Appropriate Innovation: Using AI technology to enhance clinical trial accessibility for marginalised communities

About the Project

This project explores how AI translation tools, like Google Translate and ChatGPT, can help make health research more inclusive for people from marginalised groups who face language barriers. It will investigate how researchers and communities experience these tools, examine concerns about accuracy and fairness, and work with local communities to develop practical guidance for using AI translation in clinical trials. The aim is to ensure that AI supports, not replaces professional translation, helping more people participate in health research safely and ethically.

Background:

Minoritised ethnic groups are often excluded in health research due to unmet language needs, including low first language literacy or limited English proficiency in English-dominant settings. While effective translation is essential to inclusive research, it is costly and time-consuming. For rarer languages, professional translation is often unavailable. Existing guidance on translation and interpretation in clinical trials remains limited with few regulatory standards/processes. AI technologies used for translation, such as Google Translate and ChatGPT are increasingly used in healthcare, but this use is largely going unnoticed and unregulated. These tools are widely available, inexpensive and easily accessible. They have the potential to increase access to information and reduce language barriers for populations who are under-served by current clinical trial practices. However, the use of any AI technology raises concerns around social justice as well as the practical concerns of the accuracy of AI translation. Unregulated and potentially misguided uses of these tools raise significant ethical and safety issues in clinical research. If these concerns can be adequately addressed, AI translation offers great promise by supporting (not replacing) professional translation and enabling information exchange to members of marginalised communities taking part in clinical trials.

Given the lack of knowledge and significant concerns associated with the use of AI technology in clinical trial research, this project aims to explore its appropriate use by:

1. Investigating the AI translation tools currently being used by researchers and what are their experiences and views on their use.
2. Understanding how marginalised groups perceive the use of AI translation in clinical trial research, and how do inaccuracies (including cultural insensitivity) affect trust and understanding.
3. Co-producing a set of recommendations and guidance for researchers on using AI technology to support information exchange in clinical trial research.

This project will work with local marginalised communities building on established collaborations and developing new collaborations with the Faculty of Arts. The research will include:

1. A rapid scoping review of the current literature, NHS and higher institute policies/ recommendations on the use of AI technology to support professional translation in clinical research settings (student will lead and develop skills in systematic reviewing).
2. A survey and ethnographic approach (interviews, focus groups and observations) with clinical trial researchers to explore how AI translations are being used in clinical research and the experiences and acceptability of their use (student will lead on development of survey and qualitative methodology- writing PILs, topic guides, thematic analysis).
3. Participatory Action Research with under-served communities to i) understand their views and experiences on the use of AI technology to support professional translation in clinical trial research; ii) Co-produce set of recommendations and/or guidance for clinical trial researchers (student will develop skills in Participatory Action Research, particularly in developing mutually beneficial relationships, will take a lead on running sessions with communities, and lead on dissemination/ knowledge mobilisation outputs).

University of Bristol, Bristol Medical School

Bristol Medical School is the largest and one of the most diverse Schools in the University of Bristol, with approximately 930 members of staff and over 300 postgraduate doctoral research students. The School is a leading centre for research and teaching across Population Health Sciences and Translational Health Sciences. Research in the School is collaborative and multi-disciplinary, with staff coming from a wide range of academic disciplines and clinical specialties.

The 2021 Research Excellence Framework (REF) confirmed the University of Bristol’s position as a leading centre for health research. Bristol Medical School contributed to three Units of Assessment including UoA1 (Clinical Medicine), UoA2 (Public Health, Health Services and Primary Care) and UoA4 (Psychology, Psychiatry and Neuroscience). The UoA2 submission, comprising predominantly Medical School staff. was ranked 3rd in the UK with 94% of our submitted research outputs rated as world leading (4*) or internationally excellent (3*). Submissions to UoA1 and UoA4 were shared with varying degrees of representation with the Faculty of Life Sciences. Respectively UoA1 and UoA4 had 94% and 84% of submitted research ranked as 4* or 3*, which represented increases in each category in the proportions of 4* ranked papers as well in growth in GPA rankings above the previous REF2014.

Within the Medical School are several major research centres, groups and programmes. More details can be found on the Medical School website.

How to apply

You can submit an application via the University of Bristol application portal: Start your application | Study at Bristol | University of Bristol selecting the relevant 4-year PhD programme, e.g. “Population Health Sciences (PhD) (4yr)”.

Link to prospectus pages for Population Health Sciences giving entry requirements and admissions statement: Population Health Sciences

In the funding section of the application form, please select `Self-funding` or the name of your sponsor.

For project-related enquiries, please contact the project supervisor directly.

Dr. Kirsty Roberts kirsty.roberts@bristol.ac.uk

Funding Notes

For self-funders or those who have secured their own sponsorship.