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1. A Review of Empirically Supported Treatment Components in iPhone Apps for Anxiety Devon Ruhde, Dagong Ran, B.A., Matthew Schrock, Ph.D., Reza Habib, Ph.D., Sara Danitz, M.A., & Sarah J. Kertz, Ph.D. P Te Background Technology is exponentially growing, and it is taking the mental health field along with it. As of 2012, 88% percent of adults owned a smart phone (Epstein, 2013). As a result, numerous smart phone applicationshave been developed, purportedly to help decrease symptoms of worry and anxiety. However, there are no current standards for the provision of behavioral health interventions via smartphone applications. Consequently, apps may contain inaccurate information or interventions that are not evidence-based. Thus, the goal of the current study was to review the available iPhone apps targeting worry and anxiety in order to examine the representation of empirically supported components. Methods Using the search terms “anxiety” and “worry,” 566 iPhone applications were found via the iTunes store. Preliminary screening excluded: non-free apps, those clearly irrelevant (e.g., Curing Dog Anxiety), and those no longer available at the time of coding, resulting in 75 remaining apps. A coding scheme was developed based on empirically supported treatment components for generalized anxiety provided by the American Psychological Association Division 12 Society of Clinical Psychology. All 75 apps were coded based on a list of 10 criteria (see table), and each app was rated as either 0 (not consistent) or 1 (strongly consistent). In addition, we assigned each app an overall recommendation rating of 0 (not recommended), 1 (recommended with reservation), or 2 (highly recommended) based on its consistency with empirically supported interventions and overall usability. Results Descriptive statistics indicated that 18% of apps include assessment/self-monitoring components (n=14), 9% of apps include psycho-education (n = 7), 4% include progressive/applied relaxation (n = 3), 4% include exposure (n = 3), 5% include cognitive restructuring (n = 4), 3% include stimulus control (n = 2), 7% include acceptance/mindfulness (n = 5), 21% include other relaxation components (n = 16), 3% include insomnia/sleep hygiene (n = 2), and 56% include other components (n = 42). For the overall rating, 9% of apps (n = 7) are highly recommended, and 17% of apps (n = 13) are rated “recommended with reservation”. The mean score for overall rating is .36. Due to space limitations, only apps with overall ratings of 1 and 2 are presented in the table. Discussion Results suggest that the vast majority of existing apps available for iPhone users fail to incorporate empirically supported components. As there is no regulation for the delivery of behavioral health interventions by smartphones, users may be unaware of the lack of evidence supporting their use. Dissemination of such information to clinicians and clients alike will be important moving forward. In addition, as technology continues to grow, research will be needed to determine the effectiveness of smartphone apps for reducing symptoms and how such applications can best be incorporated into therapy. The current review has several limitations, including that reviewed apps were limited to iPhone and those without cost. A review including apps for other platforms and those associated with fees may yield different results. Note. 1= Recommended with reservation, 2= Highly recommended. Check marks indicate the app is consistent with corresponding rating criteria. Conference travel for the first author funded by the Center for Undergraduate Research and Creative Activities at SIU.