Predicting symptom trajectories of schizophrenia using mobile sensing

Rui Wang; Emily A. Scherer; Megan Walsh; Weichen Wang; Min Hane Aung; Dror Ben-zeev; Rachel Brian; Andrew T. Campbell; Tanzeem Choudhury; Marta Hauser; John Kane

Predicting symptom trajectories of schizophrenia using mobile sensing

Rui Wang, Emily A. Scherer, Megan Walsh, Weichen Wang, Min Hane Aung, Dror Ben-zeev, Rachel Brian, Andrew T. Campbell, Tanzeem Choudhury, Marta Hauser, John Kane

Research output: Contribution to journal › Article › peer-review

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Abstract

Continuously monitoring schizophrenia patients' psychiatric symptoms is crucial for in-time intervention and treatment adjustment. The Brief Psychiatric Rating Scale (BPRS) is a survey administered by clinicians to evaluate symptom severity in schizophrenia. The CrossCheck symptom prediction system is capable of tracking schizophrenia symptoms as measured by BPRS using passive sensing from mobile phones. We present results from a randomized control trial, where passive sensing data, self-reports, and clinician administered 7-item BPRS surveys are collected from 36 outpatients with schizophrenia. We show that our system can predict a symptom scale score based on a 7-item BPRS within +1.45 error on average. Finally, we discuss how well our predictive system reflects symptoms experienced by patients by reviewing a case study.

Original language	English
Pages (from-to)	32-37
Number of pages	6
Journal	GetMobile: Mobile Computing and Communications
Volume	22
Issue number	2
Publication status	Published - 5 Sep 2018
Externally published	Yes

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http://dl.acm.org/citation.cfm?doid=3276145.3276157

Min Hane Aung
- Min.Aunguea.acuk
- School of Computing Sciences - Associate Professor in Computing Sciences
- Norwich Epidemiology Centre - Member
- Colour and Imaging Lab - Member
- Smart Emerging Technologies - Member
Person: Research Group Member, Academic, Teaching & Research

Cite this

@article{0f74348bcfee408eb4a934a11d4b47f6,

title = "Predicting symptom trajectories of schizophrenia using mobile sensing",

abstract = "Continuously monitoring schizophrenia patients' psychiatric symptoms is crucial for in-time intervention and treatment adjustment. The Brief Psychiatric Rating Scale (BPRS) is a survey administered by clinicians to evaluate symptom severity in schizophrenia. The CrossCheck symptom prediction system is capable of tracking schizophrenia symptoms as measured by BPRS using passive sensing from mobile phones. We present results from a randomized control trial, where passive sensing data, self-reports, and clinician administered 7-item BPRS surveys are collected from 36 outpatients with schizophrenia. We show that our system can predict a symptom scale score based on a 7-item BPRS within +1.45 error on average. Finally, we discuss how well our predictive system reflects symptoms experienced by patients by reviewing a case study.",

author = "Rui Wang and Scherer, {Emily A.} and Megan Walsh and Weichen Wang and Aung, {Min Hane} and Dror Ben-zeev and Rachel Brian and Campbell, {Andrew T.} and Tanzeem Choudhury and Marta Hauser and John Kane",

year = "2018",

month = sep,

day = "5",

language = "English",

volume = "22",

pages = "32--37",

journal = "GetMobile: Mobile Computing and Communications",

issn = "2375-0529",

publisher = "Association for Computing Machinery (ACM)",

number = "2",

}

Predicting symptom trajectories of schizophrenia using mobile sensing. / Wang, Rui; Scherer, Emily A.; Walsh, Megan; Wang, Weichen; Aung, Min Hane; Ben-zeev, Dror; Brian, Rachel; Campbell, Andrew T.; Choudhury, Tanzeem; Hauser, Marta; Kane, John.

In: GetMobile: Mobile Computing and Communications, Vol. 22, No. 2, 05.09.2018, p. 32-37.

Research output: Contribution to journal › Article › peer-review

TY - JOUR

T1 - Predicting symptom trajectories of schizophrenia using mobile sensing

AU - Wang, Rui

AU - Scherer, Emily A.

AU - Walsh, Megan

AU - Wang, Weichen

AU - Aung, Min Hane

AU - Ben-zeev, Dror

AU - Brian, Rachel

AU - Campbell, Andrew T.

AU - Choudhury, Tanzeem

AU - Hauser, Marta

AU - Kane, John

PY - 2018/9/5

Y1 - 2018/9/5

N2 - Continuously monitoring schizophrenia patients' psychiatric symptoms is crucial for in-time intervention and treatment adjustment. The Brief Psychiatric Rating Scale (BPRS) is a survey administered by clinicians to evaluate symptom severity in schizophrenia. The CrossCheck symptom prediction system is capable of tracking schizophrenia symptoms as measured by BPRS using passive sensing from mobile phones. We present results from a randomized control trial, where passive sensing data, self-reports, and clinician administered 7-item BPRS surveys are collected from 36 outpatients with schizophrenia. We show that our system can predict a symptom scale score based on a 7-item BPRS within +1.45 error on average. Finally, we discuss how well our predictive system reflects symptoms experienced by patients by reviewing a case study.

AB - Continuously monitoring schizophrenia patients' psychiatric symptoms is crucial for in-time intervention and treatment adjustment. The Brief Psychiatric Rating Scale (BPRS) is a survey administered by clinicians to evaluate symptom severity in schizophrenia. The CrossCheck symptom prediction system is capable of tracking schizophrenia symptoms as measured by BPRS using passive sensing from mobile phones. We present results from a randomized control trial, where passive sensing data, self-reports, and clinician administered 7-item BPRS surveys are collected from 36 outpatients with schizophrenia. We show that our system can predict a symptom scale score based on a 7-item BPRS within +1.45 error on average. Finally, we discuss how well our predictive system reflects symptoms experienced by patients by reviewing a case study.

M3 - Article

VL - 22

SP - 32

EP - 37

JO - GetMobile: Mobile Computing and Communications

JF - GetMobile: Mobile Computing and Communications

SN - 2375-0529

IS - 2

ER -

Predicting symptom trajectories of schizophrenia using mobile sensing

Abstract

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Min Hane Aung

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