According to a team of Penn State researchers, most mHealth apps don’t use behavior change techniques in their marketing materials. The team has also found that two types of physical-activity apps are available on the market, those that focus on educating users on how to perform different exercises and those that focus on supporting users’ motivation for physical activity.
The researchers looked at top-ranked health and fitness apps as of August 28, 2013, on the two major online marketplaces – Apple iTunes and Google Play. Next, they located descriptions of each app online, reviewed the descriptions and had them coded by two trained coders using the Coventry, Aberdeen and London-Refined taxonomy, which are common behavior-change techniques used in interventions developed to give people a structure for comparing what is in one intervention versus another.
Most of the descriptions of the apps researchers have examined incorporated fewer than four behavior change techniques. The most common techniques involved providing instruction on how to perform exercises, feedback on performance, goal-setting assistance and planning social support or change. They reported their results today (May 6) in the American Journal of Preventive Medicine.
“Our results suggest that there are far fewer behavior-change techniques described in apps than in interventions, which are delivered in-person to help people increase their physical activity,” said David Conroy, professor of kinesiology. “However, this does not necessarily mean that apps are less effective, because it is possible that a number of techniques included in the in-person intervention packages are inert. We suggest that users should consider their needs carefully when selecting a physical-activity app.”
The team is completing a detailed inspection of apps to see if developers incorporated techniques that were not described in their marketing materials. The researchers also are collaborating to evaluate ways of making mobile interventions more effective by integrating advances from engineering and psychology to optimize these interventions.