Finding my place in the world of research and data as an expert by experience

James Downs, expert by experience, and peer researcher.

I have worked as an expert by experience in the field of mental health for over a decade. Ever since I was able to access treatment for a longstanding eating disorder in my early 20s, I have been involved in contributing insights about my condition and my treatment to help develop more effective and inclusive services. In more recent years, this has led to more formal work in lived experience roles relating to quality improvement and healthcare policy. It’s been really rewarding to see changes that mean some patients will have better experiences than I did in the past – but there is still a long way to go.

More recently, I have become increasingly involved in the world of research, too. A lot of my own personal experiences have brought to light that there is so much we don’t know about mental illnesses, including eating disorders – from how they develop, and who they impact, to the ways in which they might most effectively be treated. The same is true of my work in policy –  very often there is so little evidence on which to design services, which makes it extremely difficult to recommend what might work for who, when, and how.

Photo taken at DATAMIND and MQ’s Data Science Meeting, April 2024.

Relying on guesswork in the field of mental health just isn’t good enough – we can and must do better. If we are to help more people to recover more quickly, then it will be through the power of knowledge. Creating a more sophisticated knowledge of mental illness and an individualised, evidence-based approach to treatment will help lift people like me out of suffering and perhaps even prevent illness in the first place. It’s through this knowledge that we might take away the despair that people like me have experienced when living inside a knowledge gap and met – with a lack of understanding and few viable options that anyone can say with any confidence will help.

Starting out in the emerging field of co-produced research

Whilst the world of mental health research is a beacon of hope for the future, it wasn’t always easy for me to feel like it was somewhere where I could offer anything useful, or where I could belong. When I started out, research teams didn’t know anywhere near as much about co-producing knowledge with those who have lived or living experiences of the conditions under investigation. Too often, it was a tick box exercise. This can still happen today, and I have the confidence now to identify and speak up when I feel that my involvement is more about what’s meaningful or easy for the research project than it is about what is valuable and important for me. We have come a long way in including people with lived/living experience in research, but these increasingly professionalised roles are still evolving, and we need to keep developing the best ways of working that can include a diverse range of people in the most valuable and valued ways.

When it comes to diversity, I feel like I have been lucky to be able to somehow find my way in the world of mental health research. It comes as an advantage that I have studied at university level, albeit with a lot of difficulty with undiagnosed autism and ADHD. Having a basic awareness of research and the kinds of places in which it takes place has helped, and I often wonder how it would have been to be involved in research without this background knowledge. Would I have felt even more out of place? What about if I wasn’t able to talk insightfully about my experiences, as many people have said I do; able to put my thoughts in terms that researchers find useful, easy to understand, or “acceptable”? I think there are so many reasons why people who are not like me may feel especially excluded from engaging with research projects, and the loss of their expertise means we fail to learn from those whose experiences we might need to hear most in order to fill in knowledge gaps relating to under-researched groups.

I’ve learnt a lot “on the job” when it comes to research methods, study design, and processes involved in research such as academic writing and publication. A lot of the research I have been involved with has focussed on qualitative data – something that seems a natural fit when the expertise that comes from experience is so often communicated via words, narrative, and “telling your story”. One thing that has frustrated me, though, has been when “telling my story” has been seen as the end point, or all I have to offer. Any one of us is so much more than a single story of illness, treatment, or recovery, and people with lived/living experience might have a particular way of knowing about their condition, but shouldn’t be confined to this. There is so much that those like me can offer to projects which make use of other kinds of data – from longitudinal population cohort datasets, to treatment outcome data from specialist NHS services.

Bridging the gap between the personal and the statistical  

It can be difficult to feel confidence in the area of data, statistics and general trends when your expertise is more personal, specific, and experiential. There is a tension between one single person’s experience which can be dismissed as “too anecdotal” to be applied to everyone, and generalised patterns and trends which can be equally unhelpful if imposed on an individual who doesn’t fit the norm. Bringing people with lived/living experience into contact with data science can help bridge this gap between the “ideographic” and the “nomothetic”, reminding everyone involved in mental health data science that there are individuals behind the numbers, in all their differences.

There have been many examples from my own experience that illustrate this tension and how including people with lived/living experience in research can help create more nuanced understandings that can be harnessed in more sophisticated use of data. As an autistic person with multiple physical and psychiatric diagnoses, I’ve often encountered research that examines discrete categories of illness as though these in themselves are heterogenous constructs, and which doesn’t always take into account how, in many instances, mental illnesses don’t exist in isolation from other co-occurring conditions and neurodivergence.

Having worked with eating disorders services as an expert by experience, I have been surprised by the lack of standard data collection, too, with little agreement on what data to collect in order to measure the outcomes and effectiveness of treatments that are offered to patients. The wide variety of understandings that can exist about what a good outcome may be for patients isn’t always captured in data, and marrying qualitative insights and intelligent data analysis would help move the field towards a greater shared understanding of how-to best help patients like me.

It is clear from some of the examples and tensions I have highlighted here that it can be difficult to know where to begin in untangling the multifaceted nature of mental illnesses and their treatment. This can be especially the case for people with lived/living experience when getting involved in coproducing research in the field of mental health data science. I hope to have shown in my own work that these barriers are worth overcoming, and that new insights and greater knowledge can be achieved by working together and breaking down barriers between different ways of knowing – the researchers, and the researched.

How to work well, together

The first thing that helped me to do this work was learning more about the technicalities of mental health data science. Gaining more awareness of the processes and terminology involved has given me more confidence to contribute in useful ways, and DATAMIND’s Data Literacy Course and Glossary are excellent places to start if anyone is looking to familiarise themselves with mental health data science and get more involved.

Secondly, more still needs to be done to diversify the kinds of lived/living experiences that are included in research, and the range of people who experience them. We especially need to remember that many people feel particularly excluded in academic spaces, for many reasons. I believe it is the responsibility of all researchers to take on the challenge of removing barriers to participation, rather than expecting people who are marginalised or different for whatever reason to do the work of involving themselves against the odds.

Lastly, the thing that helps me when my confidence wavers now – even with all my experience – is to remember that different ways of knowing are equally important, valid, and needed in the world of mental health science. Whilst I might sometimes need to ask questions about the methods involved in data science, teams of scientists can also learn a huge amount from people like me, who hold a particular kind of expertise and way of knowing about mental health that is of equal value. By coming together, we magnify the ability of each of our expertise to create the new knowledge we need to take us into a better future for mental health, for all.

James Downs

@ jamesldowns

www.jamesdowns.co.uk

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