Smartphone-Based Muscle Relaxation for Migraine in the Emergency Department: A Randomized Clinical Trial
Abstract
Importance: The emergency department (ED) is a critical point of contact within the health care system and an opportunity to initiate nonpharmacologic migraine treatment.
Objective: To examine whether progressive muscle relaxation (PMR) smartphone-based migraine self-management improved patient-reported outcomes for migraine compared with enhanced usual care.
Design, setting, and participants: A randomized clinical trial of the smartphone application RELAXaHEAD with and without PMR. Patients aged 18 to 65 years visiting New York University Langone Health EDs for headache who met migraine criteria and self reported 4 or more migraine days per month were recruited from June 2019 to October 2021 with follow-up at 3 months. Data were analyzed from June 2022 to June 2025.
Intervention: Participants in the intervention group were asked to listen to the app-based PMR for 60 days. Participants in the control group were asked to use the app as a symptom diary.
Main outcomes and measures: Primary outcome was change in migraine-related disability (MIDAS). Secondary outcomes were change in migraine-specific quality of life (MSQv2) and monthly headache days (MHDs). Adherence (number of days of diary use, PMR use and total minutes of PMR use over 90-day period) was measured using back-end analytics.
Results: Of the 94 patients (median [IQR] age, 33 [26-45] years; 57 [82.6%] female) randomized (48 control patients and 46 PMR patients), 69 of 94 (73%) had 1 or more follow-up MIDAS scores…
How strong is the evidence?
Evidence Hub reads this as a randomized trial, done in people. Its evidence level is 2 of 5 (High · randomized trial). Randomized trials of a reasonable size are the strongest single-study design. Reported size: 94 participants or records.
Read the paper
Related studies
- Calcium Ions in the Physiology and Pathology of the Central Nervous System
- AI-powered in silico twins: redefining precision medicine through simulation, personalization, and predictive healthcare
- In silico functional, structural and pathogenicity analysis of missense single nucleotide polymorphisms in human MCM6 gene
- In Silico drug repurposing pipeline using deep learning and structure based approaches in epilepsy
- Targeting serotonin receptors with phytochemicals – an in-silico study
- In silico exploration of anti-prostate cancer compounds from differential expressed genes
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.