Randomized trial captures drinking behavior in individuals with alcohol use disorder, indicating seasonal effects and intervention timing opportunities.
Alcohol consumption (AC) is a major contributor to preventable morbidity and mortality. Fine-grained, near real-time data may capture short-term fluctuations in alcohol use, yet evidence on long-term temporal drinking patterns remains limited. Using smartphone-based ecological momentary assessment (EMA) over 12 months, we quantified weekly, seasonal, and pandemic-related drinking patterns in individuals aged 16-66 with alcohol use disorder (AUD) recruited February 2020-September 2024. Outcomes were modelled as drinking frequency (any vs. none per day) and drinking-day amount (g/day on drinking days). Mixed-effects models tested weekends, holiday-related days, annual seasonality, lockdown periods, and time since study entry. Among 670 participants, drinking frequency and drinking-day amount increased on weekends (frequency: β = 0.354; amount: β = 0.078; both p < .001) and holiday-related days (frequency: β = 0.319; amount: β = 0.056; both p < .001). During lockdowns, drinking frequency was higher (β = 0.074; p = .007), whereas drinking-day amount did not change. Seasonal variation was observed (frequency: β = 0.252; amount: β = 0.035; both p < .001), with December peaks and January declines. Drinking frequency declined early after study entry (β = -0.0005; p = .002) and then remained stable at a lower level than at study entry, with no time trend in drinking-day amount. Long-term EMA captured drinking patterns and suggested possible assessment-related changes early after study entry. Higher-consumption windows (weekends, holiday-related days, December) may help inform the timing of prevention and intervention strategies; causal effects of repeated EMA (i.e., assessment reactivity) should be tested in randomized controlled trials.
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Bahr et al. (2026) studied this question.
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