2019年12月11日
Predicting recurrence of depression using lifelog data: an explanatory feasibility study with a panel VAR approach.
BMC psychiatry
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- 巻
- 19
- 号
- 1
- 開始ページ
- 391
- 終了ページ
- 391
- 記述言語
- 英語
- 掲載種別
- 研究論文(学術雑誌)
- DOI
- 10.1186/s12888-019-2382-2
BACKGROUND: Although depression has a high rate of recurrence, no prior studies have established a method that could identify the warning signs of its recurrence. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.
- リンク情報
- ID情報
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- DOI : 10.1186/s12888-019-2382-2
- PubMed ID : 31829206
- PubMed Central 記事ID : PMC6907185