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The validity of smartphone data and its relationship to clinical symptomatology and brain biology: an exploratory analysis

BACKGROUND: Presently, there is very little research on the clinical validity of mental health smartphone application data, its relationship to brain biology, and its ability to inform clinical decisions. This paper seeks to explore these relationships within a sample of schizophrenic patients through the analysis of data collected on the mental health smartphone application Biewe.
OBJECTIVES: To validate mental health smartphone applications and support their potential to augment clinical practice.
METHODS: The application involved a series of 21 questions from several questionnaires including Patient Health Questionnaire-8 (PHQ-8), Generalized Anxiety Disorder-7 (GAD-7), Warning Signals Scale (WSS), Pittsburgh Sleep Quality Index, and the psychosis subscale of the Mini Mental State Examination. Data was collected over a period of 3 months, and patients attended a total of 4 clinic visits during this timeframe. Seven study participants also had brain scan data available from the BSNIP, PARDIP and Biceps studies currently in progress at MMHC which has been used for analysis. The structural MPRAGE T1 scans were processed using Free Surfer 6 in which thickness and volume measures were extracted. All statistical analyses on the data were carried out using R statistics software.
RESULTS: Clinic and application responses within the same week were not significantly different from each other. The application answers, however, appeared to be more sensitive to structural abnormalities in the brain. Symptoms defined as a lack of normal emotional responses (i.e. negative symptoms of schizophrenia) were negatively correlated to home time and positively correlated to distance travelled, which was a counterintuitive result.
CONCLUSIONS: The results show that mobile monitoring has the potential to be a valid and reliable method of data collection and that it may be able to augment clinical decision making.

Identiferoai:union.ndltd.org:bu.edu/oai:open.bu.edu:2144/31256
Date24 July 2018
CreatorsRizzuto, Conor
ContributorsLevy, Simon, Torous, John
Source SetsBoston University
Languageen_US
Detected LanguageEnglish
TypeThesis/Dissertation

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