@文章{信息:doi/10.2196/32643，作者=“Mackey, Rachel和Gleason, Ann和Ciulla, Robert”，标题=“一种评估移动应用程序的新方法(应用程序评级清单):发展研究”，期刊=“JMIR移动健康Uhealth”，年=“2022”，月=“4”，日=“15”，卷=“10”，数=“4”，页=“e32643”，关键词=“移动健康应用程序;应用评级;App分析方法;应用市场调研;背景:由于缺乏客观的指导方针，无法从现有的数千个应用程序中识别出高质量的应用程序，因此无法将与健康相关的应用程序选择和整合到患者护理中。目的:本研究旨在评估由国防健康局互联健康部门开发的应用程序评级清单，以支持临床决策中有关应用程序的选择，并评估医疗和行为应用程序。方法:为了提高工具的性能，消除项目冗余，减少评分系统的主观性，并确保App评分量表衍生结果的广泛应用，量表的开发包括3轮验证测试和2个为期6个月的试用期。开发集中于内容有效性测试、维度(即，工具的标准是否按照可操作的方式执行)、因素和共性分析，以及互译者可靠性(在开发过程中，可靠性得分从0.62提高到0.95)。结果:在开发阶段，我们对248款应用进行了评估，共收集了6944个数据点，并最终形成了包含28个项目、3个类别的应用评级系统。应用评级清单为以下三个类别产生分数:证据(6项)，内容(11项)和可定制性(11项)。 The final (fourth) metric is the total score, which constitutes the sum of the 3 categories. All 28 items are weighted equally; no item is considered more (or less) important than any other item. As the scoring system is binary (either the app contains the feature or it does not), the ratings' results are not dependent on a rater's nuanced assessments. Conclusions: Using predetermined search criteria, app ratings begin with an environmental scan of the App Store and Google Play. This first step in market research funnels hundreds of apps in a given disease category down to a manageable top 10 apps that are, thereafter, rated using the App Rating Inventory. The category and final scores derived from the rating system inform the clinician about whether an app is evidence informed and easy to use. Although a rating allows a clinician to make focused decisions about app selection in a context where thousands of apps are available, clinicians must weigh the following factors before integrating apps into a treatment plan: clinical presentation, patient engagement and preferences, available resources, and technology expertise. ", issn="2291-5222", doi="10.2196/32643", url="https://mhealth.www.mybigtv.com/2022/4/e32643", url="https://doi.org/10.2196/32643", url="http://www.ncbi.nlm.nih.gov/pubmed/35436227" }