Predicting Depressive Symptom Severity Through Individuals' Nearby Bluetooth Device Count Data Collected by Mobile Phones: Preliminary Longitudinal Study

• Ngā kaituhi matua: Yuezhou Zhang (Author), Amos A Folarin (Author), Shaoxiong Sun (Author), Nicholas Cummins (Author), Yatharth Ranjan (Author), Zulqarnain Rashid (Author), Pauline Conde (Author), Callum Stewart (Author), Petroula Laiou (Author), Faith Matcham (Author), Carolin Oetzmann (Author), Femke Lamers (Author), Sara Siddi (Author), Sara Simblett (Author), Aki Rintala (Author), David C Mohr (Author), Inez Myin-Germeys (Author), Til Wykes (Author), Josep Maria Haro (Author), Brenda W J H Penninx (Author), Vaibhav A Narayan (Author), Peter Annas (Author), Matthew Hotopf (Author), Richard J B Dobson (Author)
• Hōputu: Pukapuka
• I whakaputaina: JMIR Publications, 2021-07-01T00:00:00Z.
• Ngā marau: article
• Urunga tuihono: Connect to this object online.

BackgroundResearch in mental health has found associations between depression and individuals' behaviors and statuses, such as social connections and interactions, working status, mobility, and social isolation and loneliness. These behaviors and statuses can be approximated by the nearby Bluet...