Virtual Single-Session "Empowered Relief" Class for Individuals with Marfan Syndrome and Related Conditions
Abstract
Empowered Relief (ER) is a 1-session pain relief skills intervention that is delivered in-person or online by certified clinicians to groups of patients with acute or chronic pain. Prior work in has shown ER efficacy for reducing chronic pain, pain-related distress, and other symptoms 6 months post-treatment. The purpose of this study is to conduct the first feasibility and early efficacy test of online ER (two hours total treatment time) delivered to individuals with Marfan syndrome, Vascular Ehlers-Danlos Syndrome, Loeys-Dietz Syndrome, and related conditions. Participants will be followed for 3 months via 5 follow-up surveys.
Conditions: Chronic Pain, Marfan Syndrome, Vascular Ehlers-Danlos Syndrome, Loeys-Dietz Syndrome.
Primary outcome: Number of participants registered for class; Class Attendance; Treatment appraisal.
Enrollment: 92 participants.
How strong is the evidence?
Evidence Hub reads this as a clinical trial, done in people. Its evidence level is 3 of 5 (Moderate · trial / cohort / secondary analysis). Trials without a large randomized design, cohorts and secondary analyses give moderate evidence. Reported size: 92 participants or records.
Read the paper
Related studies
- The Matrisome: In Silico Definition and In Vivo Characterization by Proteomics of Normal and Tumor Extracellular Matrices
- The Escherichia coli MG1655 in silico metabolic genotype: Its definition, characteristics, and capabilities
- In silico pharmacology for drug discovery: methods for virtual ligand screening and profiling
- In silico prediction of splice-altering single nucleotide variants in the human genome
- In silico clinical trials: how computer simulation will transform the biomedical industry
- In silico optimization of a guava antimicrobial peptide enables combinatorial exploration for peptide design
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.