This clinical trial focuses on testing the efficacy of different digital interventions to promote re-engagement in cancer-related long-term follow-up care for adolescent and young adult (AYA) survivors of childhood cancer.
This study will identify unique signatures that people have which can cause pain by evaluating biological, psychological, and social markers using artificial intelligence. These markers can be used to accurately predict the response of diverse individuals with chronic low back pain (cLBP) to Mindfulness-Based Stress Reduction. This will help enhance clinician decision-making and the targeted treatment of chronic pain. The overall objective is to use a unique machine learning (ML) approach to determine the biomarker signature of persons undergoing mindfulness based stress reduction (MBSR) treatment for their chronic low back pain (cLBP). This signature will facilitate clinical prediction and monitoring of patient response to MBSR treatment. The design of the study is a single-arm clinical trial of the evidence-based MBSR program for patients with cLBP.
Integrative Mindfulness-Based Predictive Approach for Chronic Low Back Pain Treatment
Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.
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Sponsor: Boston Medical Center
These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.