NCT05754190

Assessing Symptom and Mood Dynamics in Pain Using the Smartphone Application SOMA

• Status: Recruiting
• Phase: —
• Study type: Observational
• Enrollment: 800 (estimated)
• Sponsor: Brown University · Academic / Other
• Sex: All
• Age: 18 Years
• Healthy volunteers: Accepted

Summary

This study relies on the use of a smartphone application (SOMA) that the investigators developed for tracking daily mood, pain, and activity status in acute pain, chronic pain, and healthy controls over four months.The primary goal of the study is to use fluctuations in daily self-reported symptoms to identify computational predictors of acute-chronic pain transition, pain recovery, and/or chronic pain maintenance or flareups. The general study will include anyone with current acute or chronic pain, while a smaller sub-study will use a subset of patients from the chronic pain group who have been diagnosed with chronic low back pain, failed back surgery syndrome, or fibromyalgia. These sub-study participants will first take part in one in-person EEG testing session while completing simple interoception and reinforcement learning tasks and then begin daily use of the SOMA app. Electrophysiologic and behavioral data from the EEG testing session will be used to determine predictors of treatment response in the sub-study.

Detailed description

The investigators aim to study the temporal dynamics of pain and links between self-reported pain, mood/emotion, and activities using the daily tracking app SOMA. The experience of pain fluctuates over time, specifically in patients who suffer from chronic pain and those who are transitioning from an acute to a chronic state. Emotions and mood directly influence the experience of pain and may contribute to its chronification. The investigators will use statistical and computational approaches to better understand the dynamics of these reported daily symptoms to identify computational predictors of transition from acute to chronic pain. Specifically, the investigators hypothesize that certain symptom clusters will co-occur in time and be linked to external life events (e.g. emotional and physical stress) and emotional states (e.g. worry). Statistical/computational analysis of pain dynamics could therefore identify indicators for change points in the transition from acute to chronic pain.

Conditions

• Chronic Pain
• Acute Pain
• Post Operative Pain
• Fibromyalgia, Primary
• Fibromyalgia, Secondary
• Fibromyalgia
• Irritable Bowel Syndrome
• Chronic Headache Disorder
• Chronic Migraine
• Chronic Pelvic Pain Syndrome
• Temporomandibular Joint Disorders
• Endometriosis-related Pain
• Arthritis
• Chronic Low-back Pain
• Failed Back Surgery Syndrome
• Post Herpetic Neuralgia
• Neuropathic Pain
• Painful Diabetic Neuropathy
• Painful Bladder Syndrome
• Trauma-related Wound
• Trauma, Multiple
• Chronic Pain Syndrome
• Chronic Shoulder Pain

Interventions

Type	Name	Description
DEVICE	SOMA pain manager smartphone application	SOMA is a smartphone application developed for acute and chronic pain patients to track daily mood and pain symptoms and overall activity.

Timeline

• Start date: 2023-06-20
• Primary completion: 2026-05-30
• Completion: 2026-05-30
• First posted: 2023-03-03
• Last updated: 2025-09-19

Locations

1 site across 1 country: United States