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

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...

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Bibliographic Details
Published in:Psychophysiology 2024-06, Vol.61 (6), p.e14533-n/a
Main Authors: Aschbacher, Kirstin, Mather, Mara, Lehrer, Paul, Gevirtz, Richard, Epel, Elissa, Peiper, Nicholas C.
Format: Article
Language:English
Subjects:
Age
Anxiety
Biofeedback
Body mass index
Demography
epidemiology
Feedback
Gender
Heart rate
Mental depression
Mental health
mental health services
psychophysiology
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Summary: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 
ISSN:0048-5772
1469-8986
1540-5958
DOI:10.1111/psyp.14533