Behavior Change Techniques in Popular Mobile Apps for Smoking Cessation in France: Content Analysis

Abstract

Background The mobile app market differs from country to country, and to date, no previous review of the content quality of smoking cessation apps has been conducted in France. Objective This study aimed to examine the general quality of the most popular smoking cessation apps in France and also determine the degree to which apps adhere to established behavioral and cognitive techniques (BCTs) proven effective in clinical practice. Methods A systematic research of smoking cessation apps was conducted in both the Google Play Store and Apple Store in the French market. The general quality of popular apps was rated with the Mobile App Rating Scale (MARS), and the therapeutic quality was assessed with the ratio of adherence of the behavior change technique taxonomy for smoking cessation treatment. Results A total of 14 mobile apps met all the inclusion criteria of the content analysis. The interrater reliability varied from “substantial” (0.79) to “almost perfect” (0.9) for the two measures. The mean MARS score was 3.5 out of 5 (median 3.6, IQR 0.6 [3.2-3.8]). The findings suggest that popular apps focus primarily on the functionality dimension of the MARS scale (4.2/5). The mean number of BCTs was 22, with a large difference between apps (minimum 4, maximum 38). At least half of the apps addressed motivation (8.8/14, 63%) and advised on using behavioral skills in order to quit smoking or stay a nonsmoker (8.7/14, 62%). However, only a handful of apps gathered important information (5.9/14, 42%) in order to deliver proper advice regarding the use of approved medication or the implementation of behavioral techniques (4.3/14, 31%). The mean MARS score was positively correlated with the price (r=0.70, P=.007) and the number of BCTs used (r=0.67, P=.01). User rating was not correlated with any quality scale (P=.67). Conclusions The content quality of popular smoking cessation apps in France varied by app type and price. Most popular apps propose in general good quality content but lack implementation of evidence-based BCTs associated with effectiveness on smoking cessation treatment. Further research is needed to evaluate the improvement in the content quality of smoking cessation apps in France.

The Quality of Indian Obesity-Related mHealth Apps: PRECEDE-PROCEED Model–Based Content Analysis

“…Regarding the overall quality of the 13 apps assessed using the MARS, the mean scores ranged from 1.8 to 3.7. This study supports the findings of previous studies that suggest when mHealth apps focus heavily on the functionality domain of the MARS, the performance, ease of use, navigation, and gestural design are compromised [ 20 ]. The subjective quality domain of the MARS depends on all 4 domains, engagement, functionality, aesthetics, and information.…”

“…Each sample app was coded for basic descriptive information, such as the app name, user rating, and the number of downloads. The features and quality of the sample apps were assessed using the Mobile Application Rating Scale (MARS) [ 20 - 22 ] and the potential of the app contents to promote health behavior change was assessed using the PPM [ 18 ]. MARS is a measure for classifying and assessing the quality of mHealth apps.…”

“…The coding sheet is presented in Multimedia Appendix 1 . The coders were instructed on each measure and its definition to ensure clear differentiation between the items used to assess the sample apps [ 20 ]. Both coders assessed the content of the sample apps independently.…”

Theory-Based Social and Non-Social Engagement Features in Smoking Cessation Mobile Apps: A Content Analysis

“…However, the low engagement has always been the primary concern for the effectiveness of mobile phone-based smoking cessation interventions [30]. It was found in the current study that the mean engagement score (M = 2.67) of mobile apps in the U.S. was lower than the mean score documented in the sample of French apps (M = 3.5), which was based on 14 apps though [48]. By conducting a comprehensive content analysis of free and paid smoking cessation apps, this study answered two primary research questions: (a) what social (and non-social) engagement features are present in smoking cessation apps and (b) how effective they are in potentially engaging users.…”

“…The researcher calculated descriptive statistics for focal variables, including frequency for dichotomously coded social and non-social engagement features, and means and standard deviations for users' engagement as an interval variable. Hierarchical multiple regressions were implemented to predict MARS with each social or non-social engagement features, adjusting for the price of mobile apps, which was found correlated with MARS score [48]. The social and non-social engagement features were analyzed individually in the regression models as the independent variable, with the MARS engagement score as the dependent variable.…”