The Journal of head trauma rehabilitation · 2022
Neurobehavioral Symptoms and Heart Rate Variability: Feasibility of Remote Collection Using Mobile Health Technology.
СтатьяПоддержка NIH: внешняя программаНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Nabasny Andrew, Rabinowitz Amanda, Wright Brittany, Wang Jijia, Preminger Samuel, Terhorst Lauren, Juengst Shannon B
Аннотация
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.
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.