@文章{信息:doi/10.2196/27337，作者=“桑顿，路易丝和奥斯曼，布里迪和钱皮恩，卡特里娜和格林，奥利维亚和韦斯科特，安妮B和加德纳，劳伦A和斯图尔特，考特尼和维森泰，雷切尔和怀特，杰西和帕门特，贝琳达和比雷尔，路易丝和布莱恩特，扎卡里和查普曼，凯斯和鲁本斯，大卫和斯拉德，蒂姆和托罗斯，约翰和蒂森，玛丽和范德文，佩皮金”，标题=“智能手机方法评估饮食，酒精使用和烟草使用的测量属性:“系统评论”，期刊=“JMIR Mhealth Uhealth”，年=“2022”，月=“Feb”，日=“17”，卷=“10”，号=“2”，页=“e27337”，关键词=“智能手机;应用程序;酒精;吸烟;饮食;测量;背景:不良饮食、酗酒和吸烟已被确定为慢性疾病(如心血管疾病、糖尿病和癌症)的重要决定因素。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。 Objective: The aim of our review is to identify existing smartphone-based approaches to measure these health behaviors and critically appraise the quality of their measurement properties. Methods: We conducted a systematic search of the Ovid MEDLINE, Embase (Elsevier), Cochrane Library (Wiley), PsycINFO (EBSCOhost), CINAHL (EBSCOHost), Web of Science (Clarivate), SPORTDiscus (EBSCOhost), and IEEE Xplore Digital Library databases in March 2020. Articles that were written in English; reported measuring diet, alcohol use, or tobacco use via a smartphone; and reported on at least one measurement property (eg, validity, reliability, and responsiveness) were eligible. 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 ", issn="2291-5222", doi="10.2196/27337", url="https://mhealth.www.mybigtv.com/2022/2/e27337", url="https://doi.org/10.2196/27337", url="http://www.ncbi.nlm.nih.gov/pubmed/35175212" }