Exploration of wearable sensor measures associated with panic attacks differs across mental health conditions

Panic attacks (PAs) are acute anxiety episodes that are pervasive, with one in 10 individuals having experienced a PA in the past year. PAs impair daily functioning and are associated with an increase in emergency room visits and suicide attempts. Despite their impact, the unpredictable nature of PAs makes them challenging to manage. PAs are transdiagnostic, occurring in individuals across and without a mental health diagnosis. However, prior work has largely focused on PA indications within individuals with panic disorder. This study identifies PA risk factors from over 6 months of passive sensing data recorded by Oura Rings in 182 young adults with and without adverse childhood experiences and psychiatric diagnoses, beyond just panic disorder. Our findings reveal that changes in Oura Ring-derived measures are associated with next-day PAs, with distinct associations observed across different mental health diagnoses. For individuals with panic disorder, the likelihood of PA increases with time spent inactive. For those with depression, the likelihood of PA increases with decreased variation in nightly respiratory rate, decreased rapid eye movement sleep, and increased time spent in high-intensity activity. For those without a mental health diagnosis, the likelihood of PA increases with decreased heart rate variability. Data aggregation window sizes that capture the associations with PA risk vary by diagnosis and the type of feature, suggesting that cumulative physiological patterns from windows up to 7 days before a PA contribute to onset. These findings point to the possibility that continuous monitoring of panic attack risk could one day support preventive mental health intervention.

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Publication Details

Journal
Frontiers in Digital Health
Published
2026-04-20
DOI
https://doi.org/10.3389/fdgth.2026.1764371
Primary Topic
Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes
Type
article
Field-Weighted Citation Impact
0.00
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article

Exploration of wearable sensor measures associated with panic attacks differs across mental health conditions

Johanna E. Hidalgo, Christopher M. Danforth, Josh Cherian, Ryan S. McGinnis et al.
Frontiers in Digital Health
Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes
article

Exploration of wearable sensor measures associated with panic attacks differs across mental health conditions

Johanna E. Hidalgo, Christopher M. Danforth, Josh Cherian, Ryan S. McGinnis, Natalie Noble, Nathaniel S. O’Connell, Kathryn Stanton, Peter Sheridan Dodds, Laura S. P. Bloomfield, Jordan Llorin, Julia Kim, Dheeraj D Kairamkonda, Jason Fanning, Matthew Price, Jennifer Ha, Mikaela Fudolig, Ellen W. McGinnis, Guido Mascia
article en

Abstract

Panic attacks (PAs) are acute anxiety episodes that are pervasive, with one in 10 individuals having experienced a PA in the past year. PAs impair daily functioning and are associated with an increase in emergency room visits and suicide attempts. Despite their impact, the unpredictable nature of PAs makes them challenging to manage. PAs are transdiagnostic, occurring in individuals across and without a mental health diagnosis. However, prior work has largely focused on PA indications within individuals with panic disorder. This study identifies PA risk factors from over 6 months of passive sensing data recorded by Oura Rings in 182 young adults with and without adverse childhood experiences and psychiatric diagnoses, beyond just panic disorder. Our findings reveal that changes in Oura Ring-derived measures are associated with next-day PAs, with distinct associations observed across different mental health diagnoses. For individuals with panic disorder, the likelihood of PA increases with time spent inactive. For those with depression, the likelihood of PA increases with decreased variation in nightly respiratory rate, decreased rapid eye movement sleep, and increased time spent in high-intensity activity. For those without a mental health diagnosis, the likelihood of PA increases with decreased heart rate variability. Data aggregation window sizes that capture the associations with PA risk vary by diagnosis and the type of feature, suggesting that cumulative physiological patterns from windows up to 7 days before a PA contribute to onset. These findings point to the possibility that continuous monitoring of panic attack risk could one day support preventive mental health intervention.

Frontiers in Digital HealthVol. 8
University of Vermont (US), Santa Fe Institute (US), Center For Remote Sensing (United States) (US), Institute for Complex Systems (IT), Wake Forest University (US), University of West Alabama (US)
Good health and well-being
Openalex Percentile: Top 18%
Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes
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