School of Psychological Sciences, Tel Aviv University, Tel Aviv, Israel.
Nicotine Tob Res. 2018 Nov 15;20(12):1515-1518. doi: 10.1093/ntr/ntx223.
Smartphone applications (apps) for smoking cessation are becoming increasingly available, but their efficacy remains to be demonstrated. We conducted a pilot study of SmokeBeat, a novel app designed for use with smartwatches and wristbands. SmokeBeat is powered by a data analytics software platform that processes information from the sensors embedded in wearables. It relies on an original algorithm to identify in real time the hand-to-mouth gestures that characterize smoking a cigarette. We examined whether merely monitoring and notifying smokers on smoking episodes in real time via the SmokeBeat app would lead to reduction in smoking.
Forty smokers (9 women and 31 men) who expressed a wish to reduce or quit smoking were randomly assigned to using the SmokeBeat app for 30 days or to a wait-list control group. All participants completed questionnaires at baseline and at the end of the study, including their level of smoking. Smokers in the experimental condition were notified whenever the SmokeBeat system detected a smoking episode and were asked to confirm or deny it.
The SmokeBeat algorithm correctly detected over 80% of the smoking episodes and produced very few false alarms. According to both self-report and detection of smoking episodes by the SmokeBeat system, smokers in the experimental condition showed a significant decline in smoking rate over the 30-day trial (p < .001). There was no change in the smoking rate of the control group.
These preliminary results suggest that automatic monitoring of smoking episodes and alerting the smoker in real time may facilitate smoking reduction in motivated smokers.
Raising the awareness of smokers to the act of smoking in real time, as the SmokeBeat app is able to do, can counter the automaticity of the smoking habit. Bringing smoking under conscious awareness may benefit smokers who are motivated to reduce or quit smoking to gain better control of their smoking behavior and reduce cigarette intake.
用于戒烟的智能手机应用程序（apps）越来越多，但它们的疗效仍有待证明。我们对一款名为 SmokeBeat 的新型应用程序进行了试点研究，该应用程序专为智能手表和腕带设计。SmokeBeat 由一个数据分析软件平台提供支持，该平台处理可穿戴设备中传感器的信息。它依靠一个原始算法来实时识别表征吸烟的手到嘴动作。我们研究了仅仅通过 SmokeBeat 应用程序实时监测和通知吸烟者吸烟事件是否会导致吸烟量减少。
40 名吸烟者（9 名女性和 31 名男性）表示希望减少或戒烟，他们被随机分配使用 SmokeBeat 应用程序 30 天或等待对照组。所有参与者在基线和研究结束时完成了问卷，包括他们的吸烟水平。每当 SmokeBeat 系统检测到吸烟事件时，实验组的吸烟者都会收到通知，并被要求确认或否认。
SmokeBeat 算法正确检测到 80%以上的吸烟事件，且产生的误报很少。根据自我报告和 SmokeBeat 系统检测到的吸烟事件，实验组在 30 天的试验中吸烟率显著下降（p <.001）。对照组的吸烟率没有变化。
这些初步结果表明，自动监测吸烟事件并实时提醒吸烟者可能有助于有动机的吸烟者减少吸烟。
实时提高吸烟者对吸烟行为的意识，就像 SmokeBeat 应用程序能够做到的那样，可以对抗吸烟习惯的自动性。将吸烟带入有意识的意识中可能会使有动机减少或戒烟的吸烟者受益，帮助他们更好地控制吸烟行为并减少吸烟量。
