JMIR Publications

ABSTRACT

Background:

Past research has highlighted the important role of stress in substance misuse and addiction, particularly for relapse risk. Mobile health (mHealth) interventions that incorporate real-time monitoring of physiological markers of stress offer particular promise for delivering tailored interventions to individuals during high-risk states of heightened stress to prevent relapse to alcohol. Before such interventions can be developed, measurement of these processes in ambulatory, real-world settings is needed.

Objective:

The current research is designed as a proof-of-concept study to establish the feasibility of using a wearable sensor device to provide continuous monitoring of stress in an ambulatory setting. Toward that end, we first established the validity of two continuously-monitored physiological signals, electrodermal activity (EDA) and heart rate variability (HRV), collected from a wearable sensor device. Next, we examined associations between the statistical features extracted from the EDA and HRV signals and patient-reported outcomes.

Methods:

Participants (N = 11, 10 female) were asked to wear an Empatica E4 wearable sensor for continuous unobtrusive physiological signal collection for up to 14 days. During the same timeframe, participants responded to a daily diary study using ecological momentary assessment (EMA) of self-reported stress, emotions, alcohol-related cravings, pain, and discomfort via an online survey, prompted four times daily. Participants also participated in structured, qualitative interviews throughout the study to assess daily alcohol use and to validate self-reported and physiological markers of stress. In the analysis, we first utilized existing artifact detection methods and physiological signal processing approaches to validate the physiological data. Next, we examined descriptive statistics for the self-reported outcomes. Lastly, we investigated associations among the features of physiological signals and the self-reported outcomes.

Results:

We determined that that 87.86% of the EDA signals were clean (i.e., valid data). Comparison of the frequency of skin conductance responses (SCRs) per minute to previous research also confirmed that the physiological signals collected in the ambulatory setting was successful. The results also indicated that statistical features of both the EDA and HRV measures were significantly correlated with a number of the self-reported outcomes. Several EDA features were moderately associated with the number of stressful events marked on the sensor device as well as self-reported positive and negative emotions, experienced pain, and experienced discomfort. Features of HRV were also significantly associated with participants’ reports of stressful events, positive and negative emotions, and experiences of pain and discomfort

Conclusions:

The results demonstrated that the physiological data collected via an Empatica E4 wearable sensor device were valid and that features of these physiological signals were significantly associated with several self-reported outcomes among a sample of patients diagnosed with Alcohol Use Disorder (AUD). These results suggest that ambulatory assessment of stress is feasible and can be used to develop tailored mHealth interventions to enhance sustained recovery from AUD.