JMIR Publications

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. Risk factors for AIBs include dynamics of alcohol use (quantity, speed, duration), alcohol-related behaviors (e.g., playing drinking games, not using protective behavioral strategies), and factors related to the subjective experience of alcohol intoxication (e.g., expectancies, motivations).

Objective:

The current study seeks to examine two modifiable behaviors that have 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/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/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. 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 begin in Fall 2025.

Conclusions:

This study seeks to understand two key modifiable behaviors that may be associated with increased AIB risk by leveraging multiple forms of innovative measurement. The integration of EMA with two sensors to capture alcohol use and sleep also supports potential applications in future digital interventions. The current proposal will further enhance our preliminary data on the feasibility and acceptability of these methods, providing opportunities for conducting future research on a larger scale.