DiFilippo Kristen Nicole, Huang Wenhao, Chapman-Novakofski Karen M
Division of Nutritional Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, United States.
Department of Education Policy, Organization and Leadership, University of Illinois at Urbana-Champaign, Champaign, IL, United States.
JMIR Mhealth Uhealth. 2017 Oct 27;5(10):e163. doi: 10.2196/mhealth.7441.
The extensive availability and increasing use of mobile apps for nutrition-based health interventions makes evaluation of the quality of these apps crucial for integration of apps into nutritional counseling.
The goal of this research was the development, validation, and reliability testing of the app quality evaluation (AQEL) tool, an instrument for evaluating apps' educational quality and technical functionality.
Items for evaluating app quality were adapted from website evaluations, with additional items added to evaluate the specific characteristics of apps, resulting in 79 initial items. Expert panels of nutrition and technology professionals and app users reviewed items for face and content validation. After recommended revisions, nutrition experts completed a second AQEL review to ensure clarity. On the basis of 150 sets of responses using the revised AQEL, principal component analysis was completed, reducing AQEL into 5 factors that underwent reliability testing, including internal consistency, split-half reliability, test-retest reliability, and interrater reliability (IRR). Two additional modifiable constructs for evaluating apps based on the age and needs of the target audience as selected by the evaluator were also tested for construct reliability. IRR testing using intraclass correlations (ICC) with all 7 constructs was conducted, with 15 dietitians evaluating one app.
Development and validation resulted in the 51-item AQEL. These were reduced to 25 items in 5 factors after principal component analysis, plus 9 modifiable items in two constructs that were not included in principal component analysis. Internal consistency and split-half reliability of the following constructs derived from principal components analysis was good (Cronbach alpha >.80, Spearman-Brown coefficient >.80): behavior change potential, support of knowledge acquisition, app function, and skill development. App purpose split half-reliability was .65. Test-retest reliability showed no significant change over time (P>.05) for all but skill development (P=.001). Construct reliability was good for items assessing age appropriateness of apps for children, teens, and a general audience. In addition, construct reliability was acceptable for assessing app appropriateness for various target audiences (Cronbach alpha >.70). For the 5 main factors, ICC (1,k) was >.80, with a P value of <.05. When 15 nutrition professionals evaluated one app, ICC (2,15) was .98, with a P value of <.001 for all 7 constructs when the modifiable items were specified for adults seeking weight loss support.
Our preliminary effort shows that AQEL is a valid, reliable instrument for evaluating nutrition apps' qualities for clinical interventions by nutrition clinicians, educators, and researchers. Further efforts in validating AQEL in various contexts are needed.
用于基于营养的健康干预的移动应用程序广泛可得且使用日益增加,因此评估这些应用程序的质量对于将其整合到营养咨询中至关重要。
本研究的目标是开发、验证和进行可靠性测试应用程序质量评估 (AQEL) 工具,这是一种用于评估应用程序教育质量和技术功能的工具。
评估应用程序质量的项目改编自网站评估,并添加了其他项目以评估应用程序的特定特征,从而产生了 79 个初始项目。营养和技术专业人员以及应用程序用户的专家小组对项目进行了表面效度和内容效度审查。在建议的修订之后,营养专家完成了第二次 AQEL 审查以确保清晰度。基于使用修订后的 AQEL 的 150 组回复,完成了主成分分析,将 AQEL 缩减为 5 个因素,对其进行了可靠性测试,包括内部一致性、分半信度、重测信度和评分者间信度 (IRR)。还对评估者根据目标受众的年龄和需求选择的另外两个用于评估应用程序的可修改结构进行了结构可靠性测试。使用组内相关系数 (ICC) 对所有 7 个结构进行 IRR 测试,由 15 名营养师评估一个应用程序。
经过开发和验证产生了包含 51 个条目的 AQEL。主成分分析后,这些条目在 5 个因素中缩减为 25 个条目,另外在主成分分析未包括的两个结构中有 9 个可修改条目。主成分分析得出的以下结构的内部一致性和分半信度良好(Cronbach 阿尔法系数>.80,斯皮尔曼 - 布朗系数>.80):行为改变潜力、知识获取支持、应用程序功能和技能发展。应用程序目的的分半信度为 0.65。除技能发展外(P = 0.001),重测信度显示所有项目随时间无显著变化(P>.05)。对于评估儿童、青少年和一般受众的应用程序年龄适宜性的项目,结构可靠性良好。此外,对于评估各种目标受众的应用程序适宜性,结构可靠性是可接受的(Cronbach 阿尔法系数>.70)。对于 5 个主要因素,ICC(1,k)>.80,P 值<.05。当 15 名营养专业人员评估一个应用程序时,对于所有 7 个结构,ICC(2,15)为 0.98,当为寻求减肥支持的成年人指定可修改项目时,P 值<.001。
我们的初步努力表明,AQEL 是一种有效、可靠的工具,可用于营养临床医生、教育工作者和研究人员评估营养应用程序用于临床干预的质量。需要在各种背景下进一步努力验证 AQEL。