智能手机方法在评估饮食、酒精和烟草使用方面的测量特性:卡塔尔世界杯8强波胆分析系统评价%A桑顿，%A Osman,Bridie %A Champion,Katrina %A Green,Olivia %A Wescott,Annie B %A Gardner,Lauren %A Stewart,Courtney %A Visontay,Rachel %A Whife,Jesse %A Parmenter,Belinda %A Birrell,Louise %A Bryant,Zachary %A Chapman,Cath %A Lubans,David %A Slade,Tim %A Torous,John %A Teesson,Maree %A Van de Ven,Pepijn %+悉尼大学心理健康和物质使用研究玛蒂尔达中心，2006年，悉尼坎珀当，简·福斯·罗素大楼6层，澳大利亚，61 0403744089,louise.thornton@sydney.edu.au %K智能手机%K应用程序%K酒精%K吸烟%K饮食%K测量%K手机%D回顾Mhealth Uhealth背景:不良饮食、饮酒和吸烟已被确定为慢性疾病的重要决定因素，如心血管疾病、糖尿病和癌症。智能手机有潜力提供一种实时的、普遍的、不显眼的、具有成本效益的方式来衡量这些健康行为，并向用户提供即时反馈。尽管如此，使用智能手机来测量这些行为的有效性在很大程度上是未知的。目的:我们回顾的目的是确定现有的基于智能手机的方法来测量这些健康行为，并批判性地评估其测量特性的质量。方法:我们于2020年3月系统检索了Ovid MEDLINE、Embase (Elsevier)、Cochrane Library (Wiley)、PsycINFO (EBSCOhost)、CINAHL (EBSCOhost)、Web of Science (Clarivate)、SPORTDiscus (EBSCOhost)和IEEE Xplore数字图书馆数据库。用英语写的文章;报告通过智能手机测量饮食、酒精使用或烟草使用;并且报告了至少一个测量属性(例如，有效性，可靠性和响应性)是合格的。 The methodological quality of the included studies was assessed using the Consensus-Based Standards for the Selection of Health Measurement Instruments Risk of Bias checklist. Outcomes were summarized in a narrative synthesis. This systematic review was registered with PROSPERO, identifier CRD42019122242. Results: Of 12,261 records, 72 studies describing the measurement properties of smartphone-based approaches to measure diet (48/72, 67%), alcohol use (16/72, 22%), and tobacco use (8/72, 11%) were identified and included in this review. Across the health behaviors, 18 different measurement techniques were used in smartphones. The measurement properties most commonly examined were construct validity, measurement error, and criterion validity. The results varied by behavior and measurement approach, and the methodological quality of the studies varied widely. Most studies investigating the measurement of diet and alcohol received very good or adequate methodological quality ratings, that is, 73% (35/48) and 69% (11/16), respectively, whereas only 13% (1/8) investigating the measurement of tobacco use received a very good or adequate rating. Conclusions: This review is the first to provide evidence regarding the different types of smartphone-based approaches currently used to measure key behavioral risk factors for chronic diseases (diet, alcohol use, and tobacco use) and the quality of their measurement properties. A total of 19 measurement techniques were identified, most of which assessed dietary behaviors (48/72, 67%). Some evidence exists to support the reliability and validity of using smartphones to assess these behaviors; however, the results varied by behavior and measurement approach. The methodological quality of the included studies also varied. Overall, more high-quality studies validating smartphone-based approaches against criterion measures are needed. Further research investigating the use of smartphones to assess alcohol and tobacco use and objective measurement approaches is also needed. International Registered Report Identifier (IRRID): RR2-https://doi.org/10.1186/s13643-020-01375-w %M 35175212 %R 10.2196/27337 %U https://mhealth.www.mybigtv.com/2022/2/e27337 %U https://doi.org/10.2196/27337 %U http://www.ncbi.nlm.nih.gov/pubmed/35175212