Concurrent and Prospective Associations Between Fitbit Derived RDoC Arousal and Regulation Constructs and Adolescent Internalizing Symptoms

Abstract

Background: Adolescence is characterized by alterations in biobehavioral functioning, during which individuals are at heightened risk for first onset of psychopathology, particularly internalizing disorders (e.g., depression and anxiety). Recently, researchers have proposed the use of mobile Health (mHealth) technologies to passively index biobehavioral functioning in everyday life yet, there is a dearth of research examining how wearable metrics, which map onto NIMH Research Domain Criteria (RDoC) of Arousal and Regulation, are associated with concurrent and prospective changes in mental health.Methods: We preregistered secondary data analyses using the Adolescent Brain Cognitive Development (ABCD) Study dataset to determine whether wearable indices of resting heart rate (HR), step count, and sleep duration as well as variability in these measures were cross-sectionally associated with internalizing symptomatology in 5,686 adolescents. All models were also run controlling for age, sex, body mass index, socioeconomic status, and race. We also performed prospective analyses on a subset of this sample across 25 months that had Fitbit data available at Baseline and Follow Up (n = 143). Results: Cross-sectional analyses revealed that higher resting HR, lower step count and step count variability, and greater variability in sleep duration were associated with greater internalizing symptoms. Cross-lagged panel model analysis revealed that there were no prospective associations between wearable variables, but greater internalizing symptoms predicted lower step count 25 months later.Conclusions: Findings indicate that wearable indices concurrently, but not prospectively, associate with internalizing symptoms during early adolescence. Future research should capitalize on the temporal resolution provided by wearable devices to determine the intensive longitudinal relations between biobehavioral risk factors and acute changes in mental health.

Smartphone Photoplethysmography Covaries with Stress and Anxiety During a Digital Acute Social Stressor Preprint

“…Overall, the results partly support our hypotheses, such that higher smartphone PPG indices of heart rate were significantly associated with higher concurrent self-reported stress and anxiety. This finding falls in line with past literature indicating that heart rate serves as a transdiagnostic marker for mental health (Latvala et al, 2016;Low et al, 2009;Nelson et al, 2022;Nelson, Sheeber, et al, 2020). However, the effect size of the association between concurrent heart rate and stress and anxiety was not larger than the effect size of overall anxiety symptoms, but it did have a larger effect size than stable depressive symptoms.…”

“…While recent research has identified that wearable derived heart rate is reasonably accurate, especially when pooled over longer time scales (Bent et al, 2020;Bent & Dunn, 2021;Nelson, Low, et al, 2020;Nelson & Allen, 2019), and has significant associations with mental health outcomes (Nelson et al, 2022), ownership of this new technology is unevenly distributed across important demographics, including race, ethnicity, socioeconomic, education, and age (Pew, 2020). Therefore, there is a need to democratize mobile PPG research to those without wearable devices.…”

Move more, move better: A narrative review of wearable technologies and their application to precision health.

“…The use of wearables in psychological research has also been completed in children and adolescents. For example, in a recent nationally representative sample using the Adolescent Brain Cognitive Development study dataset of over 5,000 adolescents wearing Fitbit devices, Nelson et al (2021) found that lower step count and step count variability was cross-sectionally associated with higher levels of internalizing symptoms, while higher internalizing symptoms were related to decreased step count over 25 months. In clinical samples, accelerometer-determined step count in participants at high risk for cardiovascular disease found that those with mild and moderate to severe depressive symptoms walked less than their nondepressed peers (Ludwig et al, 2018).…”

“…(Bernard et al, 2016;Dunton et al, 2014;Master et al, 2019) How does daily movement impact symptomatology in clinical samples? (Ludwig et al, 2018;Nelson et al, 2021;Wiebe et al, 2016) Intervention research Does monitoring movement with a device support behavior change? (Gal et al, 2018) Do smartphone applications that provide rewards for physical activity motivate behavior change?…”