Most mobile health (mHealth) apps are built around the core mission of improving their user’s health outcomes. Nutrition apps aspire to help users monitor their diet by giving them deep insights into every mouthful they eat, meditation apps aspire to help users combat anxiety and stress, and fitness apps aspire to get their users to be more active. However, as I’ve mentioned in my previous post, health goals are often time intensive to achieve and require discipline and practice on a day-to-day basis to get results. Furthermore, the more an app can get it’s users to do something (i.e. log that meal, finish that workout), the higher the likelihood of improving that health outcome (i.e. losing weight, managing stress) — if done right! But as the creator or PM of an app, how does one determine what features to introduce to bring about a behavior change and ultimately improve the user’s health outcome (sooner, more effectively)?
Prior to delving into target users and feature sets, it’s important to understand the various aspects of user behaviors, particularly as they help in driving an intervention or an outcome. A popular framework to understand user behaviors that drive a change is the COM-B model, which spans across 3 major constructs of the ‘behavior wheel’, Capability, Opportunity & Motivation.