RADAR-MDD Data Set

YZ Yuezhou Zhang
AF Amos A Folarin
SS Shaoxiong Sun
NC Nicholas Cummins
SV Srinivasan Vairavan
LQ Linglong Qian
YR Yatharth Ranjan
ZR Zulqarnain Rashid
PC Pauline Conde
CS Callum Stewart
PL Petroula Laiou
HS Heet Sankesara
FM Faith Matcham
KW Katie M White
CO Carolin Oetzmann
AI Alina Ivan
FL Femke Lamers
SS Sara Siddi
SS Sara Simblett
AR Aki Rintala
DM David C Mohr
IM Inez Myin-Germeys
TW Til Wykes
JH Josep Maria Haro
BP Brenda W J H Penninx
VN Vaibhav A Narayan
PA Peter Annas
MH Matthew Hotopf
RD Richard J B Dobson
k ku.ca.lck@gnahz.uohzeuy
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The EU research program RADAR-MDD aimed to investigate the utility of mobile technologies for the long-term monitoring of participants with depression in real-world settings [35,40]. Adult participants with a depression history were included in the study if they did not meet the following criteria: (1) have other psychiatric disorders (eg, bipolar disorder, schizophrenia, and dementia), (2) have received treatment for drug or alcohol use in the past 6 months, (3) a major medical diagnosis that affects daily activities, and (4) pregnancy [35]. A detailed study protocol was published previously [35]. In this study, we used a subset of RADAR-MDD data collected from a study site in the United Kingdom (King’s College London [KCL]) between November 2017 and April 2021, because the KCL site was the only site to acquire ethical approval for collecting the phone’s acceleration signals. We hereafter denote this subset as the RADAR-MDD-KCL data set for convenience. The phone’s acceleration signals were collected at 50 Hz and uploaded to an open-source platform, RADAR-base [41]. The participants’ depression symptom severity was assessed by the 8-item Patient Health Questionnaire (PHQ-8) [42] self-reported through mobile phones every 2 weeks. A patient advisory board comprising service users co-developed the study. They were involved in the choice of measures, timing, and issues of engagement, and have also been involved in developing the analysis plan.

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