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.
This project is embedded in a longitudinal study, using biological and psychological RMT measures to (1) compare young people with a 1st episode of an 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)].
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. 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.