Engaging Teenagers in Asynchronous Online Groups to Design for Stress Management.

Teenagers have unique needs for mental wellbeing that can be supported by interactive technologies. Teens also have valuable input in the design of technology, so designers and researchers must seek new methods for involving them in the design process. We enrolled 23 unacquainted teenagers in an Asynchronous Remote Communities (ARC) study consisting of two private online groups. Teens participated in 10 weekly design activities on stress management across three months. We found that teens sought support from technology tailored to their perception of control in stressful contexts, developing sense of self, and varying social needs, including asking for no intervention from others. Teens appreciated that the ARC design experience allowed for flexibility in participation and supported selective disclosure. However, there were limited interactions between teenagers online. Reflecting on our study, we provide design implications for tools to support teenager mental health and discuss how the ARC method can be adapted for designing with teenagers.

Single-arm trial of the second version of an acceptance & commitment therapy smartphone application for smoking cessation.

BACKGROUND: The first randomized trial of a smartphone application (app) for adult smoking cessation (SmartQuit 1.0) revealed key features that predict cessation. These findings guided the revision of this Acceptance & Commitment Therapy (ACT)-based application (SmartQuit 2.0), which was primarily tested to examine participant receptivity, short-term cessation and reduction, and the relationship between program completion, smoking cessation and reduction. Secondarily, outcomes were descriptively compared with the SmartQuit1.0 trial. METHOD: Adult participants (78% female, 25% with high school or less education, 30% unemployed) were recruited into the single-arm pilot trial (N=99) of SmartQuit 2.0 with a two-month follow-up (85% retention). RESULTS: Regarding receptivity, 84% of participants were satisfied with SmartQuit 2.0 (vs. 59% for SmartQuit1.0), 73% would recommend it to a friend (vs. 48% for SmartQuit1.0), 81% found the ACT exercises useful for quitting (vs. 44% for SmartQuit1.0). At the 2-month follow-up, the quit rates were 21% for 7-day point prevalence (vs. 23% for SmartQuit1.0), 11% for 30-day point prevalence (vs. 13% for SmartQuit1.0), and 75% of participants reduced their smoking frequency (vs. 57% for SmartQuit1.0). Among program completers (24% of total sample), the quit rates were 33% for 7-day point prevalence, 28% for 30-day point prevalence, and 88% of participants reduced their smoking frequency. CONCLUSIONS: The revised app had high user receptivity, modest quit rates, and high smoking reduction rates. Program completion may be key to boosting the app's effectiveness.

Get with the program: Adherence to a smartphone app for smoking cessation.

INTRODUCTION: Although engagement is generally predictive of positive outcomes in technology-based behavioral change interventions, engagement measures remain largely atheoretical and lack treatment-specificity. This study examines the extent to which adherence measures based on the underlying behavioral change theory of an Acceptance and Commitment Therapy (ACT) app for smoking cessation predict smoking outcomes, and user characteristics associated with adherence. METHODS: Study sample was adult daily smokers in a single arm pilot study (n=84). Using the app's log file data, we examined measures of adherence to four key components of the ACT behavior change model as predictors of smoking cessation and reduction. We also examined baseline user characteristics associated with adherence measures that predict smoking cessation. RESULTS: Fully adherent users (24%) were over four times more likely to quit smoking (OR=4.45; 95% CI=1.13, 17.45; p=0.032). Both an increase in tracking the number of urges passed (OR=1.02; 95% CI=1.00, 1.03; p=0.043) and ACT modules completed (OR=1.27; 95% CI=1.01, 1.60; p=0.042) predicted cessation. Lower baseline acceptance of cravings was associated with over four times higher odds of full adherence (OR=4.59; 95% CI=1.35, 15.54; p=0.014). CONCLUSIONS: Full adherence and use of specific ACT theory-based components of the app predicted quitting. Consistent with ACT theory, users with low acceptance were most likely to adhere to the app. Further research is needed on ways to promote app engagement.

Predictors of Utilization of a Novel Smoking Cessation Smartphone App.

BACKGROUND: Understanding the characteristics of high and low utilizers of smartphone applications (apps) for smoking cessation would inform development of more engaging and effective apps, yet no studies to date have addressed this critical question. Informed by prior research on predictors of cessation Web site utilization, this study examines the degree to which baseline demographic factors (gender, age, and education), smoking-related factors (smoking level and friends' smoking), and psychological factors (depression and anxiety) are predictive of utilization of a smartphone app for smoking cessation called SmartQuit. MATERIALS AND METHODS: Data came from 98 participants randomized to SmartQuit as part of a pilot trial from March to May 2013. We used negative binomial count regressions to examine the relationship between user characteristics and utilization of the app over an 8-week treatment period. RESULTS: Lower education (risk ratio [RR]=0.492; p=0.021), heavier smoking (RR=0.613; p=0.033), and depression (RR=0.958; p=0.017) prospectively predicted lower app utilization. Women (RR=0.320; p=0.022), those with lower education (RR=0.491; p=0.013), and heavier smokers (RR=0.418; p=0.039) had lower utilization of app features known to predict smoking cessation. CONCLUSIONS: Many of the predictors of utilization of smoking cessation apps are the same as those of cessation Web sites. App-delivered smoking cessation treatment effectiveness could be enhanced by focusing on increasing engagement of women, those with lower education, heavy smokers, and those with current depressive symptoms.