Medical Mental Models: An Assessment of Condition and Treatment Knowledge Structures with Implications for App Design

Abstract

Medical mobile apps whose layout, navigation, and interactions match the mental model of the user (i.e. the user's expectations) are more apt to produce positive usability outcomes than those that do not. But in order to design an app that matches a user mental model, designers must be armed with an empirically measured mental model that is represented in a meaningful way. This study sought to examine the efficacy of similarity ratings as a measurement method and Pathfinder networks as a representation method for yielding mental models beneficial to medical app design. Mental models were measured for three medical conditions (and their corresponding treatments) that are popular topics in modern mobile apps and special attention was given to differences between mental models of high and low knowledge participants. Based on the model Pathfinder networks, a series of observations and suggestions are made about the design of healthcare apps. Discussion emphasizes that the above methods are effective for turning knowledge internal to a user into a tangible informant of design. We conclude by advocating the use of Pathfinder for measuring mental models of content in healthcare apps in order to inform user-centered design.