Welcome back to our ‘In Conversation’ series where we introduce you to the people who make the Hub for Metabolic Psychiatry’s research happen. In this post, meet our newest Hub member, Elchin Asgarov, a PhD researcher based at the University of Edinburgh who is developing a digital tool to help individuals with severe mental illness track and manage their physical and mental health.

Please share a little about yourself.

My name is Elchin Asgarov, and I am from Baku, Azerbaijan. I am currently a PhD student at the Centre for Clinical Brain Sciences at the University of Edinburgh. My PhD focuses on the development and evaluation of a digital self-management resource for metabolic health in people with severe mental illness (SMI), funded by the University of Edinburgh's College of Medicine and Veterinary Medicine. I hold a Master of Science degree in Advanced Computer Science from the University of Manchester. My research interests lie in interdisciplinary fields, particularly the intersection of computer science and mental health.

Tell us a bit more about your PhD project.

My current research involves developing and evaluating a digital self-management intervention to support metabolic health in individuals with SMI. People with SMI are at a significantly higher risk of developing metabolic conditions compared to the general population. Addressing this gap is essential to improve their overall health outcome.

To address this issue, my project aims to design a digital intervention that help individuals with SMI to monitor and manage their physical health. The intervention is being co-produced with patients and healthcare professionals to ensure it is user-centred, acceptable, and clinically relevant. I believe this work can improve people's lives by helping them manage their health more effectively, leading to better outcomes for both physical and mental well-being.

How did you become involved in your current area of research?

During my master's studies at the University of Manchester, I enrolled in several interdisciplinary, research-based courses where I applied my computer science skills to real-world healthcare challenges. I worked on data management challenges in breast cancer treatment in the UK and data quality problems in genomic databases. These projects improved my understanding of the complexities of health data. During the courses, I collaborated with people from different backgrounds and tried to find computational solutions that transform healthcare. These courses caught my interest and made me realise the potential of digital solutions in health contexts.

I knew I wanted to work at the intersection of computer science and healthcare, but I wasn’t sure which area to focus on. That changed when I came across this PhD project. It was exactly what I had been looking for. Mental health is often overlooked or treated separately from physical health, but this project recognises the strong link between metabolic health and mental health. I am interested in this work because I want to help bring these two areas together and improve support for people with SMI.

How do you deal with the ethical implications of your work?

Health data is among the most sensitive types of personal data, and I work with a particularly vulnerable population. I take ethical considerations very seriously and regularly discuss them with my supervisors, who are highly experienced in conducting ethical research and public involvement. I will ensure that ethical concerns around data privacy and participant well-being will be addressed throughout the project design and implementation stages.

What kind of research would you like to see conducted in the future?

In the future, I would like to see more research that explores how digital tools and machine learning techniques can be applied to better understand the patterns and relationships between metabolic health and mental health. There is still so much we don’t know about how physical and mental health influence each other, especially in people with severe mental illness. I believe that by analysing patterns in real-world health data, we can identify patterns and offer more personalised support.

I would also like to see more research that is co-produced with patients and healthcare professionals. When people with lived experience are involved from the beginning, the solutions become more practical, relevant, and meaningful. That’s why collaboration and the involvement of patients and healthcare professionals are important.

What motivated/inspired you to carry out this research?

What motivated and inspired me to carry out this research is the chance to make a real and lasting difference in people’s lives. Individuals living with SMI often face major challenges when it comes to managing their physical health, especially metabolic conditions like diabetes, obesity, high blood pressure, high blood sugar etc. These issues are often missed or untreated, even though they have a serious impact on overall wellbeing.

I saw a real need for a supportive tool that could help people better understand and track their metabolic health. If we can help people take small, manageable steps toward looking after their physical health, we can also support improvements in their mental health. That connection between the body and mind is powerful, and too often ignored.

I am also deeply inspired by the idea of giving people more control over their own health. I believe everyone deserves tools that are designed with their needs in mind. Knowing that this work could help reduce barriers, improve access, and support people in feeling more confident about their health is what keeps me going. My goal is to make technology that supports people and fits into their lives.

What have you found the most interesting aspect of your work so far?

The most interesting aspect of my work is its interdisciplinary nature. I get to collaborate with experts from various backgrounds, including mental health professionals, psychiatrists, computer scientists, and individuals with lived experience. This creates a rich, collaborative environment that brings together diverse perspectives to solve complex problems.

This collaborative approach naturally leads into co-production, which I find to be one of the most rewarding aspects of the work. Engaging directly with the people who will use the tool helps me understand what they need. This makes sure the digital solution is practical, effective, and meaningful.

In Conversation with Elchin Asgarov