Breathewell wear: Development and testing of a stress management app for TBI and PTSD on android wear smartwatches

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Abstract

This paper describes the development and testing of BreatheWell Wear, a stress management application (mobile app) developed for Android Wear smartwatches to assist military service members with post-traumatic stress disorder (PTSD) and traumatic brain injury (TBI) to use deep, slow diaphragmatic breathing for managing stress. The paper describes rehabilitation needs and challenges of daily living of the user population, and the limitations of existing solutions for training and using diaphragmatic breathing. Features and functioning of BreatheWell Wear are presented along with a summary of our user-centered design approach to development. Testing for clinical effectiveness was conducted with a small sample. Participants were recruited from the SHARE Military Initiative at Shepherd Center in Atlanta, Georgia, USA where they were receiving comprehensive rehabilitation for TBI and PTSD. The effectiveness of the intervention was evaluated through collection of patient reported outcomes: (1) stress ratings, entered into the app by the user before and after each breathing session; (2) Goal Attainment Scaling (GAS) to measure impact of using BreatheWell Wear after extended use; (3) changes in PTSD symptom severity gathered at study completion using the Posttraumatic Checklist-5 (PCL-5); (4) changes in anxiety, depression and psychological well-being were measured at study completion using the Beck Anxiety Inventory (BAI), the Beck Depression Inventory (BDI) and the Flourishing Scale. Clinical measures of PTSD, anxiety, depression, and psychological well-being, showed moderate or greater clinically meaningful change. Participants also reported positive experiences using BreatheWell Wear.

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Morris, J. T., & Wallace, T. (2018). Breathewell wear: Development and testing of a stress management app for TBI and PTSD on android wear smartwatches. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10897 LNCS, pp. 472–478). Springer Verlag. https://doi.org/10.1007/978-3-319-94274-2_69

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