Department of Mathematics, University of California, Los Angeles, California, United States of America.
Department of Mathematics, Dartmouth College, New Hampshire, United States of America.
PLoS Comput Biol. 2020 Dec 28;16(12):e1008445. doi: 10.1371/journal.pcbi.1008445. eCollection 2020 Dec.
Which suggestions for behavioral modifications, based on mathematical models, are most likely to be followed in the real world? We address this question in the context of human circadian rhythms. Jet lag is a consequence of the misalignment of the body's internal circadian (~24-hour) clock during an adjustment to a new schedule. Light is the clock's primary synchronizer. Previous research has used mathematical models to compute light schedules that shift the circadian clock to a new time zone as quickly as possible. How users adjust their behavior when provided with these optimal schedules remains an open question. Here, we report data collected by wearables from more than 100 travelers as they cross time zones using a smartphone app, Entrain. We find that people rarely follow the optimal schedules generated through mathematical modeling entirely, but travelers who better followed the optimal schedules reported more positive moods after their trips. Using the data collected, we improve the optimal schedule predictions to accommodate real-world constraints. We also develop a scheduling algorithm that allows for the computation of approximately optimal schedules "on-the-fly" in response to disruptions. User burnout may not be critically important as long as the first parts of a schedule are followed. These results represent a crucial improvement in making the theoretical results of past work viable for practical use and show how theoretical predictions based on known human physiology can be efficiently used in real-world settings.
基于数学模型的行为改变建议在现实世界中最有可能被遵循吗?我们在人类昼夜节律的背景下探讨这个问题。时差是身体内部生物钟(约 24 小时)在适应新时间表时失调的结果。光时生物钟的主要同步器。先前的研究使用数学模型来计算光时间表,以最快的速度将生物钟转移到新的时区。当提供这些最佳时间表时,用户如何调整他们的行为仍然是一个悬而未决的问题。在这里,我们报告了通过可穿戴设备从超过 100 名旅行者在使用智能手机应用程序 Entrain 穿越时区时收集的数据。我们发现,人们很少完全按照数学建模生成的最佳时间表进行调整,但更好地遵循最佳时间表的旅行者在旅行后报告的情绪更为积极。利用收集到的数据,我们改进了最佳时间表预测,以适应现实世界的限制。我们还开发了一种调度算法,可以根据干扰情况“实时”计算近似最佳时间表。只要遵守时间表的前几部分,用户的倦怠可能不是至关重要的。这些结果代表了过去工作的理论结果在实际应用中变得可行的重要改进,并展示了如何在实际环境中有效地利用基于已知人类生理学的理论预测。