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Background: The emergence of smartphones and wearable sensor technologies enables easy and unobtrusive monitoring of physiological and psychological data related to an individual’s resilience. Heart rate variability (HRV) is a promising biomarker for resilience based on between-subject population studies, but observational studies that apply a within-subject design and use wearable sensors in order to observe HRV in a naturalistic real-life context are needed. Objective: This study aims to explore whether resting HRV and total sleep time (TST) are indicative and predictive of the within-day accumulation of the negative consequences of stress and mental exhaustion. The tested hypotheses are that demands are positively associated with stress and resting HRV buffers against this association, stress is positively associated with mental exhaustion and resting HRV buffers against this association, stress negatively impacts subsequent-night TST, and previous-evening mental exhaustion negatively impacts resting HRV, while previous-night TST buffers against this association. Methods: In total, 26 interns used consumer-available wearables (Fitbit Charge 2 and Polar H7), a consumer-available smartphone app (Elite HRV), and an ecological momentary assessment smartphone app to collect resilience-related data on resting HRV, TST, and perceived demands, stress, and mental exhaustion on a daily basis for 15 weeks. Results: Multiple linear regression analysis of within-subject standardized data collected on 2379 unique person-days showed that having a high resting HRV buffered against the positive association between demands and stress (hypothesis 1) and between stress and mental exhaustion (hypothesis 2). Stress did not affect TST (hypothesis 3). Finally, mental exhaustion negatively predicted resting HRV in the subsequent morning but TST did not buffer against this (hypothesis 4). Conclusions: To our knowledge, this study provides first evidence that having a low within-subject resting HRV may be both indicative and predictive of the short-term accumulation of the negative effects of stress and mental exhaustion, potentially forming a negative feedback loop. If these findings can be replicated and expanded upon in future studies, they may contribute to the development of automated resilience interventions that monitor daily resting HRV and aim to provide users with an early warning signal when a negative feedback loop forms, to prevent the negative impact of stress on long-term health outcomes.
Originele taal-2 | English |
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Artikelnummer | e28731 |
Aantal pagina's | 15 |
Tijdschrift | JMIR Cardio |
Volume | 5 |
Nummer van het tijdschrift | 2 |
DOI's | |
Status | Published - 4 okt. 2021 |
Keywords
- veerkracht
- stress
- hartritmevariabiliteit
- wearables
- apps
- monitoring
- slaap
Vingerafdruk
Duik in de onderzoeksthema's van 'Moderation of the Stressor-Strain Process in Interns by Heart Rate Variability Measured With a Wearable and Smartphone App: within-Subject Design Using Continuous Monitoring'. Samen vormen ze een unieke vingerafdruk.Projecten
- 1 Afgelopen
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WearMe: Wearable and app-based resilience Modeling in employees
de Vries, H., Sanderman, R., van der Schans, C., Oldenhuis, H. & Kamphuis, W.
1/09/17 → 30/11/21
Project: Research
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Publication: buffering effect of HRV in the stressor-strain process
de Vries, H., 11 okt. 2021Onderzoeksoutput: Blogs and web publications › Other research output
Open Access -
Modelling employee resilience using wearables and apps: a conceptual framework and research design
de Vries, H., Kamphuis, W., Oldenhuis, H., van der Schans, C. & Sanderman, R., 30 dec. 2019, In: International Journal on Advances in Life Sciences. 11, 3-4, blz. 110-118Onderzoeksoutput: Article › Academic › peer review
Open AccessBestand
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Wearables and app-based resilience Modeling in employees (WearMe)
Herman de Vries (Speaker)
29 okt. 2020Activiteit: Invited talk
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Wearables and app-based resilience modeling in employees (WearMe)
Herman de Vries (Speaker)
18 nov. 2019Activiteit: Oral presentation
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Wearables and app-based resilience modeling in employees (WearMe)
Herman de Vries (Speaker) & Hilbrand Oldenhuis (Speaker)
26 nov. 2019Activiteit: Invited talk