Browsing by Author "Vilardaga, Roger"

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    An examination of neurocognition and theory of mind as predictors of engagement with a tailored digital therapeutic in persons with serious mental illness.
    (Schizophrenia research. Cognition, 2022-06) Halverson, Tate F; Browne, Julia; Thomas, Samantha M; Palenski, Paige; Vilardaga, Roger
    There is an increasing interest in the development and implementation of digital therapeutics (apps) in individuals with serious mental illness (SMI). However, there is limited understanding of the role of neurocognition and social cognition on engagement with apps. The present study is a secondary analysis of a pilot randomized controlled trial (N = 62) comparing a tailored digital intervention to treat tobacco use disorder in individuals with SMI to a standard of care digital intervention for the general population. The purpose of this study was to examine the impact of neurocognition, social cognition, and clinical characteristics on indices of app engagement in users of the tailored app compared to users of the standard of care app. Correlational analyses demonstrated that individuals with low levels of neurocognition and social cognition engaged more often and for longer duration with the tailored app compared to the standard of care app. In a series of multilevel zero-inflated negative binomial models, assignment to the tailored app remained the most robust predictor of app interactions (Risk Ratio [RR] = 1.72; p < .01), duration of app use (RR = 6.47; p < .01), and average length of interaction (RR = 2.70; p < .01), after adjusting for key demographic and clinical characteristics, and two measures of cognition. This is one of the first studies to demonstrate that digital therapeutics can be designed to mitigate the impact of neurocognition and social cognition on device engagement in SMI populations. Recommendations are made to advance the use of new analytic models to uncover patterns of engagement with digital therapeutics.
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    Formative, multimethod case studies of learn to quit, an acceptance and commitment therapy smoking cessation app designed for people with serious mental illness.
    (Translational behavioral medicine, 2018-11-16) Vilardaga, Roger; Rizo, Javier; Ries, Richard K; Kientz, Julie A; Ziedonis, Douglas M; Hernandez, Kayla; McClernon, Francis J
    Despite public health efforts, individuals with serious mental illness (SMI) still have very high rates of tobacco smoking. Innovative approaches to reach this population are needed. These series of case studies aimed to descriptively evaluate the usability, user experience (UX), and user engagement (UE) of Learn to Quit (LTQ), an acceptance and commitment therapy smoking cessation app designed for people with SMI, and to compare it with an app designed for the general population, NCI (National Cancer Institute) QuitGuide (QG). Both apps were combined with nicotine replacement therapy and technical coaching. Inspired by the ORBIT model, we implemented two case studies with crossover AB interventions, two B-phase training designs, and three bi-phasic AB single-case designs with Start-Point and Order randomization (A = QG, B = LTQ). Study outcomes were measured using the System Usability Scale, UX interviews, and background analytics. LTQ's usability levels were above the standard cutoff and on average higher than QG. UX outcomes suggested the relative benefits of LTQ's visual design, gamification and simple design structure. LTQ's overall UE was high; the app was opened for an average of 14 min per day (vs. QG: 7 min). However, users showed low levels of UE with each of the app's tracking feature. Measures of psychiatric functioning suggested the safety of LTQ in people with SMI. LTQ appears to be a usable and engaging smoking cessation app in people with SMI. An optimized version of LTQ should be tested in a Phase II study.
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    Mobile Applications for the Treatment of Tobacco Use and Dependence
    (Current Addiction Reports, 2019-06) Vilardaga, Roger; Casellas-Pujol, Elisabet; McClernon, Joseph F; Garrison, Kathleen A