MINDSET
Multimodal INference and Data Science for Epidemiology and Treatment (MINDSET) is the research programme established and led by Dr Justin C Yang, Senior Research Fellow in the Division of Psychiatry at University College London.
People’s experiences are distributed across health services, schools, treatment systems, communities, and environments, while real-world data provide partial and institutionally produced representations of those experiences. MINDSET treats those limitations as part of the scientific question: who becomes visible to services and datasets, what is recorded or missing, and how those processes shape conclusions. It brings psychiatric epidemiology, causal inference, and data science together with work on governance and research infrastructure.
This combination supports credible, useful, and responsible inference about mental health from complex real-world data. It makes it possible to investigate whether observed inequalities reflect differences in need, access, recognition, recording, or care, and to examine trajectories that no single source can represent. The programme is organised around three enduring questions.
What shapes mental health and inequalities over time?
Understanding how social, relational, environmental, educational, and institutional experiences influence mental health, service use, and wider outcomes across people, populations, and places.
How can complex real-world data tell us what is actually happening?
Making better use of linked records, electronic health records, clinical free text, longitudinal data, and other sources while remaining attentive to selection, measurement, missingness, and the limits of inference.
How can data systems better support research, services, and public decision-making?
Improving the infrastructures, governance, and analytical practices through which routinely collected data become useful evidence for research, policy, services, and the public.
A connected research agenda
MINDSET develops through time-bounded studies that approach the same questions from different settings. WISDOM and HOPE-SEN examine mental-health trajectories and inequalities using complementary longitudinal data. UNITED and a new anti-stigma intervention process evaluation extend this agenda into addiction treatment, professional practice, and service improvement. Work with the North London NHS Foundation Trust Research Database turns methodological and substantive lessons into better governed research infrastructure.
The relationship runs in both directions: substantive questions reveal limitations in existing data; methodological work clarifies what can credibly be inferred; and infrastructure work improves the evidence available for the next study. Individual awards start and finish, but this cycle provides continuity across the wider programme.
Work with MINDSET
MINDSET is collaborative by design, connecting researchers, NHS organisations, public-sector data providers, treatment services, charities, people with lived experience, and policy and research partners across a wider research network.
- Researchers and research groups: collaboration on psychiatric epidemiology, linked data, electronic health records, causal inference, mental-health data science, and related substantive questions.
- NHS, policy, data, and service partners: work on the responsible use of routinely collected data, research infrastructure, evaluation, and questions with practical relevance to services and public decision-making.
- People with lived experience and public partners: involvement in shaping research questions, interpretation, governance, and the use of evidence about health and care.
- Trainees: PhD, MSc, and undergraduate supervision, methods collaboration, teaching, and researcher development where there is a strong fit with the programme.
Across this work, I aim to develop research that is methodologically rigorous, transparent and reproducible, attentive to inequalities, and accountable to the people and communities represented in the data.
Explore the research programme, people and partnerships, publications, research funding, talks and presentations, teaching and supervision, open research and resources, and leadership and recognition, or get in touch.