体力活动干预时机的个性化:范围综述。
Personalization of Intervention Timing for Physical Activity: Scoping Review.
机构信息
Department of Information Systems and Analytics, School of Computing, National University of Singapore, Singapore, Singapore.
出版信息
JMIR Mhealth Uhealth. 2022 Feb 28;10(2):e31327. doi: 10.2196/31327.
BACKGROUND
The use of sensors in smartphones, smartwatches, and wearable devices has facilitated the personalization of interventions to increase users' physical activity (PA). Recent research has focused on evaluating the effects of personalized interventions in improving PA among users. However, it is critical to deliver the intervention at an appropriate time to each user to increase the likelihood of adoption of the intervention. Earlier review studies have not focused on the personalization of intervention timing for increasing PA.
OBJECTIVE
This review aims to examine studies of information technology-based PA interventions with personalized intervention timing (PIT); identify inputs (eg, user location) used by the system for generating the PIT, the techniques and methods used for generating the PIT, the content of the PA intervention, and delivery mode of the intervention; and identify gaps in existing literature and suggest future research directions.
METHODS
A scoping review was undertaken using PsycINFO, PubMed, Scopus, and Web of Science databases based on a structured search query. The main inclusion criteria were as follows: the study aimed to promote PA, included some form of PIT, and used some form of information technology for delivery of the intervention to the user. If deemed relevant, articles were included in this review after removing duplicates and examining the title, abstract, and full text of the shortlisted articles.
RESULTS
The literature search resulted in 18 eligible studies. In this review, 72% (13/18) of the studies focused on increasing PA as the primary objective, whereas it was the secondary focus in the remaining studies. The inputs used to generate the PIT were categorized as user preference, activity level, schedule, location, and predicted patterns. On the basis of the intervention technique, studies were classified as manual, semiautomated, or automated. Of these, the automated interventions were either knowledge based (based on rules or guidelines) or data driven. Of the 18 studies, only 6 (33%) evaluated the effectiveness of the intervention and reported positive outcomes.
CONCLUSIONS
This work reviewed studies on PIT for PA interventions and identified several aspects of the interventions, that is, inputs, techniques, contents, and delivery mode. The reviewed studies evaluated PIT in conjunction with other personalization approaches such as activity recommendation, with no study evaluating the effectiveness of PIT alone. On the basis of the findings, several important directions for future research are also highlighted in this review.
背景
智能手机、智能手表和可穿戴设备中传感器的使用促进了干预措施的个性化,以增加用户的身体活动(PA)。最近的研究集中在评估个性化干预措施对提高用户 PA 的效果上。然而,为了增加干预措施的采用率,关键是要在适当的时间向每个用户提供干预措施。早期的综述研究并未关注增加 PA 的干预时间的个性化。
目的
本综述旨在研究基于信息技术的 PA 干预措施,这些干预措施具有个性化干预时间(PIT);确定系统用于生成 PIT 的输入(例如,用户位置)、用于生成 PIT 的技术和方法、PA 干预的内容以及干预的传递模式;并确定现有文献中的差距,并提出未来的研究方向。
方法
根据结构化检索查询,使用 PsycINFO、PubMed、Scopus 和 Web of Science 数据库进行了范围综述。主要纳入标准如下:研究旨在促进 PA,包括某种形式的 PIT,并使用某种形式的信息技术向用户传递干预措施。如果认为相关,在删除重复项并检查入选文章的标题、摘要和全文后,将文章纳入本综述。
结果
文献检索共纳入 18 项符合条件的研究。在本综述中,72%(13/18)的研究将增加 PA 作为主要目标,而其余研究则将其作为次要目标。用于生成 PIT 的输入分为用户偏好、活动水平、日程安排、位置和预测模式。根据干预技术,研究分为手动、半自动和自动。在这些研究中,自动干预措施要么是基于知识(基于规则或指南),要么是基于数据驱动的。在 18 项研究中,只有 6 项(33%)评估了干预措施的有效性,并报告了积极的结果。
结论
本工作综述了关于 PA 干预措施的 PIT 研究,并确定了干预措施的几个方面,即输入、技术、内容和传递模式。综述中的研究将 PIT 与其他个性化方法(如活动推荐)一起评估,没有研究单独评估 PIT 的效果。基于这些发现,本综述还强调了未来研究的几个重要方向。