1/2 Self-directed mobile mindfulness to address ICU survivors' psychological distress: the Lift RCT

About This Grant

Cardiorespiratory conditions such as the acute respiratory distress syndrome (ARDS), congestive heart failure, COVID pneumonia, and sepsis are among the most common causes of mortality and morbidity. They are also notable for high rates of persistent psychological distress symptoms including depression, anxiety, and PTSD that worsen quality of life and outcomes of the underlying conditions. Yet there are few effective strategies able to overcome barriers of limited access to mental health care. To address this gap, we developed Lift, a completely automated and self-directed mindfulness training intervention, from the ground up with patient input. First, Lift reduced depression symptoms and improved quality of life compared to an education program control in a multicenter pilot RCT (R34 AT008819) among those recently hospitalized with serious cardiorespiratory conditions. Next, a 247-person multicenter 2x2x2 factorial optimization trial (U01 AT00974) compared 8 intervention versions differing by program introduction (app vs. therapist), dose (standard vs. high), and approach to in-the-moment symptom management (app vs. therapist). This trial demonstrated that while all versions had a strong effect on depression, anxiety, and PTSD symptoms, the high dose, app-only version was optimized for effect, adherence, and retention. Given these promising findings, a formal test of the optimized Lift mobile mindfulness intervention’s efficacy is needed. Therefore, we propose a 4-site multicenter RCT with 6-month follow up among 450 cardiorespiratory failure survivors with elevated post-discharge symptoms of psychological distress. Our specific aims will: (1) Test Lift vs. an education program control delivered by similar platforms on symptoms of depression, anxiety, PTSD, and quality of life; (2a) Determine patient-level characteristics associated with a greater treatment response among a priori-defined subgroups using a heterogeneity of treatment effects analysis; (2b) Explore novel adherence metrics and outcomes; and (3) Ensure off-the-shelf intervention readiness with an exploratory mixed-methods hybrid type 1 implementation framework analysis that integrates quantitative trial implementation data with semi-structured trial participant interviews. Innovative and unique elements include a fully automated mobile health delivery system that personalizes content in response to changes in symptom trajectories, a focus on enrolling a population representative of the US, and strong community engagement with formalized roles. This project addresses national research priorities and could advance the field with a personalizable yet population-scalable therapy that has the potential to broadly improve mental health access.