Opportunities for Technology in the Self-Management of Mental Health

Transcription

1 Opportunities for Technology in the Self-Management of Mental Health

2 Mental Health Conditions: Devastating & Prevalent Debilitating and life-threatening outcomes $300 billion per year 450 million people (6% of world s population) 4 of 6 leading causes of YLDs

3 What is Bipolar Disorder? ( BD ) One of 10 most debilitating illnesses worldwide Permanent neurological damage with each relapse Poor functional outcomes Very high suicide rates 60 million people; affects men and women equally Chronic progressively worsens over a lifetime

4 Mood is Central Normal Bipolar I Depressive period feeling empty, worried inactivity tired changes in sleeping, eating suicidal thoughts Balanced period Manic period very high mood irritability racing thoughts high risk behavior sleeping less

5 Tracking (to Maintain) Stable Daily Rhythms The social rhythm metric: An instrument to quantify the daily rhythms of life. Monk, T. H., Flaherty, J. F., Frank, E., Hoskinson, K., & Kupfer, D. J. (1990). Journal of Nervous and Mental Disease, 178,

6 Challenges with the Paper-Based SRM Paper logs hinder identifying of patterns Unreliable retrospective recall Least likely to be completed when most valuable

7 Bipolar Disorder and Smartphone Monitoring: A Natural Match Individuals with BD have been early and sustained adopters of smartphone technology Smartphones can track (via self-report & sensing) clinically-relevant variables BD Symptoms Smartphone Measures High or Low Mood Increased / Decreased Pscyhomotor Activity Excessive / Reduced Activity Increased / Reduced Sleep Increased / Reduced Social Activity Self-Report Microphone Accelerometer Geo-location Social Media Patterns Light Sensor Smartphone Use

8 MoodRhythm Smartphone Application Development and Evaluation of a Smartphone-Based Measure of Social Rhythms for Bipolar Disorder. Matthews, M., Abdullah, S., Murnane, E., Voida, S., Choudhury, T., Gay, G., & Frank, E.(2016). Journal of Assessment. In situ design for mental illness: Considering the pathology of bipolar disorder in mhealth design. Matthews, M., Voida, S., Abdullah, S., Doherty, G., Choudhury, T., Im, S., & Gay, G. (2015). In Proceedings of the 17th International Conference on Human-Computer Interaction with Mobile Devices and Services (pp ). ACM.

9 Participatory Design Individuals with BD Clinicians Professional psychological researchers

10 MoodRhythm s Self-Report Screen

11 MoodRhythm s Feedback Screen

12 MoodRhythm s Feedback Screen I like the rewards I think the badges are kind of cool Yes, I LOVE badges I got the badges. It gives me personal satisfaction that I have completed something. And, that s good. It keeps motivating.

13 Informing Design from Extant Practices & Lived Experiences Indicators, tools, motives Perceived benefits & challenges (Un-met) needs Self-Monitoring Practices, Attitudes, and Needs of Individuals with Bipolar Disorder: Implications for the Design of Technologies to Manage Mental Health. Murnane, E. L. Cosley, D., Chang, P., Guha, S., Frank, E., Gay, G., & Matthews, M. (2016). Journal of the American Medical Informatics Association (JAMIA), 23(3), pp Quantifying the Changeable Self: The role of self-tracking in coming to terms with and managing bipolar disorder. Matthews, M, Murnane, E. L. & Snyder, J. (2017). Under revision in Journal of Human-Computer Interaction.

14 What are people tracking? % 43.4% % % 21.5% 21.9% Mood Sleep Finance Exercise Sociability

15 How are people tracking? % % 2.7% 0.5% 6.9% 14.3% 26.9% 21.8% 32.3% 33.8% 35.6% 53.9% 31.8% 54.7% 36.5% 36.2% 33.2% 29.2% 24.9% 18.4% Mood Sleep Finance Exercise Sociability Social Feedback Mentally Technology Paper

16 Custom Tracking Setups

17 Why are people tracking? Fosters clinical interactions Promotes self-awareness, reflection, empowerment Enables pro-active condition management

18 Design Guidelines

19 From Paper to Smartphone to Sensor Social activity (built-in microphone) Physical activity (accelerometers) Location (GPS + WiFi + Cellular)

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21 Symptoms Manifest through Usage Patterns The Double-Edged Sword: A Mixed Methods Study Of The Interplay Between Bipolar Disorder and Technology Use. Matthews, M., Murnane, E. L.,Snyder, J., Guha, S., Chang, P., & Doherty, G., Gay, G. Under review in Computers in Human Behavior.

22 Evaluation and Acceptability Generalized model predicts SRM score (range 0-7) with Root Mean Square Error (RMSE) = 1.40 Personalized models: RMSE = 0.92 Classification (stable vs. unstable): precision = 0.85, recall = 0.86 Automatic detection of social rhythms in bipolar disorder. Abdullah, S., Matthews, M., Frank, E., Doherty, G., Gay, G. & Choudhury, T. (2016). Journal of the American Medical Informatics Association (JAMIA), 23(3), pp

23 Evaluation and Acceptability

24 Closing the Loop: Feedback & Intervention

25 Take-Aways & Considerations Characteristics of mental illness and patient experience can have an important impact on the design of digital interventions Smartphone solutions for self-tracking, passive sensing, and tailored intervention Weigh design tensions & take a do no harm approach

26 Take-Aways & Considerations Characteristics of mental illness and patient experience can have an important impact on the design of digital interventions Smartphone solutions for self-tracking, passive sensing, and tailored intervention Weigh design tensions & take a do no harm approach

27 Take-Aways & Considerations Characteristics of mental illness and patient experience can have an important impact on the design of digital interventions Smartphone solutions for self-tracking, passive sensing, and tailored intervention Weigh design tensions & take a do no harm approach

28 Thank You! Questions? Characteristics of mental illness and patient experience can have an important impact on the design of digital interventions Smartphone solutions for self-tracking, passive sensing, and tailored intervention Weigh design tensions & take a do no harm approach Opportunities for Technology in the Self-Management of Mental Health Elizabeth Murnane elm236@cornell.edu