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Digital phenotyping for assessment and prediction of mental health outcomes: a scoping review protocol

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 engage...

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Autores principales: Spinazze, Pier, Rykov, Yuri, Bottle, Alex, Car, Josip
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6955549/
https://www.ncbi.nlm.nih.gov/pubmed/31892655
http://dx.doi.org/10.1136/bmjopen-2019-032255
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author Spinazze, Pier
Rykov, Yuri
Bottle, Alex
Car, Josip
author_facet Spinazze, Pier
Rykov, Yuri
Bottle, Alex
Car, Josip
author_sort Spinazze, Pier
collection PubMed
description 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.
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spelling pubmed-69555492020-01-27 Digital phenotyping for assessment and prediction of mental health outcomes: a scoping review protocol Spinazze, Pier Rykov, Yuri Bottle, Alex Car, Josip BMJ Open Mental Health 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. BMJ Publishing Group 2019-12-30 /pmc/articles/PMC6955549/ /pubmed/31892655 http://dx.doi.org/10.1136/bmjopen-2019-032255 Text en © 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/.
spellingShingle Mental Health
Spinazze, Pier
Rykov, Yuri
Bottle, Alex
Car, Josip
Digital phenotyping for assessment and prediction of mental health outcomes: a scoping review protocol
title Digital phenotyping for assessment and prediction of mental health outcomes: a scoping review protocol
title_full Digital phenotyping for assessment and prediction of mental health outcomes: a scoping review protocol
title_fullStr Digital phenotyping for assessment and prediction of mental health outcomes: a scoping review protocol
title_full_unstemmed Digital phenotyping for assessment and prediction of mental health outcomes: a scoping review protocol
title_short Digital phenotyping for assessment and prediction of mental health outcomes: a scoping review protocol
title_sort digital phenotyping for assessment and prediction of mental health outcomes: a scoping review protocol
topic Mental Health
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6955549/
https://www.ncbi.nlm.nih.gov/pubmed/31892655
http://dx.doi.org/10.1136/bmjopen-2019-032255
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