Does the use of mobile applications or mobile health technology improve diet quality in adults? A protocol for a systematic literature review

HRB Open Research(2022)

引用 2|浏览6
暂无评分
摘要
Background: Mobile technology has grown at an exceptional rate and is now a huge part of our daily living. This use of mobile technology has opened up new possibilities in treating health, with almost half of the current applications linked to the mHealth sector. In particular, dietary measurement, applications have become very accessible and very popular. As dietary issues have become more prevalent, more mobile and mHealth applications offer various solutions. This systematic review aims to address if the use of such mobile applications or mobile health technology can improve diet quality in adults that interact with them. Methods: A systematic review of randomised controlled trials (RCTs) and non-randomised controlled trials (NRCTs) will be conducted. The Cumulative Index to Nursing and Allied Health Literature (Cinahl), The American Psychological Association’s (APA Psycinfo), and PubMed will be searched from January 2010 to November 2021. Primary outcomes will include identifying if adults who use mobile applications and health technology improve their diet quality compared to adults who do not use this technology. Study selection will follow the Preferred Reporting Items for Systematic Reviews and MetaAnalyses (PRISMA) guidelines. The methodological appraisal of the studies will be assessed independently by two different reviewers (AS and JR) using the Cochrane Risk-of-Bias Tool for RCTs and the Risk-of Bias In Non-Randomised Studies Tool for NRCTs. Ethics and dissemination: Ethical approval is not essential for this systematic review. Only data from studies that are publically available from previously published studies will be used. The findings of this systematic review will be submitted for publication in a peer-reviewed journal and presented at relevant conferences. PROSPERO registration: CRD42021240224 (01/03/2021).
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要