TY - JOUR
T1 - Neurobehavioral Symptoms and Heart Rate Variability
T2 - Feasibility of Remote Collection Using Mobile Health Technology PhD, CRC
AU - Nabasny, Andrew
AU - Rabinowitz, Amanda
AU - Wright, Brittany
AU - Wang, Jijia
AU - Preminger, Samuel
AU - Terhorst, Lauren
AU - Juengst, Shannon B.
N1 - Publisher Copyright:
© 2022 Lippincott Williams and Wilkins. All rights reserved.
PY - 2022/5/1
Y1 - 2022/5/1
N2 - 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.
AB - 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.
KW - EMA
KW - ecological momentary assessment
KW - heart rate variability
KW - mHealth
KW - neurobehavioral
KW - traumatic brain injury
UR - http://www.scopus.com/inward/record.url?scp=85132453791&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85132453791&partnerID=8YFLogxK
U2 - 10.1097/HTR.0000000000000764
DO - 10.1097/HTR.0000000000000764
M3 - Article
C2 - 35125433
AN - SCOPUS:85132453791
SN - 0885-9701
VL - 37
SP - 178
EP - 188
JO - Journal of Head Trauma Rehabilitation
JF - Journal of Head Trauma Rehabilitation
IS - 3
ER -