Department of Psychological Sciences, University of Liverpool, Liverpool, L69 7ZA, UK.
UK Centre for Tobacco and Alcohol Studies, Liverpool, UK.
Psychopharmacology (Berl). 2018 May;235(5):1487-1496. doi: 10.1007/s00213-018-4860-5. Epub 2018 Mar 1.
Deficient inhibitory control is predictive of increased alcohol consumption in the laboratory; however, little is known about this relationship in naturalistic, real-world settings.
In the present study, we implemented ecological momentary assessment methods to investigate the relationship between inhibitory control and alcohol consumption in the real world.
Heavy drinkers who were motivated to reduce their alcohol consumption (N = 100) were loaned a smartphone which administered a stop signal task twice per day at random intervals between 10 a.m. and 6 p.m. for 2 weeks. Each day, participants also recorded their planned and actual alcohol consumption and their subjective craving and mood. We hypothesised that day-to-day fluctuations in inhibitory control (stop signal reaction time) would predict alcohol consumption, over and above planned consumption and craving.
Multilevel modelling demonstrated that daily alcohol consumption was predicted by planned consumption (β = .816; 95% CI .762-.870) and craving (β = .022; 95% CI .013-.031), but inhibitory control did not predict any additional variance in alcohol consumption. However, secondary analyses demonstrated that the magnitude of deterioration in inhibitory control across the day was a significant predictor of increased alcohol consumption on that day (β = .007; 95% CI .004-.011), after controlling for planned consumption and craving.
These findings demonstrate that short-term fluctuations in inhibitory control predict alcohol consumption, which suggests that transient fluctuations in inhibition may be a risk factor for heavy drinking episodes.
抑制控制不足可预测实验室中饮酒量增加；然而，在自然的、真实世界的环境中，人们对此类关系知之甚少。
本研究采用生态瞬时评估方法，在真实世界中研究抑制控制与饮酒之间的关系。
为了减少饮酒量，参与者（n=100）被借了一部智能手机，该手机在上午 10 点至下午 6 点之间的随机时间间隔内每天两次随机向参与者发送停止信号任务。每天，参与者还记录了他们计划的和实际的饮酒量以及他们的主观渴望和情绪。我们假设，抑制控制（停止信号反应时间）的日常波动会预测饮酒量，超过计划饮酒量和渴望。
多层次模型表明，每日饮酒量由计划饮酒量（β=0.816；95%置信区间：0.762-0.870）和渴望（β=0.022；95%置信区间：0.013-0.031）预测，但抑制控制并不能预测饮酒量的任何额外变化。然而，二次分析表明，一天中抑制控制的恶化程度是当天饮酒量增加的一个重要预测因素（β=0.007；95%置信区间：0.004-0.011），控制了计划饮酒量和渴望。
这些发现表明，抑制控制的短期波动可预测饮酒量，这表明抑制的短暂波动可能是重度饮酒发作的一个风险因素。
