Predicting Depressive Symptom Severity Through Individuals’ Nearby Bluetooth Device Count Data Collected by Mobile Phones: Preliminary Longitudinal Study
JMIR mhealth and uhealth2021Vol. 9(7), pp. e29840–e29840
Citations Over TimeTop 10% of 2021 papers
Yuezhou Zhang, Amos Folarin, Shaoxiong Sun, Nicholas Cummins, Yatharth Ranjan, Zulqarnain Rashid, Pauline Conde, Callum Stewart, Petroula Laiou, Faith Matcham, Carolin Oetzmann, Femke Lamers, Sara Siddi, Sara Simblett, Aki Rintala, David C. Mohr, Inez Myin‐Germeys, Til Wykes, Josep María Haro, Brenda W.J.H. Penninx, Vaibhav A. Narayan, Peter Annas, Matthew Hotopf, Richard Dobson
Abstract
Our statistical results indicate that the NBDC data have the potential to reflect changes in individuals' behaviors and statuses concurrent with the changes in the depressive state. The prediction results demonstrate that the NBDC data have a significant value in predicting depressive symptom severity. These findings may have utility for the mental health monitoring practice in real-world settings.
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