Clinical Research Directory

Evidence Based Mental Wellness Programming Online for Adults Across Chronic Physical Conditions

Chronic physical conditions are defined as conditions that require ongoing management and treatment over extended periods of time. Chronic physical conditions are not only leading causes of death and disability in North America but they are commonly associated with mental distress and reduced quality of life. Online mind-body wellness programming ranging from physical activity to mindfulness interventions has been shown to be effective in improving mental wellness in a variety of chronic disease populations, but there is a need to evaluate scalable ways to deliver these programs. Building upon a previously developed online wellness program for inflammatory bowel disease (IBD) and primary biliary cholangitis (PBC), the research team has developed a mind-body wellness program for adults ≥18 years of age living with different chronic conditions (e.g., cirrhosis, PBC, heart failure). The 12-week program will be delivered online, and include follow- along mindful movement, breathwork and meditation routines, and a psychology based coping skills program. In a three-armed randomized controlled trial, the study will assess the impact on the primary outcome of anxiety and depression as measured through the hospital anxiety and depression scale (HADS). At the beginning and the end of the 12-week research study, participants will complete surveys to assess secondary/exploratory outcome measures including quality of life, fatigue, frailty, demoralization, and healthcare usage. After the program, the research team will conduct interviews with participants to allow them to share their other feedback about the program. The researchers will also send surveys to the participants eight weeks after the program ends to assess longer- term impacts on primary and secondary outcomes.

AI-Driven Multimodal Imaging Integration for Diagnosis and Prognostication of Digestive System Diseases

The goal of this observational, retrospective and prospective study is to develop a noninvasive disease assessment system by leveraging artificial intelligence (AI) to comprehensively analyze multi-modal imaging features, including magnetic resonance enterography (MRE) and computed tomography enterography (CTE), for the diagnosis and prognostication of digestive diseases. To this end, the investigators retrospectively enrolled imaging, endoscopic, and clinical data from 21 centers across China to construct and iteratively optimize the AI model. The model's performance will be prospectively validated in two centers, and its accuracy in lesion localization will be verified through real-world deployment in endoscopy suites.