots may increase access to clinical services but their effectiveness and safety need to be established. Future research should identify which chatbots designs and functions lead to optimal engagement with this innovation.
Keywords: AI, artificial intelligence, chatbot, e-health, education, health promotion, health services, risk assessment.
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