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Using a Smartphone App to Identify Clinically Relevant Behavior Trends via Symptom Report, Cognition Scores, and Exercise Levels

A Case Series

Datos Bibliográficos

ID15519348
AutoresHannah Wisniewski (0000-0002-9931-2447, Beth Israel Deaconess Medical Center), Philip Henson (0000-0001-5206-9374, Beth Israel Deaconess Medical Center), John Torous (0000-0002-5362-7937, Beth Israel Deaconess Medical Center, autor de correspondencia)
Año2019
Volumen10
Páginas652-652
Fecha de publicación2019-09-23
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaFrontiers in Psychiatry (JOURNAL)
Identificadores de la revistaISSN: 1664-0640 • E-ISSN: 1664-0640
EditorialFrontiers Media (PUBLISHER • CH)
DOI10.3389/fpsyt.2019.00652
PMID31607960
OpenAlexW2967270105
IdiomaEN
Citas recibidas8
Referencias citadas9

The use of smartphone apps for research and clinical care in mental health has become increasingly popular, especially within youth mental health. In particular, digital phenotyping, the monitoring of data streams from a smartphone to identify proxies for functional outcomes like steps, sleep, and sociability, is of interest due to the ability to monitor these multiple relevant indications of clinically symptomatic behavior. However, scientific progress in this field has been slow due to high heterogeneity among smartphone apps and lack of reproducibility. In this paper, we discuss how our division utilized a smartphone app to retrospectively identify clinically relevant behaviors in individuals with psychosis by measuring survey scores (symptom report), games (cognition scores), and step count (exercise levels). Further, we present specific cases of individuals and how the relevance of these data streams varied between them. We found that there was high variability between participants and that each individual's relevant behavior patterns relied heavily on unique data streams. This suggests that digital phenotyping has high potential to augment clinical care, as it could provide an efficient and individualized mechanism of identifying relevant clinical implications even if population-level models are not yet possible

Cognition · Internet privacy · Mental health · Population · Psychiatry · Relevance (law · Smartphone app · Clinical Psychology · Computer Science · Digital Mental Health Interventions · Medicine · Mental Health Research Topics · Psychology · Tryptophan and brain disorders

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    Open Access•Patrick D Mcgorry, Cristina Mei et al.•World Psychiatry•2022

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    Open Access•Simon Coghlan, Simon D’Alfonso•Philosophy & Technology•2021

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    Open Access•Benjamin Buck, Kevin A Hallgren et al.•Frontiers in Psychiatry•2021

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    Open Access•Max Birchwood, Jo Smith et al.•The British Journal of Psychiatry•1990

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    Stanley R Kay, Abraham Fiszbein et al.•Schizophrenia Bulletin•1987

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Obras citantes distintas8
Citas por año1,33
Intervalo de citas2020 - 2023 (4)
Velocidad de citaciónhistorical
Altamente citadoNo
Tipos de citaNeutras: 8
Ethnos_APP • Proyecto Open Source • Licencia MIT • Frontend v2.0.0 • Privacidad y Cookies • Documentación de la API: api.ethnos.app/docs • Código de la API: GitHub • DOI: 10.5281/zenodo.17049435 • Código del Frontend: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae