Forberger Sarah, Reisch Lucia A, van Gorp Peter, Stahl Christoph, Christianson Lara, Halimi Jihan, De Santis Karina Karolina, Malisoux Laurent, de-Magistris Tiziana, Bohn Torsten
Leibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany
Department of Health Science, University of York, York, UK.
BMJ Open. 2024 Jul 31;14(7):e080644. doi: 10.1136/bmjopen-2023-080644.
Recommender systems, digital tools providing recommendations, and digital nudges increasingly affect our lives. The combination of digital nudges and recommender systems is very attractive for its application in preventing overweight and obesity. However, linking recommender systems with personalised digital nudges has a potential yet to be fully exploited. Therefore, this study aims to conduct a scoping review to identify which digital nudges or recommender systems or their combinations have been used in obesity prevention and to map these systems according to the target population, health behaviour, system classification (eg, mechanisms for developing recommendations, delivery channels, personalisation, interconnection, used combination), and system implementation.
The Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews guideline was used to inform protocol development. The eligibility criteria are based on the PCC framework (Population: any human; Concept: recommender systems or digital nudges; Context: obesity prevention). MEDLINE, PsycINFO, Web of Science, CINHAL, Scopus, ACM Digital Library and IEEE Xplore were searched until September 2023. Primary studies with any design published in peer-reviewed academic journals and peer-reviewed conference papers will be included. Data will be extracted into a pre-developed extraction sheet. Results will be synthesised descriptively and narratively.
No ethical approval is required for the scoping review, as data will be obtained from publicly available sources. The results of this scoping review will be published in a peer-reviewed journal, presented at conferences and used to inform the co-creation process and intervention adaptation in the context of a HealthyW8 project (www.healthyw8.eu).
推荐系统、提供推荐的数字工具以及数字助推正日益影响着我们的生活。数字助推与推荐系统的结合在预防超重和肥胖方面的应用极具吸引力。然而，将推荐系统与个性化数字助推相联系的潜力尚未得到充分挖掘。因此，本研究旨在进行一项范围综述，以确定在肥胖预防中使用了哪些数字助推或推荐系统或它们的组合，并根据目标人群、健康行为、系统分类（例如，推荐生成机制、传播渠道、个性化、互联性、使用的组合）以及系统实施情况对这些系统进行梳理。
系统评价和Meta分析扩展的范围综述首选报告项目指南用于指导方案制定。纳入标准基于PCC框架（人群：任何人；概念：推荐系统或数字助推；背景：肥胖预防）。检索了MEDLINE、PsycINFO（心理学文摘数据库）、科学引文索引、护理学与健康领域数据库、Scopus数据库、美国计算机协会数字图书馆和电气与电子工程师协会数据库，检索截止到2023年9月。将纳入在同行评审学术期刊上发表的任何设计的原发性研究以及同行评审会议论文。数据将提取到预先制定的提取表中。结果将进行描述性和叙述性综合分析。
由于数据将从公开可用来源获取，因此范围综述无需伦理批准。本范围综述的结果将发表在同行评审期刊上，在会议上展示，并用于为HealthyW8项目（www.healthyw8.eu）背景下的共同创造过程和干预调整提供参考。
