Using passive sensing to isolate a biosignature for craving among individuals in early alcohol use disorder recovery

Abstract

Craving is one of the most robust proximal predictors of both treatment dropout and relapse during early recovery for alcohol use disorder (Andersson et al., 2019; Gossop et al., 2002; Tiffany, 2010). Unsurprisingly, craving management is a central feature of most current AUD treatment models (Hendershot et al., 2011). However, craving can onset rapidly (Epstein et al., 2009) and the ability to accurately predict or modulate cravings varies significantly within- and between-person (Ellis et al., 2022; Joos et al., 2013; Kruschwitz et al., 2019; Preston et al., 2018). These factors make implementation of change strategies in the moment challenging, but creating a measurement and detection of craving through passive biosensor monitoring could offer a crucial opportunity for empirically supported just-in-time interventions. Heart rate variability has been associated with craving and changes in affect (Carter & Tiffany, 2002; Wascher, 2021). This study aims to characterize craving as a biosignature via heart rate variability to best capture the momentary nature of craving and individual differences by pairing wearable technologies with EMA among those in early recovery (N = 40, observations = 400). Multilevel regression analyses will be conducted to estimate correlations of craving and heart rate variability. Results from this line of research hold clinical implications for relapse prevention by laying the groundwork for the efficacy of isolating a biosignature for craving, which may inform just-in-time interventions by providing real-time information for recovery goals and enabling personalized interventions during critical recovery moments.