Mobile Phone Sensor Correlates of Depressive Symptom Severity in Daily-Life Behavior: An Exploratory Study
| Autor: | Saeb, Sohrab, Zhang, Mi, Karr, Christopher J, Schueller, Stephen M, Corden, Marya E, Kording, Konrad P, Mohr, David C |
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| Rok vydání: | 2015 |
| Předmět: |
Adult
Male medicine.medical_specialty Telemedicine Activities of daily living Psychological intervention Health Informatics Audiology lcsh:Computer applications to medicine. Medical informatics Phone Surveys and Questionnaires medicine Cluster Analysis Humans mobile health (mHealth) Original Paper Depression lcsh:Public aspects of medicine Behavioral pattern lcsh:RA1-1270 Regression analysis Middle Aged Mental health 3. Good health classification Mobile phone Exploratory Behavior Geographic Information Systems Quality of Life lcsh:R858-859.7 Female Self Report activities of daily living Psychology Social psychology Cell Phone |
| Zdroj: | Journal of Medical Internet Research, Vol 17, Iss 7, p e175 (2015) Journal of Medical Internet Research |
| ISSN: | 1438-8871 |
| Popis: | Background: Depression is a common, burdensome, often recurring mental health disorder that frequently goes undetected and untreated. Mobile phones are ubiquitous and have an increasingly large complement of sensors that can potentially be useful in monitoring behavioral patterns that might be indicative of depressive symptoms. Objective: The objective of this study was to explore the detection of daily-life behavioral markers using mobile phone global positioning systems (GPS) and usage sensors, and their use in identifying depressive symptom severity. Methods: A total of 40 adult participants were recruited from the general community to carry a mobile phone with a sensor data acquisition app (Purple Robot) for 2 weeks. Of these participants, 28 had sufficient sensor data received to conduct analysis. At the beginning of the 2-week period, participants completed a self-reported depression survey (PHQ-9). Behavioral features were developed and extracted from GPS location and phone usage data. Results: A number of features from GPS data were related to depressive symptom severity, including circadian movement (regularity in 24-hour rhythm; r =-.63, P =.005), normalized entropy (mobility between favorite locations; r =-.58, P =.012), and location variance (GPS mobility independent of location; r =-.58, P =.012). Phone usage features, usage duration, and usage frequency were also correlated ( r =.54, P =.011, and r =.52, P =.015, respectively). Using the normalized entropy feature and a classifier that distinguished participants with depressive symptoms (PHQ-9 score ≥5) from those without (PHQ-9 score |
| Databáze: | OpenAIRE |
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