Compliance Using Mobile Health Heart Rate Variability and Ecological Momentary Assessment Tools in a Chronic Traumatic Brain Injury Sample

2021 ◽  
Vol 102 (10) ◽  
pp. e70-e71
Author(s):  
Andrew Nabasny ◽  
Samrudhi Mishra ◽  
Lexis Khetsavanh ◽  
Mason Kitchens ◽  
Samuel Preminger ◽  
...  
2021 ◽  
Vol 36 (6) ◽  
pp. 1160-1160
Author(s):  
Julianne Wilson ◽  
Amanda R Rabinowitz ◽  
Tessa Hart

Abstract Objective In persons with moderate–severe traumatic brain injury (msTBI), we compared traditional measures of mood with dynamic measures of affect derived from ecological momentary assessment (EMA), for the purpose of validating the EMA indices and exploring their unique contributions to emotional assessment. Method 23 community-dwelling participants with chronic msTBI were enrolled in a treatment trial for anxiety and/ or depression. At baseline, participants completed the Brief Symptom Inventory-18 Depression and Anxiety subscales (BSI-D, BSI-A) and the Environmental Reward Observation Scale (EROS), a measure of everyday pleasure and reward. EMA data, including the Positive and Negative Affect Scale (PANAS), were collected via smartphone 5 times daily for 7–14 days prior to treatment (M = 8.65; SD = 1.87). Spearman correlations tested associations between baseline BSI-D, BSI-A, and EROS scores with both overall means and temporal variability measures for positive and negative affect (PA, NA). Results Mean PA was significantly correlated with BSI-D (rho −0.60, p < 0.05) and EROS (rho 0.72, p < 0.01). Mean NA and affect variability measures were uncorrelated with baseline scores. NA mean and variability were intercorrelated (rho 0.87, p < 0.001), but this was not the case for PA. Conclusion EMA measures of averaged positive affect showed robust relationships with retrospective measures of depression and environmental reward, providing support for the validity of EMA measures of PA, and for use of the EROS in msTBI. While negative findings must be interpreted with caution, the lack of association of affective variability with retrospective measures suggest a unique role for EMA in examining temporal dynamics of affect.


Brain Injury ◽  
2015 ◽  
Vol 29 (11) ◽  
pp. 1351-1361 ◽  
Author(s):  
Shannon B. Juengst ◽  
Kristin M. Graham ◽  
I. Wayan Pulantara ◽  
Michael McCue ◽  
Ellen M. Whyte ◽  
...  

Neurology ◽  
2019 ◽  
Vol 93 (14 Supplement 1) ◽  
pp. S2.2-S2
Author(s):  
Harrison Seltzer ◽  
Karim Elghawy ◽  
Robert Baker

ObjectiveUse biofeedback measures to manage a patient's long term recovery from concussion.BackgroundSports-related mild traumatic brain injury (MTBI) is estimated to affect 3.8 million people in the United States. Identifying quantitative measures of recovery has become a point of interest in treatment. Heart Rate Variability (HRV), the average fluctuation in the interval between heartbeats, shows promise as a noninvasive biomarker.Design/MethodsCase report following cardiovascular recovery of a 15 year old cross country runner 4 months post-injury. Average heart rate and maximum heart rate per training session were collected from the patient's smart device.ResultsA 15-year-old Caucasian male cross-country runner hit the back of his head during a soccer game suffering an MTBI. The patient rested from the activity for 1 week then returned to training. Two months after the injury the patient complained of persistent shortness of breath, fatigue, and increased heart rate while running. According to the patient, his average BPM while running prior to the injury was in the 160s. The patient's smart device post-concussion reports a spike into the 180s. 3 months post-concussion the patient was instructed to keep his heart rate below 170 during training. In the following month, the patient's condition improved gradually with a return to baseline activity.ConclusionsHRV is a promising point of investigation for the management of post-concussive symptoms. Further research is necessary to elucidate the long term effects of concussion on heart rate variability.


Author(s):  
Larry Chan ◽  
Vedant Das Swain ◽  
Christina Kelley ◽  
Kaya de Barbaro ◽  
Gregory D. Abowd ◽  
...  

Biofeedback ◽  
2015 ◽  
Vol 43 (1) ◽  
pp. 27-30 ◽  
Author(s):  
Andrea Reid-Chung ◽  
Michael Thompson ◽  
Lynda Thompson

This paper discusses the clinical applications of heart rate variability (HRV) data in the treatment of clients who have experienced traumatic brain injuries (TBIs). In the authors' clinical practice, HRV data is collected at the initial assessment, at progress assessments, and again after the completion of a course of neurofeedback combined with HRV biofeedback treatment. This paper describes HRV seen in healthy individuals compared to HRV in individuals known to have experienced a TBI. Three clinical case examples are discussed that explore the changes in heart rate variability following traumatic brain injury as well as improvements noted during, and following, a course of neurofeedback combined with HRV biofeedback training. The cases illustrated in this paper demonstrate the impressive changes in heart rate variability that can occur following a traumatic brain injury and also highlight how neurofeedback combined with biofeedback training can be used to improve heart rate variability and ameliorate related cognitive symptoms.


2000 ◽  
Vol 28 (12) ◽  
pp. 3907-3912 ◽  
Author(s):  
Abhik K. Biswas ◽  
William A. Scott ◽  
John F. Sommerauer ◽  
Peter M. Luckett

2016 ◽  
Vol 38 (3) ◽  
pp. 282-291 ◽  
Author(s):  
David M. Williams ◽  
Shira Dunsiger ◽  
Jessica A. Emerson ◽  
Chad J. Gwaltney ◽  
Peter M. Monti ◽  
...  

Affective response to exercise may mediate the effects of self-paced exercise on exercise adherence. Fiftynine low-active (exercise <60 min/week), overweight (body mass index: 25.0–39.9) adults (ages 18–65) were randomly assigned to self-paced (but not to exceed 76% maximum heart rate) or prescribed moderate intensity exercise (64–76% maximum heart rate) in the context of otherwise identical 6-month print-based exercise promotion programs. Frequency and duration of exercise sessions and affective responses (good/bad) to exercise were assessed via ecological momentary assessment throughout the 6-month program. A regression-based mediation model was used to estimate (a) effects of experimental condition on affective response to exercise (path a = 0.20, SE = 0.28, f2 = 0.02); (b) effects of affective response on duration/latency of the next exercise session (path b = 0.47, SE = 0.25, f2 = 0.04); and (c) indirect effects of experimental condition on exercise outcomes via affective response (path ab = 0.11, SE = 0.06, f2 = 0.10). Results provide modest preliminary support for a mediational pathway linking self-paced exercise, affective response, and exercise adherence.


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