Feasibility of Using Wearable Technology for Just-in-Time Prediction of Smoking Lapses

拟议研究路线的长期目标是开发以技术为基础的干预措施，以增加 通过提供及时的支持来最大限度地减少吸烟引发铅的可能性，从而提高戒烟率 对吸烟的疏忽。为此，我们建议使用连续的生理和环境时间- 从广泛使用的消费者可穿戴技术中嵌入的传感器获得的系列数据，以构建 用于检测吸烟事件的前因(例如，应激源、吸烟线索等)的预测模型。在这 项目中，我们将对吸烟者在临时吸烟期和非吸烟期进行观察研究。 他们试图戒烟的时期。在观察期间，吸烟者将佩戴三种装置 能够收集生理和运动数据。我们假设消费者可穿戴技术可以 可靠地捕捉随机吸烟期间吸烟前事件的生理反应 在停止期内并在终止期间之前失效。证明迫在眉睫的吸烟可以 预测将导致开发和测试可通过以下方式提供的即时干预 智能手机或智能手表等设备上的定制消息。

The long-term goal of the proposed line of research is to develop technology-based interventions that increase smoking cessation rates by delivering just-in-time support to minimize the likelihood that smoking triggers lead to smoking lapses. Towards this objective we propose to use continuous physiological and environmental time- series data obtained from sensors embedded in widely used consumer wearable technology to construct a predictive model for detecting antecedents of smoking events (e.g., stressors, smoking cues, etc). In this project, we will conduct an observational study of smokers during an ad libitum smoking period and during a period in which they attempt to quit smoking. During the observation period, smokers will wear three devices capable of collecting physiological and motion data. We hypothesize that consumer wearable technology can reliably capture physiological response to events that precede smoking during the ad libitum smoking period and precede lapse during the cessation period. Demonstrating that imminent smoking can be predicted would lead to the development and testing of just-in-time interventions that can be delivered via customized messaging on devices such as smartphones or smartwatches.