1/2 self-directed mobile mindfulness to address ICU survivors' psychological distress: the lift RCT - cardiorespiratory conditions such as the acute respiratory distress syndrome (ards), congestive…

The National Center for Complementary and Integrative Health (NCCIH), within the Department of Health and Human Services National Institutes of Health, awarded Duke University a $1,980,122 cooperative agreement on April 23, 2026, to conduct a multicenter randomized controlled trial (RCT) testing the efficacy of LIFT, a self-directed mobile mindfulness intervention designed to reduce psychological distress in cardiorespiratory failure survivors.

The award funds a 4-site multicenter RCT with 6-month follow-up among 450 patients recently discharged from intensive care units following serious cardiorespiratory conditions including acute respiratory distress syndrome, congestive heart failure, COVID pneumonia, and sepsis. Prior pilot and optimization trials demonstrated that LIFT, an automated app-based mindfulness training program, reduced depression, anxiety, and PTSD symptoms and improved quality of life compared to education controls. The current trial will test the optimized high-dose, app-only intervention against a similar platform-delivered education control on outcomes of depression, anxiety, PTSD symptoms, and quality of life, and will identify patient-level characteristics associated with greater treatment response and mechanisms of intervention effect.

The award is supported under the Research and Training in Complementary and Integrative Health program (CFDA 93.213), which funds scientific research on complementary and integrative health approaches through competitive peer review. Place of performance is Durham, North Carolina. The period of performance extends through March 31, 2027.

1/2 self-directed mobile mindfulness to address ICU survivors' psychological distress: the lift RCT - 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.