- Abstract:
-
Background
Traditionally, assessment of psychiatric symptoms has been relying on their retrospective report to a trained interviewer. The emergence of smartphones facilitates passive sensor-based monitoring and active real-time monitoring through time-stamped prompts; however there are few validated self-report measures designed for this purpose.
Methods
We introduce a novel, compact questionnaire, Mood Zoom (MZ), embedded in a customized smartphone application. MZ...
Expand abstract - Publication status:
- Published
- Peer review status:
- Peer reviewed
- Version:
- Accepted manuscript
- Files:
-
-
(pdf, 1.6mb)
-
- Publisher copy:
- 10.1016/j.jad.2016.06.065
-
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- Funding agency for:
- Osipov, M
- Funding agency for:
- Palmius, NT
- Publisher:
- Elsevier Publisher's website
- Journal:
- Journal of Affective Disorders Journal website
- Volume:
- 205
- Pages:
- 225-233
- Publication date:
- 2016-06-05
- DOI:
- ISSN:
-
1573-2517
- URN:
-
uuid:8773eed7-5d0a-4f05-a0e0-0cc4380beec3
- Source identifiers:
-
631701
- Local pid:
- pubs:631701
- Copyright holder:
- de Vos et al
- Copyright date:
- 2016
- Notes:
- © 2016 The Authors. Published by Elsevier B.V. Open Access funded by Wellcome Trust under a Creative Commons license
Journal article
Daily longitudinal self-monitoring of mood variability in bipolar disorder and borderline personality disorder
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+ Research Councils UK Digital Economy Programme
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+ Research Councils UK Digital Economy Programme
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