Concordance Of Clinical & Electronic Data In Assessment of Depression: Findings From The Smartphone And Online Usage Based Evaluation For Depression (SOLVD) Study Anh Truong* MD, Jian Cao#, BS, Nidal Moukaddam* MD PhD, Asim Shah* MD, Peter Washington# BS, Ashutosh Sabharwal# PhD * #

Mental Health & Technology Opportunity Depression is a serious illness that carries significant emotional, financial, and medical burden for modern society Global lifetime prevalence of 28.8% (Whiteford et al., 2010) Treated in inpatient or outpatient settings Clinician-administered assessments Self-reported rating scale - recall bias, may be inaccurate 67% of patients with mental health disorder owned smartphones (Torous, 2014) Unique opportunity to use smartphones for monitoring and intervention

Smartphone Advantages and Challenges Pervasive, stigma-free and could bypass access barrier Intuitive and no training is required Flurry of mobile apps, most used for screening via questions-based assessment Challenges Mental health conditions are often poorly defined & understood Layperson and clinical understanding tend to differ Smartphones have many sensors – can we use that data for mental healthcare? Smartphones usage produces lots of data – how do we make sense of that data?

Smartphone And Online Usage Based Evaluation For Depression (SOLVD): Self input Sensor data PHQ-9 HAM-D HAM-A

Smartphone & Online Usage Based Evaluation For Depression (SOLVD) Pilot study SOLVD has two components: Self-input module Background information gathering re: data usage, SMS use, calls, browser use Standard clinician psychometric instruments including Patient Health Questionnaire-9 (PHQ-9), Hamilton Rating Scale for Depression (HAM- D), and Hamilton Anxiety Rating Scale (HAM-A)

SOLVD Research Questions Can we use mobile apps in clinically depressed population? Can an app be an adjunct for traditional psychiatric treatment? Was SOLVD acceptable to patients? Was SOLVD easy to use for the clinician? Do self input, sensor data, and clinician ratings match?

Results 25 patients, average age ~51 years Adherence rate to daily self-reported moods was 82.47% Show rate to in-person session: 95% Patients were comfortable with smartphone usage monitoring if only their doctors saw the data Correlations between: Self-input mood and clinician-rated depression PHQ-9 and: daily steps taken, text-messaging frequency, and time spent text messaging

Future Directions Smartphone data may be more useful in patients with more severe depression symptoms May be a valuable tool to help predict depression severity May serve as educational tool for patient and as an: Adjunct for information gathering for the physician Trial expanding to adolescent and perinatal depression

Many Thanks…