Digital phenotyping for assessment and prediction of mental health outcomes: A scoping review protocol
File(s)DigitalPhenotypingForAssessmentAndPrediction.pdf (355.71 KB)
Published version
Author(s)
Spinazze, Pier
Rykov, Yuri
Bottle, Robert
Car, Josip
Type
Journal Article
Abstract
Introduction: Rapid advancements in technology and the ubiquity of personal mobile digital devices have brought forth innovative methods of acquiring healthcare data. Smartphones can capture vast amounts of data both passively through inbuilt sensors or connected devices and actively via user engagement. This scoping review aims to evaluate evidence to date on the use of passive digital sensing/phenotyping in assessment and prediction of mental health.Methods and analysis: The methodological framework proposed by Arksey and O’Malley will be used to conduct the review following the five-step process. A three-step search strategy will be used: 1. Initial limited search of online databases namely, MEDLINE for literature on digital phenotyping or sensing for key terms; 2. Comprehensive literature search using all identified keywords, across all relevant electronic databases: IEEE Xplore, MEDLINE, the Cochrane Database of Systematic Reviews, PubMed, the ACM Digital Library and Web of Science Core Collection (Science Citation Index Expanded and Social Sciences Citation Index), Scopus; and 3. Snowballing approach using the reference and citing lists of all identified key conceptual papers and primary studies. Data will be charted and sorted using a thematic analysis approach.Ethics and Dissemination: The findings from this systematic scoping review will be reported at scientific meetings and published in a peer-reviewed journal.
Date Issued
2019-12-30
Date Acceptance
2019-12-13
Citation
BMJ Open, 2019, 9 (12)
ISSN
2044-6055
Publisher
BMJ Journals
Journal / Book Title
BMJ Open
Volume
9
Issue
12
Copyright Statement
© Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
Subjects
Depression & mood disorders
MENTAL HEALTH
digital phenotyping
sensing
1103 Clinical Sciences
1117 Public Health and Health Services
1199 Other Medical and Health Sciences
Publication Status
Published
Article Number
e032255
Date Publish Online
2019-12-30