Reinforcement Learning to Send Reminders at Right Moments in Smartphone Exercise Application: A Feasibility Study.
Reinforcement Learning to Send Reminders at Right Moments in Smartphone Exercise Application: A Feasibility Study.
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DOI：
10.3390/ijerph18116059
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发表时间：
2021-06-04
影响因子：
--
通讯作者：
Kröse B
中科院分区：
文献类型：
--
作者：
Wang S;Sporrel K;van Hoof H;Simons M;de Boer RDD;Ettema D;Nibbeling N;Deutekom M;Kröse B
Just-in-time adaptive intervention （JITAI）近年来受到关注，已有研究表明它是移动医疗干预领域中一种有效的策略。确定干预的正确时机是一个关键组成部分。本文将强化学习（RL）技术应用于智能手机运动应用程序中，以促进身体活动。这个RL模型根据用户的临时上下文信息（即时间和日历），自适应地确定发送有限数量通知的“正确”时间。我们进行了为期四周的试验研究，以检验我们的模型在真实目标用户中的可行性。RL模型在干预的第四周发送JITAI提醒，而参与者只能在前三周访问应用程序的其他功能。11名目标用户注册了这项研究，并分析了7名参与者使用该应用程序4周并接收干预提醒的数据。我们不仅从应用数据中分析用户收到提醒后的反应行为，还通过问卷调查和离职访谈探讨用户对提醒的体验。结果表明，83.3%的自适应时刻提醒能在50分钟内引起用户反应，66.7%的干预周体力活动在提醒发出后5小时内完成。我们的研究结果表明了RL模型的可用性，而发送提醒的时间可以根据经验教训进一步改进。
Just-in-time adaptive intervention (JITAI) has gained attention recently and previous studies have indicated that it is an effective strategy in the field of mobile healthcare intervention. Identifying the right moment for the intervention is a crucial component. In this paper the reinforcement learning (RL) technique has been used in a smartphone exercise application to promote physical activity. This RL model determines the ‘right’ time to deliver a restricted number of notifications adaptively, with respect to users’ temporary context information (i.e., time and calendar). A four-week trial study was conducted to examine the feasibility of our model with real target users. JITAI reminders were sent by the RL model in the fourth week of the intervention, while the participants could only access the app’s other functionalities during the first 3 weeks. Eleven target users registered for this study, and the data from 7 participants using the application for 4 weeks and receiving the intervening reminders were analyzed. Not only were the reaction behaviors of users after receiving the reminders analyzed from the application data, but the user experience with the reminders was also explored in a questionnaire and exit interviews. The results show that 83.3% reminders sent at adaptive moments were able to elicit user reaction within 50 min, and 66.7% of physical activities in the intervention week were performed within 5 h of the delivery of a reminder. Our findings indicated the usability of the RL model, while the timing of the moments to deliver reminders can be further improved based on lessons learned.
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影响因子：
3.6
作者：
Thomas Craig KJ;Morgan LC;Chen CH;Michie S;Fusco N;Snowdon JL;Scheufele E;Gagliardi T;Sill S
通讯作者：
Sill S
影响因子：
4.2
作者：
Thomas, J. Graham;Bond, Dale S.
通讯作者：
Bond, Dale S.
影响因子：
3.1
作者：
Forman, Evan M.;Kerrigan, Stephanie G.;Moskow, Danielle
通讯作者：
Moskow, Danielle
DOI：
10.1186/1748-5908-6-42
发表时间：
2011-04-23
期刊：
Implementation science : IS
影响因子：
--
作者：
Michie S;van Stralen MM;West R
通讯作者：
West R
DOI：
10.1145/2632048.2636082
发表时间：
2014
期刊：
Proceedings of the ... ACM International Conference on Ubiquitous Computing . UbiComp (Conference)
影响因子：
--
作者：
Sarker H;Sharmin M;Ali AA;Rahman MM;Bari R;Hossain SM;Kumar S
通讯作者：
Kumar S