IntroductionCurrent evidence has demonstrated the usefulness of mobile technology in supporting smoking cessation. 1 The most recent Cochrane review, based on 20 studies and a total sample size of 9100 smokers, indicated significant benefit of mobile phone-based smoking cessation interventions on long-term outcomes, with a relative risk estimate of 1.71, compared to no intervention or less intensive intervention via mobile.1 These effects were achieved with fully-automated, highly cost-effective programs of unprecedented reach. They were also achieved with a relatively low level of technological sophistication, as up to this point, mobile technology approaches to smoking cessation have largely used text messaging. AbstractIntroduction: Smartphone technology is ideally suited to provide tailored smoking cessation support, yet it is unclear to what extent currently existing smartphone "apps" use tailoring, and if tailoring is related to app popularity and user-rated quality. Methods: We conducted a content analysis of Android smoking cessation apps (n = 225), downloaded between October 1, 2013 to May 31, 2014. We recorded app popularity (>10 000 downloads) and user-rated quality (number of stars) from Google Play, and coded the existence of tailoring features in the apps within the context of using the 5As ("ask, " "advise, " "assess, " "assist, " and "arrange follow-up"), as recommended by national clinical practice guidelines. Results: Apps largely provided simplistic tools (eg, calculators, trackers), and used tailoring sparingly: on average, apps addressed 2.1 ± 0.9 of the 5As and used tailoring for 0.7 ± 0.9 of the 5As. Tailoring was positively related to app popularity and user-rated quality: apps that used two-way interactions (odds ratio ), proactive alerts .38]), responsiveness to quit status ), addressed more of the 5As (OR = 1.53 [1.10-2.14]), used tailoring for more As (OR = 1.67 [1.21-2.30]), and/or used more ways of tailoring 5As content (OR = 1.35 [1.13-1.62]) were more likely to be frequently downloaded. Higher star ratings were associated with a higher number of 5As addressed (b = 0.16 [0.03-0.30]), a higher number of 5As with any level of tailoring (b = 0.14 [0.01-0.27]), and a higher number of ways of tailoring 5As content (b = 0.08 [0.002-0.15]). Conclusions: Publically available smartphone smoking cessation apps are not particularly "smart": they commonly fall short of providing tailored feedback, despite users' preference for these features.

No abstract

If replicated, findings may suggest the utility of targeting difficulties regulating positive emotions in treatments aimed at reducing alcohol and drug misuse among college students.