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Evaluation ViewAttendees 4

Technology/Digital Health
Symposia

Symposium 10 - Broadening the Reach of Passive Sensing: Insights and Lessons Learned from Clinical Researchers

Friday, November 15, 2024
8:30 AM – 10:00 AM EST
Location: Liberty B, Level 3, Marriott Downtown
CE: 1.5

Keywords: Technology / Mobile Health, Research Methods,
Level of Familiarity: All
Recommended Readings: Jacobson, Nicholas & Feng, Brandon. (2022). Digital Phenotyping of Generalized Anxiety Disorder: Using Artificial Intelligence to Accurately Predict Symptom Severity Using Wearable Sensors in Daily Life. Translational Psychiatry. https://doi.org/10.1038/s41398-022-02038-1,   Cornet, V. P., & Holden, R. J. (2018). Systematic review of smartphone-based passive sensing for health and wellbeing. Journal of biomedical informatics, 77, 120–132. https://doi.org/10.1016/j.jbi.2017.12.008,   Trifan, A., Oliveira, M., & Oliveira, J. L. (2019). Passive Sensing of Health Outcomes Through Smartphones: Systematic Review of Current Solutions and Possible Limitations. JMIR mHealth and uHealth, 7(8), e12649. https://doi.org/10.2196/12649,   ,  

With growing utilization and capabilities of technology, there is recent emphasis on integrating other passively-collected physiological data into clinical research. Passive sensing allows scientists to study variables of interest continuously, noninvasively, and in an ecological setting. A common example is the use of wearable sensors to measure heart rate, sleep, or activity. We expect continued rapid development of technologies that have significant promise for understanding psychopathology. For example, methods for ambulatory salivary and electroencephalography (EEG) analysis are already well underway. This current landscape is exciting for trainees and early career researchers, as more and more tools are available to help understand, predict, and prevent psychopathology. However, this turning point in the field also poses great challenges, as the technical and analytical skills needed to successfully collect and analyze complex, densely-sampled data are not a core part of clinical psychology training. In this symposium, we will hear from early career clinical researchers who are integrating passive sensing and/or physiological (non-subjective) data into their programs of research.  Presenter 1 will discuss saliva sampling and EEG methods as promising tools for contextualizing worry’s association with neural function across the menstrual cycle. She will discuss future directions and opportunities for continuous, real-time assessment. Presenter 2 will discuss methods for predicting psychological states (alcohol craving) from passively-collected heart rate variability data. Presenter 3 will build on this to discuss methods for predicting behavior from passively-collected data. Specifically, she uses continuous glucose monitoring to detect binge eating and vomiting among adults with eating disorders. Finally, Presenter 4 will discuss sleep monitoring via consumer wearables as a potential way to improve prediction of depression symptoms after spine surgery. In addition to sharing clinical implications, all presenters will share how they developed the skills needed to apply passive sensing and/or physiological monitoring to their areas of interest. Our discussant will synthesize the presentations, elaborate on clinical implications, and discuss future directions for integrating passive sensing and physiological monitoring into clinical research.

Learning Objectives:

At the end of this session, the learner will be able to:
  1. Describe the advantages of passive sensing and which research questions may particularly benefit from this method.
  2. Describe the current limitations of passive sensing and common pitfalls.
  3. Explain how to increase participant adherence and limit participant burden while collecting a rich dataset .
  4. Be familiar with analytic methods for highly dimensional time series data collected by passive sensing.
  5. Identify the potential clinical implications of passive sensing methods.

Presentations:

  • 8:30 AM – 10:00 AM EST
    (SYM 10) Examining Modulators of the Association Between Worry and Neurocognitive Function: A Focus on Dopamine and Estradiol

    Speaker: Courtney C. Louis, M.A. (she/her/hers) – Massachusetts General Hospital

    Co-author: Jason Moser, Ph.D. (he/him/his) – Michigan State University

  • 8:30 AM – 10:00 AM EST
    (SYM 10) Using Passive Sensing to Isolate a Biosignature for Craving Among Individuals in Early Alcohol Use Disorder Recovery

    Speaker: Sara Mei, B.S. (she/her/hers) – Colorado State University

    Co-author: Sara Mei, B.S. (she/her/hers) – Colorado State University

    Co-author: David Eddie, Ph.D. – Harvard Medical School

    Co-author: Noah N. Emery, Ph.D. – Colorado State University

  • 8:30 AM – 10:00 AM EST
    (SYM 10) Using Continuous Glucose Monitoring and Machine Learning to Passively Detect Naturalistic Binge Eating and Vomiting Among Adults with Binge-spectrum Eating Disorders: A Preliminary Investigation

    Speaker: Emily Presseller, M.S. (she/her/hers) – Drexel University

    Co-author: Elizabeth Velkoff, Ph.D. – Drexel University

    Co-author: Devyn Riddle, B.A. – Drexel University

    Co-author: Jianyi Liu, M.A. – Drexel University

    Co-author: Fengqing Zhang, Ph.D. – Drexel University

    Co-author: Adrienne Juarascio, Ph.D. (she/her/hers) – Drexel University

  • 8:30 AM – 10:00 AM EST
    (SYM 10) Sleep, Pain, and Psychopathology in Chronic Back Pain Patients: Insights from Consumer Wearables

    Speaker: Madelyn Frumkin, Ph.D. (she/her/hers) – Massachusetts General Hospital

    Co-author: Jacob Greenberg, MD – Washington University School of Medicine

    Co-author: Jingwen Zhang, MS – Washington University in St. Louis

    Co-author: Ziqi Xu, BA – Washington University in St. Louis

    Co-author: Saad Javeed, MD – Washington University School of Medicine

    Co-author: Justin Zhang, MD – University of utah

    Co-author: Kathleen Botterbush, BS – St. Louis University

    Co-author: Braeden Benedict, MS – Washington University School of Medicine

    Co-author: Wilson Ray, MD – Washington University School of Medicine

    Co-author: Chenyang Lu, PhD – Washington University in St. Louis

    Co-author: Thomas Rodebaugh, PhD – University of North Carolina at Chapel Hill