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      GPS mobility as a digital biomarker of negative symptoms in schizophrenia: a case control study

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          Abstract

          Mobility is an important correlate of physical, cognitive, and mental health in chronic illness, and can be measured passively with mobile phone global positional satellite (GPS) sensors. To date, GPS data have been reported in a few studies of schizophrenia, yet it is unclear whether these data correlate with concurrent momentary reports of location, vary by people with schizophrenia and healthy comparison subjects, or associate with symptom clusters in schizophrenia. A total of 142 participants with schizophrenia ( n = 86) or healthy comparison subjects ( n = 56) completed 7 days of ecological momentary assessment (EMA) reports of location and behavior, and simultaneous GPS locations were tracked every five minutes. We found that GPS-derived indicators of average distance travelled overall and distance from home, as well as percent of GPS samples at home were highly correlated with EMA reports of location at the day- and week-averaged level. GPS-based mobility indicators were lower in schizophrenia with medium to large effect sizes. Less GPS mobility was related to greater negative symptom severity, particularly diminished motivation, whereas greater GPS mobility was weakly associated with more community functioning. Neurocognition, depression, and positive symptoms were not associated with mobility indicators. Therefore, passive GPS sensing could provide a low-burden proxy measure of important outcomes in schizophrenia, including negative symptoms and possibly of functioning. As such, passive GPS sensing could be used for monitoring and timely interventions for negative symptoms in young persons at high risk for schizophrenia.

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          Most cited references18

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          Relapse prediction in schizophrenia through digital phenotyping: a pilot study

          Among individuals diagnosed, hospitalized, and treated for schizophrenia, up to 40% of those discharged may relapse within 1 year even with appropriate treatment. Passively collected smartphone behavioral data present a scalable and at present underutilized opportunity to monitor patients in order to identify possible warning signs of relapse. Seventeen patients with schizophrenia in active treatment at a state mental health clinic in Boston used the Beiwe app on their personal smartphone for up to 3 months. By testing for changes in mobility patterns and social behavior over time as measured through smartphone use, we were able to identify statistically significant anomalies in patient behavior in the days prior to relapse. We found that the rate of behavioral anomalies detected in the 2 weeks prior to relapse was 71% higher than the rate of anomalies during other time periods. Our findings show how passive smartphone data, data collected in the background during regular phone use without active input from the subjects, can provide an unprecedented and detailed view into patient behavior outside the clinic. Real-time detection of behavioral anomalies could signal the need for an intervention before an escalation of symptoms and relapse occur, therefore reducing patient suffering and reducing the cost of care.
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            Mobile Sensing in Environmental Health and Neighborhood Research

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              Measuring life space in older adults with mild-to-moderate Alzheimer's disease using mobile phone GPS.

              As an indicator of physical and cognitive functioning in community-dwelling older adults, there is increasing interest in measuring life space, defined as the geographical area a person covers in daily life. Typically measured through questionnaires, life space can be challenging to assess in amnestic dementia associated with Alzheimer's disease (AD). While global positioning system (GPS) technology has been suggested as a potential solution, there remains a lack of data validating GPS-based methods to measure life space in cognitively impaired populations. The purpose of the study was to evaluate the construct validity of a GPS system to provide quantitative measurements of global movement for individuals with mild-to-moderate AD. Nineteen community-dwelling older adults with mild-to-moderate AD (Mini-Mental State Examination score 14-28, age 70.7 ± 2.2 years) and 33 controls (CTL; age 74.0 ± 1.2 years) wore a GPS-enabled mobile phone during the day for 3 days. Measures of geographical territory (area, perimeter, mean distance from home, and time away from home) were calculated from the GPS log. Following a log-transformation to produce symmetrical distributions, group differences were tested using two-sample t tests. Construct validity of the GPS measures was tested by examining the correlation between the GPS measures and indicators of physical function [steps/day, gait velocity, and Disability Assessment for Dementia (DAD)] and affective state (Apathy Evaluation Scale and Geriatric Depression Scale). Multivariate regression was performed to evaluate the relative strength of significantly correlated factors. GPS-derived area (p < 0.01), perimeter (p < 0.01), and mean distance from home (p < 0.05) were smaller in the AD group compared to CTL. The correlation analysis found significant associations of the GPS measures area and perimeter with all measures of physical function (steps/day, DAD, and gait velocity; p < 0.01), symptoms of apathy (p < 0.01), and depression (p < 0.05). Multivariate regression analysis indicated that gait velocity and dependence were the strongest variables associated with GPS measures. This study demonstrated that GPS-derived area and perimeter: (1) distinguished mild-to-moderate AD patients from CTL and (2) were strongly correlated with physical function and affective state. These findings confirm the ability of GPS technology to assess life space behaviour and may be particularly valuable to continuously monitor functional decline associated with neurodegenerative disease, such as AD.
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                Author and article information

                Contributors
                +858 822 4251 , cdepp@ucsd.edu
                Journal
                NPJ Digit Med
                NPJ Digit Med
                NPJ Digital Medicine
                Nature Publishing Group UK (London )
                2398-6352
                8 November 2019
                8 November 2019
                2019
                : 2
                : 108
                Affiliations
                [1 ]ISNI 0000 0001 2107 4242, GRID grid.266100.3, Department of Psychiatry, , UC San Diego, ; La Jolla, CA USA
                [2 ]Psychology Service, VA San Diego, San Diego, CA USA
                [3 ]ISNI 0000 0001 2171 9311, GRID grid.21107.35, Johns Hopkins School of Nursing, ; Baltimore, MD USA
                [4 ]ISNI 0000 0001 2106 639X, GRID grid.412041.2, National Center for Scientific Research, , University of Bordeaux (UMR 5287); EPHE PSL Research University, ; Bordeaux, France
                [5 ]ISNI 0000 0004 1936 8606, GRID grid.26790.3a, Department of Psychiatry and Behavioral Sciences, , University of Miami, ; Miami, FL USA
                Article
                182
                10.1038/s41746-019-0182-1
                6841669
                31728415
                5f75c009-88e1-4495-8f16-7657a815ac58
                © The Author(s) 2019

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 14 March 2019
                : 23 September 2019
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                © The Author(s) 2019

                health care,medical research
                health care, medical research

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