ArticleJMIR research protocols2026
Using Alcohol and Sleep Sensors to Understand Blackout Risk in Young Adults' Natural Settings (The Lights Out Study): Protocol for an Intensive Longitudinal Pilot Study.
Article in JMIR research protocols, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Authors and funding
7 authors.
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Abstract
Background: Alcohol-induced blackouts (AIBs) are a serious consequence of alcohol use that are strongly associated with experiencing excess alcohol-related harms. AIBs are common and recurrent among young adults who drink. The risk factors for AIBs include dynamics of alcohol use (quantity, speed, duration), alcohol-related behaviors (eg, playing drinking games, not using protective behavioral strategies), and factors related to the subjective experience of alcohol intoxication (eg, expectancies, motivations). Objective: This study seeks to examine 2 modifiable behaviors that have been shown to impact both alcohol consumption and subjective experiences of intoxication and may therefore be associated with AIB risk: (1) other substance use and (2) sleep. Methods: Approximately 50 participants will be recruited to participate in this study. Interested individuals will complete an online screening assessment, and those who are eligible (young adults who report recent heavy episodic drinking and AIBs) will be invited to an in-person baseline visit. At the baseline visit, participants will complete a baseline assessment, be fitted with a wrist-worn alcohol sensor (BACtrack Skyn) and a sleep or activity ring sensor (Oura ring), and receive training on the study protocol. Participants will complete a 14-day intensive data collection period consisting of twice daily scheduled mobile surveys and participant-initiated drinking surveys with hourly follow-ups. Participants will also wear the alcohol and sleep or activity sensors continuously during this 14-day period. After the intensive data collection period ends, participants will complete an in-person return visit to return their sensors, complete a follow-up survey, and receive compensation. The data will be processed and cleaned, and analyses will include multi-level structural equation models. Results: This study was funded in July 2025. Data collection is projected to span January 2026 through June 2026. Conclusions: This study seeks to understand 2 key modifiable behaviors that may be associated with increased AIB risk by leveraging multiple forms of innovative measurement. The integration of ecological momentary assessments with 2 sensors to capture alcohol use and sleep also supports potential applications in future digital interventions. This study will further enhance our preliminary data on the feasibility and acceptability of these methods, providing opportunities for conducting future research on a larger scale.
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