People from ethnic minority backgrounds are disproportionately affected by STIs and HIV and experience challenges accessing typical sexual health services. This research involves designing and piloting an AI chatbot for supporting people with STIs/HIV from ethnic minority backgrounds.

Why was this work needed?


People from ethnic minority backgrounds are disproportionately affected by sexually transmitted infections (STIs) and HIV. Furthermore, discrimination, stigma, and reluctance to discuss sexuality prevents them from accessing typical sexual health services. Although the NHS has started offering at-home and online screening for STIs/HIV, they may not be socially and culturally appropriate to ethnic minorities, leading to lower uptake of interventions and thus ultimately poorer health outcomes and exacerbated health inequalities. AI tools such as chatbots could offer a way of supporting these groups in a way that better suits their needs.

What happened?

Researchers have designed and piloted a chatbot called ‘Pat’ which works to improve users’ knowledge of STIs/HIV and promote online screening services. They are first exploring the views of minorities in order to tailor it to these groups and using simulation exercises to determine how willing they would be to disclose personal health information to the chatbot and likelihood of engaging in further sexual health testing. The chatbot uses AI by taking personal health information provided by the user and crosschecking it against information it has been trained with in order to suggest the most appropriate advice.

What were the benefits?

Research and testing of the chatbot is ongoing, not just in terms of its accuracy but also in terms of how willing people will be to use it – many are receptive to the idea, but remain hesitant and sceptical which could impact their engagement with the chatbot.

If the tool works, though, it could have a significant impact on health inequalities for ethnic minorities with STIs/HIV and lead to further development on AI resources that are more appropriate and sensitive to social and cultural differences amongst these groups.

Research like this benefits from participants’ willingness to participate in studies to share their perspective on these tools, as well as access to data on patient diagnosis, treatment, outcomes and ethnicity in order for the tool to provide the most accurate advice to the user.

Who funded and collaborated on this work?

Researchers from University of Westminster - in partnership with Positive East, University of Southampton, and Brighton & Sussex Medical School - were funded by the NHS AI Lab as part of their AI Ethics initiative which focuses on using AI to counter health inequalities.

Where can I go for more information?

Westminster researchers receive £240,838 funding for a new study addressing racial and ethnic inequalities in healthcare using artificial intelligence

Guardian article about AI projects to tackle racial inequality in UK healthcare

Acceptability of artificial intelligence (AI)-led chatbot services in healthcare: A mixed-methods study – from the lead researcher for the chatbot research