Using artificial intelligence and longitudinal location data to differentiate persons who develop posttraumatic stress disorder following childhood trauma

Abstract Post-traumatic stress disorder (PTSD) is characterized by complex, heterogeneous symptomology, thus detection outside traditional clinical contexts is difficult. Fortunately, advances in mobile technology, passive sensing, and analytics offer promising avenues for research and development....

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Autores principales:	Damien Lekkas, Nicholas C. Jacobson
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/afee207b554f4a2c9aace1cf2520d977
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spelling	oai:doaj.org-article:afee207b554f4a2c9aace1cf2520d9772021-12-02T16:50:17ZUsing artificial intelligence and longitudinal location data to differentiate persons who develop posttraumatic stress disorder following childhood trauma10.1038/s41598-021-89768-22045-2322https://doaj.org/article/afee207b554f4a2c9aace1cf2520d9772021-05-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-89768-2https://doaj.org/toc/2045-2322Abstract Post-traumatic stress disorder (PTSD) is characterized by complex, heterogeneous symptomology, thus detection outside traditional clinical contexts is difficult. Fortunately, advances in mobile technology, passive sensing, and analytics offer promising avenues for research and development. The present study examined the ability to utilize Global Positioning System (GPS) data, derived passively from a smartphone across seven days, to detect PTSD diagnostic status among a cohort (N = 185) of high-risk, previously traumatized women. Using daily time spent away and maximum distance traveled from home as a basis for model feature engineering, the results suggested that diagnostic group status can be predicted out-of-fold with high performance (AUC = 0.816, balanced sensitivity = 0.743, balanced specificity = 0.8, balanced accuracy = 0.771). Results further implicate the potential utility of GPS information as a digital biomarker of the PTSD behavioral repertoire. Future PTSD research will benefit from application of GPS data within larger, more diverse populations.Damien LekkasNicholas C. JacobsonNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-10 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Damien Lekkas Nicholas C. Jacobson Using artificial intelligence and longitudinal location data to differentiate persons who develop posttraumatic stress disorder following childhood trauma
description	Abstract Post-traumatic stress disorder (PTSD) is characterized by complex, heterogeneous symptomology, thus detection outside traditional clinical contexts is difficult. Fortunately, advances in mobile technology, passive sensing, and analytics offer promising avenues for research and development. The present study examined the ability to utilize Global Positioning System (GPS) data, derived passively from a smartphone across seven days, to detect PTSD diagnostic status among a cohort (N = 185) of high-risk, previously traumatized women. Using daily time spent away and maximum distance traveled from home as a basis for model feature engineering, the results suggested that diagnostic group status can be predicted out-of-fold with high performance (AUC = 0.816, balanced sensitivity = 0.743, balanced specificity = 0.8, balanced accuracy = 0.771). Results further implicate the potential utility of GPS information as a digital biomarker of the PTSD behavioral repertoire. Future PTSD research will benefit from application of GPS data within larger, more diverse populations.
format	article
author	Damien Lekkas Nicholas C. Jacobson
author_facet	Damien Lekkas Nicholas C. Jacobson
author_sort	Damien Lekkas
title	Using artificial intelligence and longitudinal location data to differentiate persons who develop posttraumatic stress disorder following childhood trauma
title_short	Using artificial intelligence and longitudinal location data to differentiate persons who develop posttraumatic stress disorder following childhood trauma
title_full	Using artificial intelligence and longitudinal location data to differentiate persons who develop posttraumatic stress disorder following childhood trauma
title_fullStr	Using artificial intelligence and longitudinal location data to differentiate persons who develop posttraumatic stress disorder following childhood trauma
title_full_unstemmed	Using artificial intelligence and longitudinal location data to differentiate persons who develop posttraumatic stress disorder following childhood trauma
title_sort	using artificial intelligence and longitudinal location data to differentiate persons who develop posttraumatic stress disorder following childhood trauma
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/afee207b554f4a2c9aace1cf2520d977
work_keys_str_mv	AT damienlekkas usingartificialintelligenceandlongitudinallocationdatatodifferentiatepersonswhodevelopposttraumaticstressdisorderfollowingchildhoodtrauma AT nicholascjacobson usingartificialintelligenceandlongitudinallocationdatatodifferentiatepersonswhodevelopposttraumaticstressdisorderfollowingchildhoodtrauma
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Using artificial intelligence and longitudinal location data to differentiate persons who develop posttraumatic stress disorder following childhood trauma

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