作者
Faith Matcham, Daniel Leightley, Sara Siddi, Femke Lamers, Katie M White, Peter Annas, Giovanni de Girolamo, Sonia Difrancesco, Josep Maria Haro, Melany Horsfall, Alina Ivan, Grace Lavelle, Qingqin Li, Federica Lombardini, David C Mohr, Vaibhav A Narayan, Carolin Oetzmann, Brenda WJH Penninx, Stuart Bruce, Raluca Nica, Sara K Simblett, Til Wykes, Jens Christian Brasen, Inez Myin-Germeys, Aki Rintala, Pauline Conde, Richard JB Dobson, Amos A Folarin, Callum Stewart, Yatharth Ranjan, Zulqarnain Rashid, Nick Cummins, Nikolay V Manyakov, Srinivasan Vairavan, Matthew Hotopf, RADAR-CNS consortium
发表日期
2022/2/21
期刊
BMC psychiatry
卷号
22
期号
1
页码范围
136
出版商
BioMed Central
简介
Background
Major Depressive Disorder (MDD) is prevalent, often chronic, and requires ongoing monitoring of symptoms to track response to treatment and identify early indicators of relapse. Remote Measurement Technologies (RMT) provide an opportunity to transform the measurement and management of MDD, via data collected from inbuilt smartphone sensors and wearable devices alongside app-based questionnaires and tasks. A key question for the field is the extent to which participants can adhere to research protocols and the completeness of data collected. We aimed to describe drop out and data completeness in a naturalistic multimodal longitudinal RMT study, in people with a history of recurrent MDD. We further aimed to determine whether those experiencing a depressive relapse at baseline contributed less complete data.
Methods
Remote Assessment of Disease and Relapse – Major Depressive …
引用总数