Abstract
BackgroundThe 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.ObjectiveThis 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.MethodsIn 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.ResultsMultiple 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).ConclusionsTo 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.
Highlights
BackgroundPsychological stress is associated with increased risk of several forms of cancer [1], musculoskeletal diseases [2], periodontal diseases [3], type 2 diabetes mellitus [4], stroke [5], cardiovascular disease [6], and recurrent cardiovascular disease [7]
Multiple linear regression analysis of within-subject standardized data collected on 2379 unique person-days showed that having a high resting Heart rate variability (HRV) buffered against the positive association between demands and stress and between stress and mental exhaustion
Mental exhaustion negatively predicted resting HRV in the subsequent morning but total sleep time (TST) did not buffer against this
Summary
BackgroundPsychological stress is associated with increased risk of several forms of cancer [1], musculoskeletal diseases [2], periodontal diseases [3], type 2 diabetes mellitus [4], stroke [5], cardiovascular disease [6], and recurrent cardiovascular disease [7]. Psychosocial risk factors such as high job demands are estimated to increase the risk of stress-related diseases (eg, burnout) by 60%-90% [8]. Stress occurs when the brain subconsciously appraises a demand as threatening because of a lack of resources to cope with it [10]. Acute stress can have negative effects, it is the cumulative wear and tear on bodily systems (allostatic load) caused by excessive stress or inefficient management of the systems that promote adaptation that is detrimental to long-term health and well-being [13]. Allostatic load is considered a measure of the cumulative biological burden on health [15]. 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
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