To reduce the ambiguity, we only included the 47,883 apps with either Health & Fitness or Medical as their primary category in our app repository. The primary categories of some apps are neither Health & Fitness nor Medical, but others, such as Lifestyle, Education, Sports, Food & Drink, or Games. We note the category of each app is defined by the app’s owner (developer or seller) and approved by Apple’s customer service, so the app categorization was done in the server side (API) and was used directly as our app selection criteria. By removing duplicated entries, we obtained 62,621 totally unique apps in these two subcategories. In the US market, there are 74,211 apps listed in the Apple iTunes Health & Fitness and Medical subcategories as of December 4, 2014. The number of user ratings for current version The URL for the artwork in 512*512 pixelsĪverage of user ratings for current version The URL for the artwork in 100*100 pixels Table 1 lists all the 39 features along with their annotations.
In the text files, each row corresponds to an app with 39 features, including the app unique identity (ID), app name, description, user rating count, average user rating, etc. For the convenience of researchers, we transferred the files from JSON format to tab-delimited text files encoded with “utf8mb4” (flat files with array format), so that researchers can directly import these files to Excel or another program for ease of analysis. We noticed the results from our data extraction step are in the JavaScript Object Notation (JSON) format. Then using our own crawling program, we extracted detailed information of each app via the iTunes Search app program interface (API). The list of apps was crawled from the Apple iTunes Web pages, including the pages for the Health & Fitness and the Medical subcategories. Since the Apple App Store (AppStore) is the major representative in the market, we first created an app repository based on all the health related apps from the AppStore. We expect the analysis of apps in this repository can provide insights for future mHealth research developments. In this study, we aim to obtain a comprehensive view on the mHealth apps by creating an app repository. While the app stores provide a wealth of information including the prices and customer reviews for apps, there is not a centralized resource that collects information of all health-related apps for researchers to systematically evaluate the apps regarding their effectiveness and health outcome. Due to the difference in health conditions and app specialization, Tomlinson et al suggested an open mHealth architecture-based platform to facilitate scalable and sustainable health information systems. Sama et al manually installed around 400 apps to evaluate existing mHealth app tools. For example, Chomutare et al manually installed 488 diabetes related apps to review their features. However, there is still a lack of systematic research on the impact of the mHealth apps on health outcomes.Ĭurrently, most research in this field often investigates the apps individually, either by searching the apps from app stores, or by manually installing each individual app on smartphones or tablets one by one to get the detailed information of each app. Recently, there have been a number of studies in the field, including the development of a mHealth behavior change system, the creation of a food database, and a collaborative effort aiming to integrate apps platform, research data repository, and patient summarization. According to a new report (May 2014) generated by the Research2Guidance firm, there are more than 100,000 apps falling into the health, fitness, or medical categories, which doubles the market size of that in two and a half years ago. With the constant expansion of mobile health (mHealth) in the past few years, the market of mobile apps related to health is rapidly evolving, making countless new mobile technologies potentially available to the health care system.
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