Methodological challenges in research on physical-mental health multimorbidity

Physical-mental health multimorbidity is common and its occurrence is increasing. Research in this area is needed to better understand the relationship between physical and mental health conditions – however, measuring mental health conditions and more widely, multimorbidity, is complicated.

Researchers from two MRC/NIHR funded projects, which are examining physical-mental health multimorbidity, will present findings from their work and lead discussion on challenges surrounding this research.

The programme will examine a number of key challenges in this field including:

• optimal ways of defining depression and other morbidities/multimorbidity in both research cohorts and routine data
• methods for clustering morbidities in cross-sectional and/or longitudinal data

Please Register to join via Zoom webinar

Please contact Usher Communications for further details.

Programme

09:15     Platform opens for attendees to log in  

09:30     Welcome & overview - Bruce Guthrie, The University of Edinburgh

Session 1 – Measuring multimorbidity 

09:50    Talk 1: Variation in the definition and measurement of multimorbidity in research - Iris Ho, The University of Edinburgh

10:00    Talk 2: How to operationalize physical and mental health conditions using routine records - Regina Prigge, The University of Edinburgh

10:10    Talk 3: How to efficiently harmonise data across different birth cohorts for multimorbidity research - Jorge Arias de la Torre, King's College London

10:20    Questions and discussion

10:40    Break

10:55    Talk 4: Defining depression in health datasets - Kelly Fleetwood, The University of Edinburgh

11:05    Talk 5: Pooled cohort data: challenges and remedies to temporal variability in depression measurements and its consequence for multimorbidity trajectory - Alexandru Dregan, King's College London

11:15    Questions and discussion

Session 2 – Methods for clustering and trajectories      

11:30    Talk 6: A comparison of methods for identifying multimorbidity patterns - Amy Ronaldson, King's College London

11:40    Talk 7: Modelling trajectories of disease in multimorbidity for the population of Wales - Rhiannon Owen, Swansea University

11:50    Talk 8: On clustering of multiple long term conditions: what can we do more with machine learning? - Sohan Seth, The University of Edinburgh

12:00    Questions and discussion        

12:20    Break

12:30    Chaired panel discussion

               Chair: Caroline Jackson, The University of Edinburgh

               Panel: Alexandru Dregan, Bruce Guthrie, Rhiannon Owen

12:50    Closing remarks - Bruce Guthrie 

13:00   Close

Download the programme PDF