Predicting recurrence of depression using lifelog data: an explanatory feasibility study with a panel VAR approach

Although depression has a high rate of recurrence, no prior studies have established a method that could identify the warning signs of its recurrence. We collected digital data consisting of individual activity records such as location or mobility information (lifelog data) from 89 patients who were...

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Bibliographic Details
Published in:BMC psychiatry 2019-12, Vol.19 (1), p.391-391, Article 391
Main Authors: Kumagai, Narimasa, Tajika, Aran, Hasegawa, Akio, Kawanishi, Nao, Horikoshi, Masaru, Shimodera, Shinji, Kurata, Ken'ichi, Chino, Bun, Furukawa, Toshi A
Format: Article
Language:English
Subjects:
Analysis
Depression
Diaries
Feasibility studies
Health
Health surveys
Kessler psychological distress scale
Kurashi-app
Lifelog
Lifestyles
Long sleep time
Meals
Mental depression
Mental disorders
Mental health care
Panel vector autoregressive model
Patients
Prognosis
Psychiatry
Questionnaires
Recurrence (Disease)
Risk factors
Sleep
Smart phones
Smartphones
Stress (Psychology)
Surveys
Survival analysis
Variables
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Summary:Although depression has a high rate of recurrence, no prior studies have established a method that could identify the warning signs of its recurrence. We collected digital data consisting of individual activity records such as location or mobility information (lifelog data) from 89 patients who were on maintenance therapy for depression for a year, using a smartphone application and a wearable device. We assessed depression and its recurrence using both the Kessler Psychological Distress Scale (K6) and the Patient Health Questionnaire-9. A panel vector autoregressive analysis indicated that long sleep time was a important risk factor for the recurrence of depression. Long sleep predicted the recurrence of depression after 3 weeks. The panel vector autoregressive approach can identify the warning signs of depression recurrence; however, the convenient sampling of the present cohort may limit the scope towards drawing a generalised conclusion.
ISSN:1471-244X
1471-244X
DOI:10.1186/s12888-019-2382-2