Wearable Technologies and Health Behaviors: New Data and New Methods to Understand Population Health
研究了一项针对大型企业员工的可穿戴设备随机对照试验，发现其对睡眠和锻炼行为的影响在统计上显著但经济上很小，并利用机器学习分析了异质性处理效应。
We study a randomized control trial in a large employer population of access to “wearable” technologies and the associated planning and monitoring tools on improved health behaviors (sleep and exercise). Both ITT and IV estimates based on actual plan enrollment for the treatment group suggest statistically significant but economically small changes in behavior after three months. We then implement machine learning-based models to assess treatment effect heterogeneity. We find little evidence for heterogeneous treatment effects base on observables. We also present detailed data on sleep patterns underscoring the value of this new data source to researchers.