Targeted Realtime Assessment of Chronic Pain in Youth

Recruiting

• Conditions: Chronic Pain; Musculoskeletal Pain

• Registration Number: NCT06867757
• Lead Sponsor: Stanford University

Brief Summary

The purpose of this study is to evaluate the feasibility and acceptability of using wearable digital health technology for continuous monitoring of physiological, sleep, and physical activity data in adolescents with chronic musculoskeletal (MSK) pain. This research aims to develop objective digital endpoints of the pain experience to improve diagnosis, prevention, and treatment outcomes.

Detailed Description

Up to 5% of adolescents (\~3.5 million in the US alone) suffer from high-impact chronic musculoskeletal (MSK) pain, affecting quality of life, school attendance, mood, and family function, and posing a significant economic burden of $19.5 billion annually in the US. A substantial proportion of these youths continue to suffer from pain into adulthood. Chronic MSK pain is characterized by a complex biological response, including physiological disturbances in cognition, sleep, and energy levels (fatigue), and is associated with impairments in both physical and emotional function. The chronic pain experience fluctuates over time with intra- and inter-daily variations and the occurrence of pain flares, contributing to unpredictability, uncertainty, and greater impairment.

Current gold standard self-report assessments are burdensome and fail to provide comprehensive, reliable measures of the pain experience due to inherent recall bias. A potential solution lies in the widespread adoption of digital health technologies, particularly wearable devices, which offer continuous monitoring of physiological, sleep, and physical activity data. This approach can yield unprecedented insights into individual health, informing diagnosis, prevention, monitoring, and treatment.

Through artificial intelligence (AI) and machine learning (ML), several groundbreaking digital biosignatures of human health have been developed by the research team, including those for glucose variability, preterm birth, panic attacks, fall risk, and surgical recovery. This real-time, personalized approach not only empowers patients but also enables healthcare providers to make more informed decisions, optimizing treatment strategies and improving outcomes. Despite these advancements, less than half of adolescents with chronic MSK pain who undergo pain treatment experience meaningful improvement.

The scientific rationale of this proposal is to overcome the limitations of self-report by integrating precise physiological, sleep, and physical activity measures from wearable devices with AI/ML to develop and validate a monitoring digital biosignature of the individual pain experience in youth with MSK pain. This biosignature will monitor the pain experience, track its progression, assess responses to interventions, and evaluate impacts on quality of life.

The research team is well positioned to execute these aims with: (1) a diverse, highly skilled team with expertise in digital technology, AI/ML, digital endpoint development, and clinical trials, alongside clinical expertise in chronic pain in youth and lived experience from patients, caregivers, and pain advocacy groups; (2) a centralized and standardized digital data collection, processing, and storage system via the scalable and secure My Personal Health Dashboard (MyPHD; Stanford); and (3) cutting-edge preliminary data supporting the capability to develop this digital health biosignature.

UG3/Discovery Phase: We will enroll up to 500 youth (ages 14-24) with chronic MSK pain, capturing continuous physiological (heart, respiratory), sleep, and physical (activity level, mobility, gait) activity metrics via wearables. Repeated intra-daily self-reports of the pain experience (pain interference, pain intensity, fatigue, mood, stress, pain flares) will be collected over 12 weeks. For a subset, data from physical and social stress tasks will also be gathered. The aim is to assess feasibility and relevance, develop a digital biosignature of the pain experience, and prepare for the UH3 phase through outreach and collaboration. Consultations with individuals with lived experience, those experiencing health disparities, and the FDA will ensure the relevance and acceptability of the biosignature and promote recruitment of underrepresented youth, coupled with scalability for clinical use.

UH3/Validation Phase: We will enroll up to 400 diverse youth with chronic MSK pain, capturing wearable and self-reported pain experience metrics over 12 weeks: a 4-week baseline followed by 8 weeks of abnormal reading-triggered alerts. The aim of this phase is to clinically validate the digital biosignature of the pain experience, and evaluate the accuracy and potential of an enhanced wellness alert system.

Significance and Clinical Impact: The successful development and validation of digital endpoints for the pain experience are crucial for advancing pain management. These endpoints promise to improve therapeutic development by providing robust, objective measures of treatment response. The outcomes of this study will be foundational for seeking regulatory approval for the commercialization of the associated software or for disseminating open-source analysis packages for future clinical trials.

Study Timeline

• Study Start: 2025-02-28
• Status Verified: 2025-03
• Study First Submitted: 2025-03-04
• Study First Submitted QC: 2025-03-04
• Last Update Submitted: 2025-03-04
• Study First Posted: 2025-03-25
• Last Update Posted: 2025-03-25
• Primary Completion: 2026-11
• Study Completion: 2026-11

Recruitment & Eligibility

• Status: RECRUITING
• Sex: All
• Target Recruitment: 500

Inclusion Criteria

• The patient has a diagnosis of Chronic widespread pain or Chronic primary musculoskeletal pain (other than orofacial) derived from ICD-11 (MG30.0; chronic primary pain is pain in 1 or more anatomic regions that persists for > 3 months, is associated with significant distress or functional disability and cannot be better explained by another chronic pain condition (e.g., cancer)).
• Diagnosis of a secondary MSK pain condition (e.g., arthritis, lupus, sickle cell)

Exclusion Criteria

• Significant cognitive impairment (e.g., unable to communicate)
• Hospitalization in the past 30 days for something other than their pain condition
• Currently undergoing treatment for cancer
• Currently pregnant or think you might become pregnant in the next 3 months

Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Primary Outcome Measures

Name	Time	Method
Pain, Enjoyment of Life, and General Activity (PEG) Scale	Daily from baseline to discharge, for a duration of 12 weeks	The PEG scale, a subset of the Brief Pain Inventory (BPI), evaluates pain intensity and its impact on enjoyment of life and general activity using a ranked scale (score 0 = "no interference" to 10 = "highest level of interference") with a higher score reflecting greater disruption in daily functioning.

Secondary Outcome Measures

Name	Time	Method
Numeric Rating Scale (NRS) of Present Pain	Daily from baseline to discharge, for a duration of 12 weeks	The Numeric Rating Scale (NRS) for Present pain assesses the intensity of current pain using a ranked scale (0 = "no pain" to 10 = "the worst possible pain") with a higher score reflecting greater pain severity.
Numeric Rating Scale (NRS) Fatigue	Daily from baseline to discharge, for a duration of 12 weeks	The Numeric Rating Scale (NRS) for Fatigue measures the level of fatigue experienced using a ranked scale (0 = "no fatigue" to 10 = "the most extreme fatigue") with a higher score indicating greater exhaustion.
Numeric Rating Scale (NRS) Stress Level	Daily from baseline to discharge, for a duration of 12 weeks	The Numeric Rating Scale (NRS) for Stress Level evaluates the severity of stress using a ranked scale (0 = "no stress" to 10 = "the highest level of stress") with a higher score reflecting increased stress intensity.
Numeric Rating Scale (NRS) Activity Level	Daily from baseline to discharge, for a duration of 12 weeks	The Numeric Rating Scale (NRS) for activity level assesses a person's level of physical activity using a ranked scale (0 = "no activity" to 10 = "the highest possible level of activity") with a higher score reflecting greater engagement in physical activity.
Numeric Rating Scale (NRS) Sleep Quality	Daily from baseline to discharge, for a duration of 12 weeks	The Numeric Rating Scale (NRS) for Sleep Quality evaluates the quality of sleep using a ranked scale (0 = "the worst possible sleep quality" to 10 = "the best possible sleep quality") with a higher score reflecting better sleep quality.

Trial Locations

Locations (1)

Stanford University; 🇺🇸 Palo Alto, California, United States