Abstract

Background: To identify critical periods for just-in-time adaptive interventions (JITAIs), we measured time-varying correlates of drinking (e.g. stress, mood) daily to predict near-term alcohol use. Methods: Emerging adults (aged 17–24; n = 51) who reported past-month alcohol use used SARA, an app use designed to assess substance use, for 30 days. Participants completed daily process measures of stress, mood, hopefulness, free time, fun, and loneliness. Candidate variables for prediction of next-day drinking included a contextual factor (day of the week), between-person factors (age, sex), and within-person factors (daily process measure responses) as well as daily process measure noncompletion. We compared two approaches to predict next-day use. From the daily process measure responses, Approach 1 used the current day’s survey responses; whereas, Approach 2 used the deviation of daily responses from the participant’s average response in prior days. Backward model selection identified candidate variables to include in the logistic model. Each model’s discriminatory power was determined using the area under the curve (AUC). Toward identifying critical periods for interventions, decision rules for when next day alcohol use was likely are reported for the better performing approach. Results: Approach 1 included day of the week, hopefulness, stress, and participant sex (AUC = 0.76). Approach 2 included day of the week, and deviation in hopefulness rating (AUC = 0.71). Decisional cutpoints are provided for the better performing model. Conclusions: Approach 1 provided better prediction than Approach 2. Decisional tools for identification of near-term alcohol use in emerging adults open the door for JITAIs to reduce drinking and prevent consequences of use.

Abbreviations

JITAI: Just-in-time adaptive intervention; ROC: receiver operating characteristic; AUC: area under the curve; MRT: micro-randomized trial

中文翻译：

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采取及时的适应性干预措施来减少新兴成人饮酒：测试确定何时干预的方法

 抽象的

背景：为了确定及时适应性干预（JITAI）的关键时期，我们每天测量饮酒的时变相关性（例如压力、情绪），以预测近期饮酒情况。方法：报告过去一个月饮酒情况的新兴成年人（17-24 岁； n = 51）使用 SARA（一款旨在评估物质使用情况的应用程序）30 天。参与者完成了压力、情绪、希望、空闲时间、乐趣和孤独的日常过程测量。预测第二天饮酒的候选变量包括情境因素（一周中的某一天）、人际因素（年龄、性别）和人内因素（每日过程测量反应）以及每日过程测量未完成。我们比较了两种预测第二天使用情况的方法。从日常过程测量响应中，方法 1 使用当天的调查响应；而方法 2 使用每日响应与参与者前几天平均响应的偏差。向后模型选择确定了要包含在逻辑模型中的候选变量。每个模型的辨别力是使用曲线下面积 (AUC) 确定的。为了确定干预的关键时期，报告了第二天何时可能饮酒的决策规则，以获得更好的效果。结果：方法 1 包括星期几、希望、压力和参与者性别（AUC = 0.76）。方法 2 包括一周中的某一天和希望评级的偏差 (AUC = 0.71)。提供决策切点以获得更好的模型性能。结论：方法 1 比方法 2 提供了更好的预测。 用于识别新生成年人近期饮酒情况的决策工具为 JITAI 减少饮酒和预防饮酒后果打开了大门。

 缩写

JITAI：及时适应性干预； ROC：接收器工作特性； AUC：曲线下面积； MRT：微观随机试验