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Capturing behavioral indicators of persecutory ideation using mobile technology.
Buck, Benjamin; Hallgren, Kevin A; Scherer, Emily; Brian, Rachel; Wang, Rui; Wang, Weichen; Campbell, Andrew; Choudhury, Tanzeem; Hauser, Marta; Kane, John M; Ben-Zeev, Dror.
Afiliação
  • Buck B; Health Services Research & Development, Puget Sound VA Healthcare System, Seattle, WA, USA; Department of Health Services, School of Public Health, Univ. of Washington, Seattle, WA, USA; Behavioral Research in Technology and Engineering (BRiTE) Center, Department of Psychiatry and Behavioral Sci
  • Hallgren KA; Behavioral Research in Technology and Engineering (BRiTE) Center, Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, USA.
  • Scherer E; Geisel School of Medicine, Dartmouth College, Hanover, NH, USA.
  • Brian R; Behavioral Research in Technology and Engineering (BRiTE) Center, Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, USA.
  • Wang R; Department of Computer Science, Dartmouth College, Hanover, NH, USA.
  • Wang W; Department of Computer Science, Dartmouth College, Hanover, NH, USA.
  • Campbell A; Department of Computer Science, Dartmouth College, Hanover, NH, USA.
  • Choudhury T; Department of Information Science, Cornell University, Ithaca, NY, USA.
  • Hauser M; The Zucker Hillside Hospital, Northwell Health, Glen Oaks, NY, USA; Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA.
  • Kane JM; The Zucker Hillside Hospital, Northwell Health, Glen Oaks, NY, USA; Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA.
  • Ben-Zeev D; Behavioral Research in Technology and Engineering (BRiTE) Center, Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, USA.
J Psychiatr Res ; 116: 112-117, 2019 09.
Article em En | MEDLINE | ID: mdl-31226579
ABSTRACT
Most existing measures of persecutory ideation (PI) rely on infrequent in-person visits, and this limits their ability to assess rapid changes or real-world functioning. Mobile health (mHealth) technology may address these limitations. Little is known about passively sensed behavioral indicators associated with PI. In the current study, sixty-two participants with schizophrenia spectrum disorders completed momentary assessments of PI on a smartphone that also passively collected behavioral data for one year. Results suggested that PI was prevalent (n = 50, 82% of sample) but had infrequent incidence (25.2% of EMA responses). PI was also associated with changes in several passively sensed variables, including decreases in distance traveled (Mkilometers = -1.20, SD = 18.88), time spent in a vehicle (Mminutes = -4.15, SD = 49.59), length of outgoing phone calls (Mminutes = -0.79, SD = 13.13), time spent proximal to human speech (Mminutes = -6.26, SD = 153.03), and an increase in time sitting still (Mminutes = 4.04, SD = 94.69). The present study suggests changes associated with PI may be detectable by passive sensors, including reductions in moving or traveling, and time spent around others or in self-initiated phone conversations. These constructs might constitute risk for PI.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Transtornos Paranoides / Transtornos Psicóticos / Telemedicina / Aplicativos Móveis / Smartphone / Avaliação Momentânea Ecológica Idioma: En Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Transtornos Paranoides / Transtornos Psicóticos / Telemedicina / Aplicativos Móveis / Smartphone / Avaliação Momentânea Ecológica Idioma: En Ano de publicação: 2019 Tipo de documento: Article