Targeting Anxiety to Improve Sleep Disturbance: A Randomized Clinical Trial of App-Based Mindfulness Training.

OBJECTIVE: Sleep disturbance is experienced by nearly 20% of Americans and is highly comorbid with anxiety. Sleep disturbances may predict the development of anxiety disorders. Mindfulness training (MT) has shown efficacy for anxiety yet remains limited by in-person-based delivery. Digitally delivered MT may target habitual worry processes, yet its effects on sleep have not been studied. This study tested if app-based MT for anxiety could reduce worry and improve sleep and examined the underlying mechanisms. METHODS: Individuals reporting worry interfering with sleep were randomized to treatment as usual (TAU; n = 40) or TAU + app-based MT (n = 40). Treatment-related changes in worry-related sleep disturbances (WRSDs), worry, nonreactivity, and anxiety were evaluated via self-report questionnaires at 1 and 2 months after treatment initiation. Fitbit devices were used to record total sleep time and estimate sleep efficiency. At 2 months, TAU received access to app-based MT, and both groups were reassessed at 4 months. RESULTS: In a modified intent-to-treat analysis, WRSD scores decreased by 27% in TAU + MT (n = 36) and 6% in TAU (n = 35) at 2 months (median [IQR] change = 11 [4.3] versus 15 [5.0], p = .001). These WRSD reductions were mediated by decreased worry, particularly improved nonreactivity (p values < .001). At 4 months, TAU reported a significant 29% reduction after beginning app-based MT at 2 months and TAU + MT maintained its gains. No significant between-group differences in average estimated total sleep time or sleep efficiency were found after 2 months of using the app. CONCLUSIONS: Few mindfulness-related apps have been evaluated for clinical efficacy and/or mechanism. Results from this study demonstrate a mechanistic link between MT and increased emotional nonreactivity, decreased worry, and reduction in reported sleep disturbances, suggesting that app-based MT may be a viable option to help individuals who report that worry interferes with their sleep.Trial Registration: ClinicalTrials.gov identifier: NCT03684057.

Can mindfulness mechanistically target worry to improve sleep disturbances? Theory and study protocol for app-based anxiety program.

OBJECTIVE: Anxiety is associated with sleep disturbance and insomnia. Mindfulness-based interventions, such as mindfulness-based stress reduction, have shown consistent anxiety reduction. Mindfulness training has been theorized to affect reinforcement learning, affecting habitual behaviors such as smoking and overeating, but a direct mechanistic link between the use of mindfulness training for anxiety reduction and improvement in sleep has not been studied. Moreover, the mechanisms by which mindfulness might affect worry and subsequent sleep disturbances have not been elucidated. This study protocol evaluates the impact an app-based mindfulness training program for anxiety might have on decreasing worry and improvement in sleep. METHOD: A randomized controlled study will be conducted in approximately 80 adults with worry that interferes with their sleep. Participants will be randomly allocated (1:1) to two groups: treatment-as-usual (TAU) or TAU + App-Based Mindfulness Training (Unwinding Anxiety app). The primary outcomes will be the non-reactivity subscale of the Five Facet Mindfulness Questionnaire and Patient-Reported Outcomes Measurement Information System sleep quality measures (Baer et al., 2008; Yu et al., 2011). Secondary outcomes will include the Penn State Worry Questionnaire, Generalized Anxiety Disorder-7, and Multidimensional Assessment of Interoceptive Awareness Scale (Mehling et al., 2012; Meyer, Miller, Metzger, & Borkovec, 1990; Spitzer, Kroenke, Williams, & Löwe, 2006). DISCUSSION: This study will be the first to test the mechanism of app-based mindfulness training on worry and sleep disturbance. Testing the mechanistic effects of mindfulness training using the science of behavior change framework will help move the field forward both in further elucidation of potential mechanisms of mindfulness (e.g., targeting reinforcement learning) and determining whether such a platform might be a viable method for delivering high-fidelity treatment at scale and for a low cost. (PsycInfo Database Record (c) 2020 APA, all rights reserved).