Russell Michael A, Richards Veronica L, Turrisi Robert J, Exten Cara L, Pesigan Ivan Jacob Agaloos, Rodríguez Gabriel C
Department of Biobehavioral Health, Pennsylvania State University.
Edna Bennett Pierce Prevention Research Center, Pennsylvania State University.
Psychol Addict Behav. 2025 Mar;39(2):173-185. doi: 10.1037/adb0001022. Epub 2024 Aug 1.
Transdermal alcohol concentration (TAC) sensors capture aspects of drinking events that self-reports cannot. The multidimensional nature of TAC data allows novel classification of drinking days and identification of associated behavioral and contextual risks. We used multilevel latent profile analysis (MLPA) to create day-level profiles of TAC features and test their associations with (a) daily behaviors and contexts and (b) risk for alcohol use disorders at baseline.
Two hundred twenty-two regularly heavy-drinking young adults ( = 22.3) completed the Alcohol Use Disorders Identification Test (AUDIT) at baseline and then responded to mobile phone surveys and wore TAC sensors for six consecutive days. MLPA identified day-level profiles using four TAC features (peak, rise rate, fall rate, and duration). TAC profiles were tested as correlates of daily drinking behaviors, contexts, and baseline AUDIT.
Four profiles emerged: (a) high-fast (8.5% of days), (b) moderate-fast (12.8%), (c) low-slow (20.4%), and (d) little-to-no drinking days (58.2%). Profiles differed in the odds of risky drinking behaviors and contexts. The highest risk occurred on high-fast days, followed by moderate-fast, low-slow, and little-to-no drinking days. Higher baseline AUDIT predicted higher odds of high-fast and moderate-fast days.
Days with high and fast intoxication are reflective of high-risk drinking behaviors and were most frequent among those at risk for alcohol use disorders. TAC research using MLPA may offer novel and important insights to intervention efforts. (PsycInfo Database Record (c) 2025 APA, all rights reserved).
经皮酒精浓度(TAC)传感器能够捕捉自我报告所无法涵盖的饮酒事件的各个方面。TAC数据的多维度性质使得对饮酒日进行新颖的分类以及识别相关的行为和情境风险成为可能。我们使用多水平潜在类别分析(MLPA)来创建TAC特征的日水平类别,并测试它们与(a)日常行为和情境以及(b)基线时酒精使用障碍风险之间的关联。
222名经常大量饮酒的年轻成年人(平均年龄 = 22.3岁)在基线时完成了酒精使用障碍识别测试(AUDIT),然后连续六天回复手机调查并佩戴TAC传感器。MLPA使用四个TAC特征(峰值、上升速率、下降速率和持续时间)来识别日水平类别。将TAC类别作为日常饮酒行为、情境和基线AUDIT的相关因素进行测试。
出现了四类情况:(a)高且快(占天数的8.5%),(b)中且快(12.8%),(c)低且慢(20.4%),以及(d)几乎无饮酒日(58.2%)。不同类别在危险饮酒行为和情境的几率上存在差异。风险最高的是高且快的日子,其次是中且快、低且慢以及几乎无饮酒日。基线AUDIT得分越高,出现高且快和中且快日子的几率就越高。
高且快速醉酒的日子反映了高风险饮酒行为,并且在有酒精使用障碍风险的人群中最为常见。使用MLPA的TAC研究可能为干预措施提供新颖且重要的见解。(PsycInfo数据库记录(c)2025美国心理学会,保留所有权利)