Assessing Real-Time Moderation for Developing Adaptive Mobile Health Interventions for Medical Interns: Micro-Randomized Trial
Assessing Real-Time Moderation for Developing Adaptive Mobile Health Interventions for Medical Interns: Micro-Randomized Trial
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DOI：
10.2196/15033
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发表时间：
2020-03-31
影响因子：
7.4
通讯作者：
Wu, Zhenke
中科院分区：
文献类型：
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作者：
NeCamp, Timothy;Sen, Srijan;Wu, Zhenke
背景：处于压力大的工作环境中的人经常会遇到心理健康问题，如抑郁症。降低抑郁症发病率是困难的，因为持续紧张的工作环境和时间或资源不足，以获得传统的精神卫生保健服务。移动的健康干预措施为在真实的世界中提供实时干预措施提供了机会。此外，干预的递送时间可以基于利用移动终端收集的实时数据。到目前为止，数据和分析通知交付mHealth干预措施的时间一般lack.Objective：本研究旨在探讨何时提供mHealth干预措施，以个人在紧张的工作环境，以改善他们的行为和心理健康。移动健康干预措施针对3类行为：情绪，活动和睡眠。这些干预措施旨在改善3种不同的结果：每周情绪（通过每日调查评估），每周步数和每周睡眠时间。我们探讨了当这些干预措施是最有效的，根据以前的情绪，步骤，和睡眠scores.Methods：我们进行了为期6个月的微随机试验1565医学实习生。在医生实习培训的第一年，医学实习是高度紧张的，导致抑郁症的发生率比普通人群高出几倍。每周，实习生被随机分配接收与特定类别（情绪，活动，睡眠或无通知）相关的推送通知。每天，我们收集实习生的日常情绪效价、睡眠和步数数据。我们通过前一周的情绪、步数和睡眠来评估因果效应适度。具体来说，我们研究了包含情绪，活动和睡眠消息的通知的效果的变化，这些消息是基于前一周的情绪，步骤和睡眠分数。适度进行了评估与加权和集中的最小二乘estimate.Results：我们发现，前一周的情绪负缓和的影响，通知对当前一周的情绪，估计适度为-0.052（P=.001）。也就是说，当被研究的实习生在前一周情绪低落时，通知对情绪有更好的影响。类似地，我们发现前一周的步数负向调节活动通知对当前周的步数的影响，估计调节为-0.039（P=.01），并且前一周的睡眠负向调节睡眠通知对当前周的睡眠的影响，估计调节为-0.075（P
Background: Individuals in stressful work environments often experience mental health issues, such as depression. Reducing depression rates is difficult because of persistently stressful work environments and inadequate time or resources to access traditional mental health care services. Mobile health (mHealth) interventions provide an opportunity to deliver real-time interventions in the real world. In addition, the delivery times of interventions can be based on real-time data collected with a mobile device. To date, data and analyses informing the timing of delivery of mHealth interventions are generally lacking.Objective: This study aimed to investigate when to provide mHealth interventions to individuals in stressful work environments to improve their behavior and mental health. The mHealth interventions targeted 3 categories of behavior: mood, activity, and sleep. The interventions aimed to improve 3 different outcomes: weekly mood (assessed through a daily survey), weekly step count, and weekly sleep time. We explored when these interventions were most effective, based on previous mood, step, and sleep scores.Methods: We conducted a 6-month micro-randomized trial on 1565 medical interns. Medical internship, during the first year of physician residency training, is highly stressful, resulting in depression rates several folds higher than those of the general population. Every week, interns were randomly assigned to receive push notifications related to a particular category (mood, activity, sleep, or no notifications). Every day, we collected interns' daily mood valence, sleep, and step data. We assessed the causal effect moderation by the previous week's mood, steps, and sleep. Specifically, we examined changes in the effect of notifications containing mood, activity, and sleep messages based on the previous week's mood, step, and sleep scores. Moderation was assessed with a weighted and centered least-squares estimator.Results: We found that the previous week's mood negatively moderated the effect of notifications on the current week's mood with an estimated moderation of -0.052 (P=.001). That is, notifications had a better impact on mood when the studied interns had a low mood in the previous week. Similarly, we found that the previous week's step count negatively moderated the effect of activity notifications on the current week's step count, with an estimated moderation of -0.039 (P=.01) and that the previous week's sleep negatively moderated the effect of sleep notifications on the current week's sleep with an estimated moderation of -0.075 (P