| Title | Neurobehavioral Symptoms and Heart Rate Variability: Feasibility of Remote Collection Using Mobile Health Technology. | ||
| Author | Nabasny, Andrew; Rabinowitz, Amanda; Wright, Brittany; Wang, Jijia; Preminger, Samuel; Terhorst, Lauren; Juengst, Shannon B | ||
| Journal | J Head Trauma Rehabil | Publication Year/Month | 2022-May-Jun |
| PMID | 35125433 | PMCID | PMC9203863 |
| Affiliation | 1.Departments of Applied Clinical Research (Mr Nabasny and Drs Wright, Wang, and Juengst) and Physical Medicine and Rehabilitation (Drs Wright and Juengst and Mr Preminger), University of Texas Southwestern Medical Center, Dallas; Moss Rehabilitation, Philadelphia, Pennsylvania (Dr Rabinowitz); and Department of Occupational Therapy, University of Pittsburgh, and Center for Clinical and Translational Science Institute, University of Pittsburgh, Pittsburgh, Pennsylvania (Dr Terhorst). | ||
OBJECTIVES: To determine the covariance of heart rate variability (HRV) and self-reported neurobehavioral symptoms after traumatic brain injury (TBI) collected using mobile health (mHealth) technology. SETTING: Community. PARTICIPANTS: Adults with lifetime history of TBI (n = 52) and adults with no history of brain injury (n = 12). DESIGN: Two-week prospective ecological momentary assessment study. MAIN MEASURES: Behavioral Assessment Screening Tool (BASTmHealth) subscales (Negative Affect, Fatigue, Executive Dysfunction, Substance Abuse, and Impulsivity) measured frequency of neurobehavioral symptoms via a RedCap link sent by text message. Resting HRV (root mean square of successive R-R interval differences) was measured for 5 minutes every morning upon waking using a commercially available heart rate monitor (Polar H10, paired with Elite HRV app). RESULTS: Data for n = 48 (n = 38 with TBI; n = 10 without TBI) participants were included in covariance analyses, with average cross-correlation coefficients (0-day lag) varying greatly across participants. We found that the presence and direction of the relationship between HRV and neurobehavioral symptoms varied from person to person. Cross-correlation coefficients r </= -0.30, observed in 27.1% to 29.2% of participants for Negative Affect, Executive Dysfunction, and Fatigue, 22.9% of participants for Impulsivity, and only 10.4% of participants for Substance Abuse, supported our hypothesis that lower HRV would covary with more frequent symptoms. However, we also found 2.0% to 20.8% of participants had positive cross-correlations (r >/= 0.30) across all subscales, indicating that higher HRV may sometimes correlate with more neurobehavioral symptoms, and 54.2% to 87.5% had no significant cross-correlations. CONCLUSIONS: It is generally feasible for community-dwelling adults with and without TBI to use a commercially available wearable device to capture daily HRV measures and to complete a short, electronic self-reported neurobehavioral symptom measure for a 2-week period. The covariance of HRV and neurobehavioral symptoms over time suggests that HRV could be used as a relevant physiological biomarker of neurobehavioral symptoms, though how it would be interpreted and used in practice would vary on a person-by-person and symptom domain basis and requires further study.