Purpose: Nowadays smart phone users can choose between millions of mhealth applications, but the huge selection raises an important question: how should the user choose? The information that is most readily available to the users, such as the star rating in app stores, reviews left by previous users, short descriptions and attractive screenshots, do not address many points which are important during use. How do users know that the application they are downloading is reliable, professionally relevant, and living up to its promise, for example? Several studies have already tried to answer this question and come up with models to help evaluating health applications. It is important to note that while applications focusing on more serious health areas are subject to more complex regulations, there are fewer rules for lighter topics such as weight-loss, fitness, smoking cessation, or drinking water. Thus, evaluation frameworks, usually created for serious health topic related apps, that are easy to use and understand for users, can play an important role for the less serious applications as well. The purpose of this article is to find and compare these models, to identify commonalities and any missing elements. In the second part of the article, the number one free application in the health and fitness category (considering in-app purchase revenue), MyFitnessPal is evaluated with the selected models. It will also be determined how these evaluating systems can be utilized from the users' point of view for hobby type mhealth apps, and if the suggested criteria are available for the average user at all. Design/methodology/approach: After a literature review was conducted, four evaluation models were selected. With those, one of the most popular apps in the health and fitness category was assessed. This approach enabled the evaluation of the usability of the models from end user point of view. At the end of the article a common set of criteria is presented based on the models that were introduced and the usability of the evaluation criteria in them. Findings: The paper points out the many possible angles that can be considered during an assessment of an application. Although not all the systems were created for end users, all are beneficial to them. Each model has criteria that is unique for them and that was not mentioned in other models, but there also were similarities. Although the authors were familiar with the application that is assessed with the models, before the evaluation was started, with the various questions from the models, lot of new useful information was found. At the end of the article a possible, useful blend of the assessment aspects is also presented. Research limitations/implications: The authors of this paper selected various models for investigation, but the final selection was based on personal preferences to fit the aim of the article precisely. Practical implications: Understanding the possible aspects of evaluating a mobile application is crucial for end users, especially if the app they are going to use is for health topics. Getting familiar with the models and assessing the application with a critical approach will help users to find more reliable, research based, secure applications. Social implications: The secondary aim of the article is to raise awareness of the several aspects of using a mobile application. A lot has to be considered from end user point of view but also from app provider view, to make sure that users have the right information to trust the app. Originality/value: The value of this paper is that it compares and describes the various methods for application evaluation, then it shows a possible blend for end users that would like to use applications more carefully. It points out that although there are end user focused models that help assessing an application, several other details can be checked that help deciding about an application, which are just as important for developers as for end users.(original abstract)
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