Alignment Between Heart Rate Variability From Fitness Trackers and Perceived Stress: Perspectives From a Large-Scale In Situ Longitudinal Study of Information Workers
Creators: name: Martinez, Gonzalo
name: Grover, Ted
name: Mattingly, Stephen
name: Mark, Gloria
name: D'Mello, Sidney
name: Aledavood, Talayeh
name: Akbar, Fatema
name: Robles-Granda, Pablo
name: Striegel, Aaron
Publisher: name: American University of Bahrain
Year: 2024
Subjects: classificationCode: 46
subject: Information and computing sciences
classificationCode: 420308
subject: Health informatics and information systems
classificationCode: 401611
subject: Wearable materials
classificationCode: 400906
subject: Electronic sensors

description: <b>Background:</b>Stress can have adverse effects on health and well-being. Informed by laboratory findings that heart rate variability (HRV) decreases in response to an induced stress response, recent efforts to monitor perceived stress in the wild have focused on HRV measured using wearable devices. However, it is not clear that the well-established association between perceived stress and HRV replicates in naturalistic settings without explicit stress inductions and research-grade sensors.<br><b>Objective:</b>This study aims to quantify the strength of the associations between HRV and perceived daily stress using wearable devices in real-world settings.<br><b>Methods:</b>In the main study, 657 participants wore a fitness tracker and completed 14,695 ecological momentary assessments (EMAs) assessing perceived stress, anxiety, positive affect, and negative affect across 8 weeks. In the follow-up study, approximately a year later, 49.8% (327/657) of the same participants wore the same fitness tracker and completed 1373 EMAs assessing perceived stress at the most stressful time of the day over a 1-week period. We used mixed-effects generalized linear models to predict EMA responses from HRV features calculated over varying time windows from 5 minutes to 24 hours.<br><b>Results:</b>Across all time windows, the models explained an average of 1% (SD 0.5%; marginal <i>R</i><sup>2</sup>) of the variance. Models using HRV features computed from an 8 AM to 6 PM time window (namely work hours) outperformed other time windows using HRV features calculated closer to the survey response time but still explained a small amount (2.2%) of the variance. HRV features that were associated with perceived stress were the low frequency to high frequency ratio, very low frequency power, triangular index, and SD of the averages of normal-to-normal intervals. In addition, we found that although HRV was also predictive of other related measures, namely, anxiety, negative affect, and positive affect, it was a significant predictor of stress after controlling for these other constructs. In the follow-up study, calculating HRV when participants reported their most stressful time of the day was less predictive and provided a worse fit (<i>R</i><sup>2</sup>=0.022) than the work hours time window (<i>R</i><sup>2</sup>=0.032).<br><b>Conclusions:</b>A significant but small relationship between perceived stress and HRV was found. Thus, although HRV is associated with perceived stress in laboratory settings, the strength of that association diminishes in real-life settings. HRV might be more reflective of perceived stress in the presence of specific and isolated stressors and research-grade sensing. Relying on wearable-derived HRV alone might not be sufficient to detect stress in naturalistic settings and should not be considered a proxy for perceived stress but rather a component of a complex phenomenon.