University Presentation Showcase: Undergraduate Division
Using Smartwatch Physiological Data as a Predictor of Mental Health
Presenter Hometown
Richmond, KY
Major
Psychology
Department
Psychology
Degree
Undergraduate
Mentor
Dan Florell
Mentor Department
Psychology
Recommended Citation
Zampardo, Alexandra L.; Ruley, Hannahlee; Bartley, Kayleigh R.; and Bryden, Erik A., "Using Smartwatch Physiological Data as a Predictor of Mental Health" (2026). University Presentation Showcase Event. 13.
https://encompass.eku.edu/swps/2026/undergraduate/13
Abstract
Exploring the Apple Watch’s efficacy to detect symptoms of anxiety and depression using physiological data. Previous research on the topic notes lower heart rate variability (HRV) is associated with increased symptoms of depression and anxiety. We hypothesize that low HRV is correlated with lower instances of self-reported anxiety, and high HRV is correlated with higher instances of self-reported anxiety. Method: The Generalized Anxiety Disorder Questionnaire (GAD-7) and the Patient Health Questionnaire (PHQ-9) are combined into the PHQ-ADS. Participants completed a baseline PHQ-ADS during the onboarding phase. Participants wore the Apple Watch for 2 weeks and shared heart rate (HR), HRV, sleep duration, and sleep stages via Amissa Health. Daily PHQ-ADS Qualtrics surveys gauged anxiety and depression symptoms. During the exit phase, participants took a final PHQ-ADS. The study is still ongoing, but has preliminary data that has been analyzed. We hope that the findings support our hypothesis and show potential for wearable devices as an early intervention tool for mental health disorders and promote positive physical and mental health via monitoring.
Presentation format
Poster
Using Smartwatch Physiological Data as a Predictor of Mental Health
Exploring the Apple Watch’s efficacy to detect symptoms of anxiety and depression using physiological data. Previous research on the topic notes lower heart rate variability (HRV) is associated with increased symptoms of depression and anxiety. We hypothesize that low HRV is correlated with lower instances of self-reported anxiety, and high HRV is correlated with higher instances of self-reported anxiety. Method: The Generalized Anxiety Disorder Questionnaire (GAD-7) and the Patient Health Questionnaire (PHQ-9) are combined into the PHQ-ADS. Participants completed a baseline PHQ-ADS during the onboarding phase. Participants wore the Apple Watch for 2 weeks and shared heart rate (HR), HRV, sleep duration, and sleep stages via Amissa Health. Daily PHQ-ADS Qualtrics surveys gauged anxiety and depression symptoms. During the exit phase, participants took a final PHQ-ADS. The study is still ongoing, but has preliminary data that has been analyzed. We hope that the findings support our hypothesis and show potential for wearable devices as an early intervention tool for mental health disorders and promote positive physical and mental health via monitoring.
