Log in to save to my catalogue

Predicting Depressive Symptom Severity Through Individuals' Nearby Bluetooth Device Count Data Colle...

Predicting Depressive Symptom Severity Through Individuals' Nearby Bluetooth Device Count Data Colle...

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_89530fa51a394f92affcd99f75ee3726

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

About this item

Full title

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

Publisher

Canada: JMIR Publications

Journal title

JMIR mHealth and uHealth, 2021-07, Vol.9 (7), p.e29840

Language

English

Formats

Publication information

Publisher

Canada: JMIR Publications

More information

Scope and Contents

Contents

Research 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 Bluetooth device count (NBDC) detected by Bluetooth sensors in mobile...

Alternative Titles

Full title

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

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_doaj_primary_oai_doaj_org_article_89530fa51a394f92affcd99f75ee3726

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_89530fa51a394f92affcd99f75ee3726

Other Identifiers

ISSN

2291-5222

E-ISSN

2291-5222

DOI

10.2196/29840

How to access this item