Real-time heart rate variability biofeedback amplitude during a large-scale digital mental health intervention differed by age, gender, and mental and physical health.

Autor: Aschbacher K; Meru Health, San Mateo, California, USA., Mather M; Leonard Davis School of Gerontology, University of Southern California, Los Angeles, California, USA.; Department of Psychology, University of Southern California, Los Angeles, California, USA.; Department of Biomedical Engineering, University of Southern California, Los Angeles, California, USA., Lehrer P; Department of Psychiatry, Robert Wood Johnson Medical School, Rutgers University, Monmouth Junction, New Jersey, USA., Gevirtz R; Department of Clinical Psychology, California School of Professional Psychology, Alliant International University, San Diego, California, USA., Epel E; Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, San Francisco, California, USA., Peiper NC; Meru Health, San Mateo, California, USA.; Department of Epidemiology and Population Health, University of Louisville, Louisville, Kentucky, USA.
Jazyk: angličtina
Zdroj: Psychophysiology [Psychophysiology] 2024 Jun; Vol. 61 (6), pp. e14533. Date of Electronic Publication: 2024 Mar 07.
DOI: 10.1111/psyp.14533
Abstrakt: Heart rate variability biofeedback (HRVB) is an efficacious treatment for depression and anxiety. However, translation to digital mental health interventions (DMHI) requires computing and providing real-time HRVB metrics in a personalized and user-friendly fashion. To address these gaps, this study validates a real-time HRVB feedback algorithm and characterizes the association of the main algorithmic summary metric-HRVB amplitude-with demographic, psychological, and health factors. We analyzed HRVB data from 5158 participants in a therapist-supported DMHI incorporating slow-paced breathing to treat depression or anxiety symptoms. A real-time feedback metric of HRVB amplitude and a gold-standard research metric of low-frequency (LF) power were computed for each session and then averaged within-participants over 2 weeks. We provide HRVB amplitude values, stratified by age and gender, and we characterize the multivariate associations of HRVB amplitude with demographic, psychological, and health factors. Real-time HRVB amplitude correlated strongly (r = .93, p < .001) with the LF power around the respiratory frequency (~0.1 Hz). Age was associated with a significant decline in HRVB (β = -0.46, p < .001), which was steeper among men than women, adjusting for demographic, psychological, and health factors. Resting high- and low-frequency power, body mass index, hypertension, Asian race, depression symptoms, and trauma history were significantly associated with HRVB amplitude in multivariate analyses (p's < .01). Real-time HRVB amplitude correlates highly with a research gold-standard spectral metric, enabling automated biofeedback delivery as a potential treatment component of DMHIs. Moreover, we identify demographic, psychological, and health factors relevant to building an equitable, accurate, and personalized biofeedback user experience.
(© 2024 Society for Psychophysiological Research.)
Databáze: MEDLINE
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