How Notifications Affect Engagement With a Behavior Change App: Results From a Micro-Randomized Trial.
How Notifications Affect Engagement With a Behavior Change App: Results From a Micro-Randomized Trial.
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通知如何影响行为改变应用的用户粘性：来自微随机试验的结果。
DOI：
10.2196/38342
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发表时间：
2023-06-09
影响因子：
5
通讯作者：
Williamson, Elizabeth
中科院分区：
文献类型：
--
作者：
Bell, Lauren;Garnett, Claire;Bao, Yihan;Cheng, Zhaoxi;Qian, Tianchen;Perski, Olga;Potts, Henry W. W.;Williamson, Elizabeth
关键词：
Drink Less是一款行为改变应用程序，旨在帮助英国的高风险饮酒者减少饮酒量。该应用程序包括一个每日通知，要求用户“请完成您的饮料和情绪日记”，但我们不了解通知对参与度的因果关系，也不知道如何改善少喝酒的这一组成部分。我们开发了一个新的银行30个新的消息，以增加用户的反思动机，参与少喝酒。这项研究旨在确定标准和新的通知如何影响参与度。我们的目标是估计通知对近期参与的因果影响，探索这种影响是否随时间而变化，并创建证据库，以进一步为通知政策的优化提供信息。我们进行了一项微随机试验（MRT），增加了2个平行组。入选标准为同意参加试验的少饮酒者，自我报告基线酒精使用障碍识别测试评分≥8，居住在英国，年龄≥18岁，并报告有兴趣少饮酒。我们的MRT随机抽取了350名新用户，以测试在下载Drink Less后的前30天内，与没有收到通知相比，收到通知是否会增加在随后一个小时内打开应用程序的概率。每天晚上8点，用户随机抽取30%的概率收到标准消息，30%的概率收到新消息，或者有40%的概率收不到消息我们还探索了脱离的时间，将60%的合格用户随机分配到MRT（n=350），40%的合格用户随机分配到2个平行组，接受无通知政策（n=98）或标准通知政策（n=121）。辅助分析探讨了最近的习惯化和参与状态的影响适度。与未收到通知相比，收到通知后，在接下来的一个小时内打开应用程序的概率增加了3.5倍（95% CI 2.91-4.25）。这两种信息同样有效。随着时间的推移，通知的效果没有发生重大变化。处于已经参与状态的用户将新通知效果降低了0.80（95% CI 0.55-1.16），尽管不显著。在3组中，至脱离接触的时间无显著差异。我们发现参与对通知的短期影响很大，但在接收标准固定通知、根本没有通知或MRT内通知的随机序列之间，用户的脱离时间没有总体差异。通知的强烈近期效应为定向通知提供了机会，以增加“即时”参与。需要进一步优化，以改善长期参与。RR2-10.2196/18690
Drink Less is a behavior change app to help higher-risk drinkers in the United Kingdom reduce their alcohol consumption. The app includes a daily notification asking users to “Please complete your drinks and mood diary,” yet we did not understand the causal effect of the notification on engagement nor how to improve this component of Drink Less. We developed a new bank of 30 new messages to increase users’ reflective motivation to engage with Drink Less. This study aimed to determine how standard and new notifications affect engagement. Our objective was to estimate the causal effect of the notification on near-term engagement, to explore whether this effect changed over time, and to create an evidence base to further inform the optimization of the notification policy. We conducted a micro-randomized trial (MRT) with 2 additional parallel arms. Inclusion criteria were Drink Less users who consented to participate in the trial, self-reported a baseline Alcohol Use Disorders Identification Test score of ≥8, resided in the United Kingdom, were aged ≥18 years, and reported interest in drinking less alcohol. Our MRT randomized 350 new users to test whether receiving a notification, compared with receiving no notification, increased the probability of opening the app in the subsequent hour, over the first 30 days since downloading Drink Less. Each day at 8 PM, users were randomized with a 30% probability of receiving the standard message, a 30% probability of receiving a new message, or a 40% probability of receiving no message. We additionally explored time to disengagement, with the allocation of 60% of eligible users randomized to the MRT (n=350) and 40% of eligible users randomized in equal number to the 2 parallel arms, either receiving the no notification policy (n=98) or the standard notification policy (n=121). Ancillary analyses explored effect moderation by recent states of habituation and engagement. Receiving a notification, compared with not receiving a notification, increased the probability of opening the app in the next hour by 3.5-fold (95% CI 2.91-4.25). Both types of messages were similarly effective. The effect of the notification did not change significantly over time. A user being in a state of already engaged lowered the new notification effect by 0.80 (95% CI 0.55-1.16), although not significantly. Across the 3 arms, time to disengagement was not significantly different. We found a strong near-term effect of engagement on the notification, but no overall difference in time to disengagement between users receiving the standard fixed notification, no notification at all, or the random sequence of notifications within the MRT. The strong near-term effect of the notification presents an opportunity to target notifications to increase “in-the-moment” engagement. Further optimization is required to improve the long-term engagement. RR2-10.2196/18690
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作者：
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作者：
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制定和评估复杂的干预措施：新的医学研究委员会指南。
DOI：
10.1136/bmj.a1655
发表时间：
2008-09-29
期刊：
BMJ (Clinical research ed.)
影响因子：
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作者：
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通讯作者：
Medical Research Council Guidance