Abstract
BackgroundThe 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.ObjectiveThe 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.MethodsItems 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.ResultsDevelopment 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.ConclusionsOur 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.
Highlights
MethodsSmartphone ownership reached 68% of Americans in 2015, increasing from 35% in 2011 [1]
Once modifications were completed as described, the three subtools were combined into the full app quality evaluation (AQEL) with 51-scaled items for evaluating app quality plus items for app identification
After three rounds of principal component analyses (PCA), the result was a survey with 25 items grouped into 5 factors for evaluating apps, plus 5 additional items that can be used for evaluating app appropriateness for various age groups, and 4 additional items which can be used to evaluate apps for specific target audiences (Multimedia Appendix 2)
Summary
MethodsSmartphone ownership reached 68% of Americans in 2015, increasing from 35% in 2011 [1]. A nationwide survey corroborated these results, showing 58% of mobile phone users in the United States had downloaded a health app, citing tracking physical activity (52.8%), tracking diet (46.6%), weight loss (46.8%), and to learn exercises (34.0%) as the most common reasons for health app use [3]. The study further suggested that research is needed to create methods to evaluate health app quality to ensure the needs of app users are met [3]. No method grounded in empirical studies for evaluating and selecting apps for use in nutrition interventions exists. 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
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