Department of Computer Science, KU Leuven, Leuven, Belgium.
Faculty of Health Sciences, University of Maribor, Maribor, Slovenia.
J Med Internet Res. 2021 Jun 29;23(6):e18035. doi: 10.2196/18035.
Health recommender systems (HRSs) offer the potential to motivate and engage users to change their behavior by sharing better choices and actionable knowledge based on observed user behavior.
We aim to review HRSs targeting nonmedical professionals (laypersons) to better understand the current state of the art and identify both the main trends and the gaps with respect to current implementations.
We conducted a systematic literature review according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines and synthesized the results. A total of 73 published studies that reported both an implementation and evaluation of an HRS targeted to laypersons were included and analyzed in this review.
Recommended items were classified into four major categories: lifestyle, nutrition, general health care information, and specific health conditions. The majority of HRSs use hybrid recommendation algorithms. Evaluations of HRSs vary greatly; half of the studies only evaluated the algorithm with various metrics, whereas others performed full-scale randomized controlled trials or conducted in-the-wild studies to evaluate the impact of HRSs, thereby showing that the field is slowly maturing. On the basis of our review, we derived five reporting guidelines that can serve as a reference frame for future HRS studies. HRS studies should clarify who the target user is and to whom the recommendations apply, what is recommended and how the recommendations are presented to the user, where the data set can be found, what algorithms were used to calculate the recommendations, and what evaluation protocol was used.
There is significant opportunity for an HRS to inform and guide health actions. Through this review, we promote the discussion of ways to augment HRS research by recommending a reference frame with five design guidelines.
健康推荐系统 (HRS) 通过分享基于观察到的用户行为的更好选择和可操作的知识，为激励和吸引用户改变行为提供了潜力。
我们旨在审查针对非专业人士（外行）的 HRS，以更好地了解当前的技术水平，并确定当前实施的主要趋势和差距。
我们根据 PRISMA（系统评价和荟萃分析的首选报告项目）指南进行了系统的文献回顾，并对结果进行了综合分析。共纳入并分析了 73 篇已发表的研究报告，这些研究报告均报告了针对外行的 HRS 的实施和评估。
推荐项目被分为四大类：生活方式、营养、一般保健信息和特定健康状况。大多数 HRS 使用混合推荐算法。HRS 的评估差异很大；一半的研究仅使用各种指标评估算法，而其他研究则进行全面的随机对照试验或进行实地研究来评估 HRS 的影响，从而表明该领域正在逐步成熟。基于我们的综述，我们得出了五条报告指南，可作为未来 HRS 研究的参考框架。HRS 研究应明确目标用户是谁以及推荐适用于谁，推荐什么以及如何向用户展示推荐，数据集可以在哪里找到，使用了哪些算法来计算推荐，以及使用了哪些评估方案。
HRS 有很大的机会为健康行为提供信息和指导。通过本次综述，我们通过推荐包含五条设计指南的参考框架，促进了对增强 HRS 研究的讨论。
