Project ID NS-MH2024_54

ThemeNS-MH

Co Supervisor 1A Institute of Psychiatry, Psychology & Neuroscience, School of Academic Psychiatry, Department of Psychological MedicineWebsite

Co Supervisor 1B Institute of Psychiatry, Psychology & Neuroscience, School of Mental Health & Psychological Sciences, Department of Biostatistics & Health InformaticsWebsite

Additional Supervisor Prof. Richard Dobson

Partner Oura

Using remote measurement technology to understand recovery processes in eating disorders

Scientific basis: Eating disorders (EDs) are common and disabling mental disorders. Processes that help or hinder recovery are poorly understood. Remote Measurement Technology (RMT) uses inbuilt sensors in smartphones and/or wearables to: (a) unobtrusively measure human behaviour and physiology (passive RMT) or (b) actively measure daily experiences via smartphone apps (active RMT). RMT provides real time information about patients’ clinical state and can predict remission/recovery or relapse. It hasn’t been used in EDs.

Project aims: This project is embedded in a longitudinal study (see https://edifyresearch.co.uk/), using biological and psychological RMT measures to (1) compare young people with a recent onset 1st episode of an ED (anorexia nervosa; bulimic eating disorders) and those with a longer-lasting ED with healthy controls; (2) assess differences in recovery trajectories within/across ED groups and (3) identify early RMT predictors of recovery at 12 months. [See https://radar-cns.org (as an exemplar) and https://radar-base.org (for reference to the platform)].

Techniques and skills learnt: The student will learn about EDs, design and conduct of RMT studies, and analysis of features obtained from biosensors, smartphones, cognitive/speech tests and experience sampling methodology. A training needs analysis will be conducted. They will be working across the vibrant eating disorders and bioinformatics groups, where they will be taught project specific skills. In addition, the student will be expected to attend transferrable skills training as required by their project.

Overarching objectives: Year 1: The student will familiarise themselves with the project and will write a systematic review e.g. on RMT in psychiatric disorders. Year 2: The student will participate in recruitment and data acquisition in the ongoing cohort study. Year 3: Data analysis and write up.

Representative Publications

Hemmings A, Sharpe H, Allen K, Bartel H, Campbell IC, Desrivières S, Dobson RJB, Folarin AA, French T, Kelly J, Micali N, Raman S, Treasure J, Abbas R, Heslop B, Street T, Schmidt U. EDIFY (Eating Disorders: Delineating Illness and Recovery Trajectories to Inform Personalised Prevention and Early Intervention in Young People): project outline. BJPsych Bull. 2022 Dec 22:1-9. doi: 10.1192/bjb.2022.83. Epub ahead of print. PMID: 36545688.

Allen KL, Mountford VA, Elwyn R, Flynn M, Fursland A, Obeid N, Partida G, Richards K, Schmidt U, Serpell L, Silverstein S, Wade T. A framework for conceptualising early intervention for eating disorders. Eur Eat Disord Rev. 2023 Mar;31(2):320-334. doi: 10.1002/erv.2959. Epub 2022 Nov 25. PMID: 36426567; PMCID: PMC10100476.

Austin A, Flynn M, Shearer J, Long M, Allen K, Mountford VA, Glennon D, Grant N, Brown A, Franklin-Smith M, Schelhase M, Jones WR, Brady G, Nunes N, Connan F, Mahony K, Serpell L, Schmidt U. The First Episode Rapid Early Intervention for Eating Disorders – Upscaled study: Clinical outcomes. Early Interv Psychiatry. 2022 Jan;16(1):97-105. doi: 10.1111/eip.13139. Epub 2021 Mar 29. PMID: 33781000; PMCID: PMC9291113.

Siddi S, Bailon R, Giné-Vázquez I, Matcham F, Lamers F, Kontaxis S, Laporta E, Garcia E, Lombardini F, Annas P, Hotopf M, Penninx BWJH, Ivan A, White KM, Difrancesco S, Locatelli P, Aguiló J, Peñarrubia-Maria MT, Narayan VA, Folarin A, Leightley D, Cummins N, Vairavan S, Ranjan Y, Rintala A, de Girolamo G, Simblett SK, Wykes T; PAB members; Myin-Germeys I, Dobson R, Haro JM; RADAR-CNS consortium. The usability of daytime and night-time heart rate dynamics as digital biomarkers of depression severity. Psychol Med. 2023 Jun;53(8):3249-3260. doi: 10.1017/S0033291723001034. Epub 2023 May 15. PMID: 37184076.

Zhang Y, Pratap A, Folarin AA, Sun S, Cummins N, Matcham F, Vairavan S, Dineley J, Ranjan Y, Rashid Z, Conde P, Stewart C, White KM, Oetzmann C, Ivan A, Lamers F, Siddi S, Rambla CH, Simblett S, Nica R, Mohr DC, Myin-Germeys I, Wykes T, Haro JM, Penninx BWJH, Annas P, Narayan VA, Hotopf M, Dobson RJB; RADAR-CNS consortium. Long-term participant retention and engagement patterns in an app and wearable-based multinational remote digital depression study. NPJ Digit Med. 2023 Feb 17;6(1):25. doi: 10.1038/s41746-023-00749-3. PMID: 36806317; PMCID: PMC9938183.

de Angel V, Adeleye F, Zhang Y, Cummins N, Munir S, Lewis S, Laporta Puyal E, Matcham F, Sun S, Folarin AA, Ranjan Y, Conde P, Rashid Z, Dobson R, Hotopf M. The Feasibility of Implementing Remote Measurement Technologies in Psychological Treatment for Depression: Mixed Methods Study on Engagement. JMIR Ment Health. 2023 Jan 24;10:e42866. doi: 10.2196/42866. PMID: 36692937; PMCID: PMC9906314.