Mobile technology has already been shown to help with smoking cessation. Most previous research has focused on basic approaches, such as text message based interventions.

However, a recent study by Hoeppner et al. discusses the advantage that apps have with the capability of tailoring interventions based on an individual’s own data. Tailored interventions were defined in the paper as a:

means [of] creating communications in which information about a given individual is used to determine what specific content he or she will receive, the contexts or frames surrounding the content, by whom it will be presented and even through which channels it will be delivered.

Numerous studies on health communication and neuroscience have shown that material that is tailored to individuals is more effective in producing desirable outcomes. Hoeppner et al. analyzed whether smoking cessation apps are including tailored methods in their apps and if users prefer more sophisticated apps with tailored interventions.

In this study, 225 smoking cessation apps from the Android Google Play store met the inclusion criteria and were analyzed. The number of downloads and user ratings were recorded for each app to determine popularity and user-perceived quality, respectively. Each app was then also reviewed and rated by 2 individuals who looked at the app’s use of tailoring in general, as well as the app’s use of tailoring to address the 5A’s recommended by the U.S. Clinical Practice Guideline for Testing Tobacco Use and Dependence. The 5A’s are listed below:

  • Assess smoking status
  • Advise to quit smoking
  • Assess the readiness to quit smoking
  • Assist in a quit attempt
  • Arrange follow-up

The results of the study showed that most of the apps did not use tailoring effectively. When looking at general tailoring techniques, the study categorized these interventions as “(1) by being interactive, where the input provided by the user would result in specific feedback; (2) by being proactive, where the app reaches out to users after initial use, and (3) by being responsive to the quit attempt, where the functionality of the app changes after the quit day.” Only 45% of apps were interactive and provided feedback to data inputted by the user and most responses were very basic. Only 10% of apps were proactive and only 11% of apps changed their functionality after the quit date. Most of these interventions were also very basic such as counting the days of abstinence after quitting.

When looking at the 5A’s, the apps included more tailored interventions. 96% of apps “assisted,” 51% “asked” about smoking status and 47% gave “advice” to quit smoking. Only 11% “arranged” follow-up and only 8% “assessed” the user’s interest in quitting.

The results of the study also showed that an app was more likely to be downloaded (i.e. more popular) when it included tailored interventions, both general and addressing the 5As, than if it did not. Apps were also rated higher by users if they included general tailored interventions and tailored interventions addressing the 5As.

The study shows us that, of the smoking cessation apps available in the Android market, many do not take advantage of tailoring interventions based on the individual’s data. However, apps that do tailor interventions are seen as higher quality and rated higher by users, and are downloaded more often. Overall, apps with tailored interventions are more preferable by users, but their availability is limited.

Hoeppner BB, Hoeppner SS, Seaboyer L, et al. How Smart are Smartphone Apps for Smoking Cessation? A Content Analysis. Nicotine Tob Res. 2015;