Commentary on Östh <i>et al</i>.: Sensor‐based approaches to inform alcohol interventions – beyond BAC

Sensor-based technologies offer a transformative approach to enhance alcohol interventions by providing continuous, objective data beyond self-report. These tools can predict drinking onset, assess impairment in real time and track post-drinking effects. By integrating physiological, behavioral and contextual data, interventions can shift from reactive to proactive, tailoring harm reduction strategies to individual needs. Digital health is transforming alcohol intervention, with sensor-based technologies providing continuous, objective insights beyond self-reports and clinical check-ins. The study by Östh et al. highlights how breathalyzers can be incorporated into behavioral interventions to help alcohol-dependent adults curb heavy drinking. However, the potential for sensors extends far beyond measuring alcohol levels – they can anticipate drinking triggers, assess real-time impairment and track post-drinking recovery. Integrating sensors across all drinking phases enables a proactive, personalized harm reduction model. Predicting drinking onset: Subtle physiological and behavioral shifts – rising stress levels [1], mounting alcohol cravings [2] or changes in daily routines – often signal the lead-up to a drinking event. Wearable sensors tracking heart rate variability [3] and skin conductance [4] can detect these internal cues, whereas external patterns, such as increased phone activity [5] or movement toward alcohol-related locations [6], may further indicate imminent drinking. Real-time nudges – like mindfulness exercises [7] or cognitive reappraisal strategies [8] – can be deployed at key moments, helping individuals disrupt habitual drinking patterns before they begin. Measuring alcohol and effects: Despite the modest effects reported by Östh et al. [9] for individuals tracking their alcohol intake using commercial breathalyzers, these devices remain imprecise in estimating blood alcohol concentration (BAC) [10]. Similarly, transdermal alcohol monitors, despite significant National Institutes of Health (NIH) investment, have yet to achieve the precision needed for reliable use [11]. Given these limitations, measuring the effects of alcohol on the body – rather than just its presence – offers a promising alternative or complement. Recent research has shown that remote assessments of impairment, such as changes in gait [12], speech [13] and fine motor function (e.g. typing speed and accuracy) [14], can serve as sensitive markers for the impact of alcohol. Moreover, BAC and impairment do not exist in a vacuum – context matters. The same alcohol exposure may pose little risk in some situations but be dangerous in others. Advanced applications could incorporate geolocation and situational awareness – intensifying warnings if an individual is near their vehicle or engaged in a safety-sensitive task or de-escalating alerts when impairment is less immediately consequential. Drawing attention to the aftermath: The effects of alcohol extend beyond intoxication, often disrupting sleep, hydration and cardiovascular function. Wearable sensors tracking sleep patterns, heart rhythm (e.g. atrial fibrillation) and blood pressure provide critical insights into the ‘silent’ physiological consequences of drinking alcohol. As individuals tend to underestimate the negative consequences of drinking [15], digital platforms could help to raise awareness of post-drinking effects, such as poor sleep quality [16], arrhythmia events [17] or episodes of orthostatic hypotension [18]. These systems could also deliver hydration reminders, rest recommendations or even automated scheduling of lower risk drinking days as part of a long-term behavior change strategy. By linking acute physiological responses to alcohol use, individuals receive personalized feedback that may encourage more mindful consumption patterns over time. In conclusion, sensor-based technology has the potential to transform alcohol harm reduction, but its success hinges on thoughtful implementation. By integrating predictive monitoring of drinking triggers, real-time tracking of impairment and post-drinking recovery analysis, we can move beyond traditional approaches to a more dynamic and personalized system. Brian Suffoletto is the sole author. B.S. has no conflicts of interest to declare. None. NA