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Symposia
Technology/Digital Health
Madelyn Frumkin, Ph.D. (she/her/hers)
Massachusetts General Hospital
Boston, Massachusetts, United States
Jacob Greenberg, MD
Assistant Professor
Washington University School of Medicine
st. Louis, Missouri, United States
Jingwen Zhang, MS
PhD Student
Washington University in St. Louis
St. Louis, Missouri, United States
Ziqi Xu, BA
PhD Student
Washington University in St. Louis
St. Louis, Missouri, United States
Saad Javeed, MD
Resident Physician
Washington University School of Medicine
st. Louis, Missouri, United States
Justin Zhang, MD
Resident Physician
University of utah
East Salt Lake City, Utah, United States
Kathleen Botterbush, BS
Medical Student
St. Louis University
St. Louis, Missouri, United States
Braeden Benedict, MS
Medical Student
Washington University School of Medicine
St. Louis, Missouri, United States
Wilson Ray, MD
Professor
Washington University School of Medicine
st. Louis, Missouri, United States
Chenyang Lu, PhD
Professor
Washington University in St. Louis
St. Louis, Missouri, United States
Thomas Rodebaugh, PhD
professor
University of North Carolina at Chapel Hill
Chapel Hill, North Carolina, United States
Retrospective self-report data suggest approximately 50% of patients with chronic back pain (CBP) report clinical insomnia, and insomnia symptom severity is associated with worse pain, anxiety, and depression. In this study, we leveraged consumer wearables (Fitbit Inspire II), Ecological Momentary Assessment (EMA), and gold-standard self-report (PHQ-9, PROMIS measures) to clarify between- and within-person relationships between sleep, pain, and dimensions of psychopathology among individuals with CBP who were being evaluated for spine surgery (N=103). Participants wore a Fitbit for an average of 12 nights (SD=5.62), averaging 6.74 hours of sleep (SD=1.84) per night. The majority of variance in nightly sleep quantity was attributed to within-persons fluctuations (ICC=.28). Multilevel residual dynamic structural equation models suggest that neither pain nor depressed mood were strong dynamic predictors of same-night sleep quantity. However, inspection of individual-level estimates suggest each accounts for up to 30% of variance in sleep quantity for some individuals. At the between-person level, average nightly sleep quantity was uncorrelated with symptoms of pain or psychopathology. However, greater night-to-night variability was weakly associated with more severe symptoms of depression, anxiety, and pain (rs=.20-.27). Preliminary outcome data collected one year after surgery (n=69) suggest pre-surgical sleep variability accounts for unique variance in post-operative depression, after accounting for preoperative depression and postoperative pain. We will discuss several methodological considerations, including between- and within-person predictors of missing data (e.g., decreased Fitbit adherence over time, and among individuals with more psychopathology symptoms), low test-rest reliability of sleep variability estimates across 5-day periods (r=.44), and reliability of within-person parameters derived from Fitbit and EMA data.