Integrating Alcohol Biosensors With Ecological Momentary Intervention (EMI) for Alcohol Use: a Synthesis of the Latest Literature and Directions for Future Research.

Abstract

Excessive alcohol use is a major public health concern. With increasing access to mobile technology, novel mHealth approaches for alcohol misuse, such as ecological momentary intervention (EMI), can be implemented widely to deliver treatment content in real time to diverse populations. This review summarizes the state of research in this area with an emphasis on the potential role of wearable alcohol biosensors in future EMI/just-in-time adaptive interventions (JITAI) for alcohol use. JITAI emerged as an intervention design to optimize the delivery of EMI for various health behaviors including substance use. Alcohol biosensors present an opportunity to augment JITAI/EMI for alcohol use with objective information on drinking behavior captured passively and continuously in participants' daily lives, but no prior published studies have incorporated wearable alcohol biosensors into JITAI for alcohol-related problems. Several methodological advances are needed to accomplish this goal and advance the field. Future research should focus on developing standardized data processing, analysis, and interpretation methods for wrist-worn biosensor data. Machine learning algorithms could be used to identify risk factors (e.g., stress, craving, physical locations) for high-risk drinking and develop decision rules for interpreting biosensor-derived transdermal alcohol concentration (TAC) data. Finally, advanced trial design such as micro-randomized trials (MRT) could facilitate the development of biosensor-augmented JITAI. Wrist-worn alcohol biosensors are a promising potential addition to improve mHealth and JITAI for alcohol use. Additional research is needed to improve biosensor data analysis and interpretation, build new machine learning models to facilitate integration of alcohol biosensors into novel intervention strategies, and test and refine biosensor-augmented JITAI using advanced trial design.