Wang Yongzhen, Liu Xiaozhong, Börner Katy, Lin Jun, Ju Yingnan, Sun Changlong, Si Luo
Institute of Science of Science and S&T Management, Dalian University of Technology, Dalian, China.
Department of Computer Science, Worcester Polytechnic Institute, Worcester, MA, USA.
Digit Health. 2022 Mar 28;8:20552076221089092. doi: 10.1177/20552076221089092. eCollection 2022 Jan-Dec.
Ubiquitous internet access is reshaping the way we live, but it is accompanied by unprecedented challenges in preventing chronic diseases that are usually planted by long exposure to unhealthy lifestyles. This paper proposes leveraging online shopping behaviors as a proxy for personal lifestyle choices to improve chronic disease prevention literacy, targeted for times when e-commerce user experience has been assimilated into most people's everyday lives.
Longitudinal query logs and purchase records from 15 million online shoppers were accessed, constructing a broad spectrum of lifestyle features covering various product categories and buyer personas. Using the lifestyle-related information preceding online shoppers' first purchases of specific prescription drugs, we could determine associations between their past lifestyle choices and whether they suffered from a particular chronic disease.
Novel lifestyle risk factors were discovered in two exemplars-depression and type 2 diabetes, most of which showed reasonable consistency with existing healthcare knowledge. Further, such empirical findings could be adopted to locate online shoppers at higher risk of these chronic diseases with decent accuracy [i.e. (area under the receiver operating characteristic curve) AUC=0.68 for depression and AUC=0.70 for type 2 diabetes], closely matching the performance of screening surveys benchmarked against medical diagnosis.
Mining online shopping behaviors can point medical experts to a series of lifestyle issues associated with chronic diseases that are less explored to date. Hopefully, unobtrusive chronic disease surveillance via e-commerce sites can grant consenting individuals a privilege to be connected more readily with the medical profession and sophistication.
无处不在的互联网接入正在重塑我们的生活方式，但在预防通常因长期接触不健康生活方式而引发的慢性病方面，它也带来了前所未有的挑战。本文提出利用网络购物行为作为个人生活方式选择的代表，以提高慢性病预防素养，这适用于电子商务用户体验已融入大多数人日常生活的时代。
获取了1500万在线购物者的纵向查询日志和购买记录，构建了涵盖各种产品类别和买家角色的广泛生活方式特征。利用在线购物者首次购买特定处方药之前的生活方式相关信息，我们可以确定他们过去的生活方式选择与是否患有特定慢性病之间的关联。
在抑郁症和2型糖尿病这两个例子中发现了新的生活方式风险因素，其中大多数与现有的医疗保健知识显示出合理的一致性。此外，这些实证结果可用于以相当高的准确性定位患这些慢性病风险较高的在线购物者[即抑郁症的受试者工作特征曲线下面积（AUC）=0.68，2型糖尿病的AUC=0.70]，与以医学诊断为基准的筛查调查表现相近。
挖掘网络购物行为可以让医学专家了解一系列与慢性病相关的、迄今较少被探索的生活方式问题。希望通过电子商务网站进行的不显眼的慢性病监测能够让同意参与的个人更容易与医疗专业人员和医疗服务接轨。
