1. 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 * #

2. 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

3. 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?

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

5. 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)

6. 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?

7. 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

8. 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

9. Many Thanks…