Associations Between Physiological Signals Captured Using Wearable Sensors and Self-reported Outcomes Among Adults in Alcohol Use Disorder Recovery: Development and Usability Study

Abstract

Background Previous research has highlighted the role of stress in substance misuse and addiction, particularly for relapse risk. Mobile health interventions that incorporate real-time monitoring of physiological markers of stress offer promise for delivering tailored interventions to individuals during high-risk states of heightened stress to prevent alcohol relapse. Before such interventions can be developed, measurements of these processes in ambulatory, real-world settings are needed. Objective This research is a proof-of-concept study to establish the feasibility of using a wearable sensor device to continuously monitor stress in an ambulatory setting. Toward that end, we first aimed to examine the quality of 2 continuously monitored physiological signals—electrodermal activity (EDA) and heart rate variability (HRV)—and show that the data follow standard quality measures according to the literature. Next, we examined the associations between the statistical features extracted from the EDA and HRV signals and self-reported outcomes. Methods Participants (N=11; female: n=10) were asked to wear an Empatica E4 wearable sensor for continuous unobtrusive physiological signal collection for up to 14 days. During the same time frame, participants responded to a daily diary study using ecological momentary assessment of self-reported stress, emotions, alcohol-related cravings, pain, and discomfort via a web-based survey, which was conducted 4 times daily. Participants also participated in structured interviews throughout the study to assess daily alcohol use and to validate self-reported and physiological stress markers. In the analysis, we first used existing artifact detection methods and physiological signal processing approaches to assess the quality of the physiological data. Next, we examined the descriptive statistics for self-reported outcomes. Finally, we investigated the associations between the features of physiological signals and self-reported outcomes. Results We determined that 87.86% (1,032,265/1,174,898) of the EDA signals were clean. A comparison of the frequency of skin conductance responses per minute with previous research confirmed that the physiological signals collected in the ambulatory setting were successful. The results also indicated that the statistical features of the EDA and HRV measures were significantly correlated with the self-reported outcomes, including the number of stressful events marked on the sensor device, positive and negative emotions, and experienced pain and discomfort. Conclusions The results demonstrated that the physiological data collected via an Empatica E4 wearable sensor device were consistent with previous literature in terms of the quality of the data and that features of these physiological signals were significantly associated with several self-reported outcomes among a sample of adults diagnosed with alcohol use disorder. These results suggest that ambulatory assessment of stress is feasible and can be used to develop tailored mobile health interventions to enhance sustained recovery from alcohol use disorder.

Substance Misuse Decreases Heart Rate Variability

“…On the average, a person has a lower HRV as they grow older; therefore, HRV is an effective indicator for observing the aging of the human body. Because the inspection of HRV involves noninvasive methods, those with substance use disorders could conduct self-assessments in their home environment [22]. HRV has been used as a biomarker for severe substance use disorder [18] and also as a useful biomarker for other addictions, such as video game addiction [23] and alcohol addiction.…”

The relational change mechanisms of child‐centered play therapy with children exposed to adverse childhood experiences

“…The therapeutic relationship is a common factor (mechanism of change) across therapeutic approaches (Wampold, 2015); therefore, counseling researchers may further examine how this common factor operates among counselors utilizing other humanistic approaches, such as Adlerian Play Therapy. To examine autonomic nervous system reactivity during counseling sessions, researchers may examine child‐counselor electrodermal activity (EDA; skin conductance response [SCR]) synchrony, which is an efficient measure of sympathetic nervous system activation (Alinia et al., 2021). Through examining changes in children's autonomic nervous system regulatory capacities (via SCRs or HRV indices during sessions), researchers can determine mechanisms of play therapy that address the neurobiological consequences of trauma.…”

Exploring Digital Biomarkers of Illness Activity in Mood Episodes: Hypotheses Generating and Model Development Study

“…As previously mentioned, these physiological parameters have been shown to be altered in mood disorders and mood episodes [19][20][21][22][23][25][26][27][28]. Second, the E4 has been validated in scientific research for detecting emotional arousal, stress [43,44], and mental effort [45] using the aforementioned physiological signals. Furthermore, the E4 has proven to be useful in predicting depressive symptoms in MDD with low relative errors [46,47], predicting self-reported depressive states [48], and identifying and quantifying the severity of anxiety states [49].…”