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Published 6 January 2026

Meet Cross-Hub Research Fellow Annie

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Author name: Dr Annie Jeffery (she/her) Institution name: University College of London

Dr Annie Jeffery is an epidemiologist at UCL, specialising in the relationship between depression, metabolic health, and how this is influenced by the wider context of people's lives.

Annie is one of the first recipients of the MHP Early Career Researcher Fellowship Awards, which aim to help develop future leaders in SMI research. Her project will focus on depression, and will bring together DATAMIND, Metabolic Psychiatry and Social Health. ​She tells us more about her work and hopes for the project. 

 

Researching depression from all angles

I've just started a fellowship with the Mental Health Platform with a project called: "Treatment resistant depression, metabolic health and social health - what is the link and where can we intervene?" 

Traditional statistical methods have struggled to answer this question, as they are unable to model complex real-world situations where loads of interacting and constantly changing factors influence whether or not mental health treatments work. 

I will be testing novel methods from "Bayesian causal epidemiology" to see if we can overcome these challenges. These methods will allow me to combine clinical information with information about the wider context of people’s lives. This will help me disentangle what is really causing adverse health outcomes, not just what’s associated.

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Collaborating for change

The most exciting part of this fellowship, for me, is the opportunity to collaborate with so many talented researchers from a wide range of disciplines. My research focuses on understanding the whole-person, and that simply isn’t possible without drawing on different forms of expertise and perspectives. 

I’m particularly looking forward to working with my lived-experience collaborators. We’re planning to co-produce training that supports both researchers and members of the public to collaborate meaningfully on research that uses cutting-edge statistical methods. 

I hope to identify changes we can implement - both clinically and socially - that will make depression easier to manage for people with physical health conditions such as type 2 diabetes, and that will make physical health easier to manage for people suffering from depression. 

I also hope to make Bayesian causal epidemiology more mainstream. People often tell me that these methods are incomprehensible! I want to change that!

Social Health, Metabolic Psychiatry, DATAMIND logos

Turning the unexpected into understanding

My PhD research produced the complete opposite results to what I had expected. I'm currently trying to disprove them! When looking at clinical data alone, it seemed as though treating depression was harmful to people's physical health (I don't believe this!). 

Without understanding the bigger picture that impacts people's treatment choices, their mental health and their physical health, I think it is impossible to understand how mental health treatment is going to work. I'm now trying to bring together data from a range of sources to get a better understanding of this bigger picture. 

More about me

I couldn't be happier than when I'm skiing, hiking, or surfing. I feel a constant sense of awe when I'm surrounded by mountains. I love the thrill of skiing down something vertical, bumpy and hugely intimidating, where every move you make matters. I'm really quite bad at surfing. But I enjoy how humbling the ocean is. And when you finally catch a wave, it's the best feeling in the world.

 

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Datamind Metabolic Social
Read more about DATAMIND, Metabolic Psychiatry and Social Health. ​