Integration of AI to improve engagement from underserved groups with Digital Mental Health Pathways

The Industry and Innovation Research Institute (I2Ri) draws on talents, expertise and facilities across Sheffield Hallam University. The vision is to be the leading provider of applied research excellence delivering materials, computing, science and engineering innovations meeting the development needs of industry.

PhD Research Topic

This research aims to identify Artificial Intelligence (AI) algorithms, based on Natural Language Processing (NLP) to be integrated in the development of Digital Mental Health Pathways, as a supporting tool for women in the perinatal period.

Women in the perinatal period sometimes struggle to identify and seek help regarding mental health, this may specifically include issues such as distinguishing between ‘normal’ pregnancy changes and complications, and self-triage (deciding whether to seek help, where and how urgently).

The main aim of this project is to research what and how AI techniques can be used as a tool to maximize a digital version of mental health pathways, enhancing engagement for the targeted communities. 

There is evidence, including research conducted by the supervisory team members (e.g. Watson & Soltani 2019), that suggests that Black and Asian women are less likely to engage with mental health services or report mental health issues. Amongst reported obstacles to engagement with services were: language barriers, unfamiliarity with the service/support available or poor experiences of a previous engagement, and being from a different cultural background.

This project aims to investigate and implement the integration of AI techniques (based on text analysis) and digital technologies to increase the access and engagement of the specific sector of our community that is currently known to under-utilise and has limited access to the services.

There is limited research investigating how women in perinatal period use digital health technologies. This project aims to make a positive impact, exploring the (technologically mediated and unmediated) practices and everyday experiences of women from under-served communities.

Also, as a highlight this project aims to examine the suitability of existing theoretical frameworks for AI technology design of mental health interventions to propose a conceptual framework for designing socio-technical interventions that account for women’s lived experiences of care during perinatal period.

With the use of neural network language models to represent words as high-dimensional vectors is possible to identify and reduce bias and toxicity in text. This project aims to explore this technique to improve cultural awareness as a strategy to improve engagement with the digital Pathway.

The research outputs are the identification of barriers to digital solutions given the status of the individual and, the development of an adaptable methodology in a digital format based on intelligent text analysis techniques considering cultural diversity. This may help to improve women’s experiences of care and reduce health disparities, promoting early and more effective interventions.

The project involves the collaboration of local charities and local government, leading to a real impact on the development of future clinical Pathways with more inclusive and culturally sensitive.

The supervisory team has strong expertise on their areas. Professor Soltani leads Maternal and Infant Health Research (MIHR) team within SHU has been researching for over 25 years building an internationally recognised portfolio, her research has been ranked from clinical and organisational aspects of care with a focus on reducing health inequalities and promoting maternal and infant health at a national and global level.

Dr Davila Garcia has wide experience working in collaboration with the healthcare sector, developing and integrating technological solutions. She has wide experience in the application of AI and smart technologies in the healthcare sector.

Dr Chris Roast has an extensive supervisory experience and expertise in the areas of studies in interactive systems and interactive system design. In addition, He was PI on a preliminary work exploring this area.

Eligibility

Applicants should hold a 1st or 2:1 Honours degree in a related discipline. A Master’s degree in a related area is desirable. We welcome applications from all candidates irrespective of age, pregnancy and maternity, disability, gender, gender identity, sexual orientation, race, religion or belief, or marital or civil partnership status.

International candidates are required to provide an IELTS certificate with a score of at least 7.0 overall, and a minimum of 6.5 in all components. For further information on English Language requirements, please click here.

For further details on entry requirements, please click here.

How to apply

All applications must be submitted using the online application form. To apply, click here. In your application, be sure to include the title of the project that you are applying for.

As part of your application, please upload:

• A research proposal (max. 1500 words) in your own words, briefly outlining the proposed research, the current knowledge and context referencing key background literature; a proposed methodology or approach to answer the key questions, and any potential significance or impact of the research
• Copy of your highest degree certificate
• Non-UK applicants must submit IELTs results (or equivalent) taken in the last two years and a copy of their passport.

Applicants must provide 2 references, with at least one to be academic. References must be received directly from the referees.

We strongly recommend you contact the lead academic, Maria Luisa Davila Garcia m.l.davila-garcia@shu.ac.uk, to discuss your application.

For information on how to apply please visit https://www.shu.ac.uk/research/degrees