App for Autism: Identifying Trends in the App Market

Background: Apps for autism” are not only a fraction of the price of the devices that predated them (e.g. DyanaVox $10,000 plus), but are also non-stigmatizing and multi-functional (Parette & Scherer, 2004). However, llittle to no effort has been made to characterize the current state of this market of “apps for autism.” This represents a pressing issue as parents of children with autism and practitioners in the field can quickly become overwhelmed by the thousands of “apps for autism” and thousands more apps that could be useful but are not explicitly labeled for autism.

Objectives: To characterize the current state of apps for autism and explore current trends within this market by 1) creating an up-to-date database of apps for autism following Goodwin et al.’s classification scheme for interactive technologies for autism, with 2) Priori Data’s download, revenue, and app user ratings metrics for 55 countries, that will 3) be capable of automatically retrieving this information from Priori Data’s websites and compiling it within excel.

Methods: Apps are from two sources: databases listing apps for autism, and ongoing autism specific key-word search within Priori Data based on the “Domain” dimension of Goodwin et al.’s classification scheme (i.e., the technology’s focus area relevant to autism). Key words and terms included in the search were chosen that would expand the positive results returned of each of the label 6 labels comprising this dimension (e.g. social/emotional skills, language/communication, life/vocational skills, etc.). The current sample is comprised of 620(something) apps fitting the study’s inclusions/exclusion criteria. Priori Data’s app metrics for the past 13 months were then used to run the following analyses: 1) Global downloads – to 1.1) identify top 20 downloaded apps, 1.2) rank the 6 Domains areas according to their global downloads; 2) User Ratings, to 2.1) rank domains average user rating, 2.2) compare these average user rating of each domain to the all time average user rating for Priori Data’s primary app category; 3) App revenue, to identify 3.1) the top 20 individual apps with the highest revenue, 3.2) the rank the domains by mean total revenue, and 3.3) use app install revenue divided by app download revenue to determine the 50 apps with the highest unit price/the domain with the highest unit price.

Results: the data collected provides a picture of the most downloaded apps around the world, their revenues, the best rated apps and the number of user ratings. academic skills, language and communication and life and vocational skills are the most popular domains with biggest amount of downloads. The most user rated domains (user rated number> 100 ratings)  are  again  Life/Vocational Skills and Academic Skills respectively.

Conclusions: Two distinct indicators of app success emerged within total downloads and revenue as metrics of success, one characterized by highly specific apps (e.g. AAC apps) with a high initial install cost but relatively low overall downloads, and another with a less specific focus that might appeal to broader audience (e.g. Life and vocational skills and apps that could be classified as “edutainment”).