Targeted real-time assessment of chronic pain (TRAC-Pain) in youth: protocol for digital biosignature development through a prospective observational cohort study (Preprint)

<sec> <title>BACKGROUND</title> Approximately one in five children and adolescents live with chronic pain, with musculoskeletal (MSK) pain being one of the most prevalent sub-types. Unfortunately, less than half of youth with chronic pain experience improvements with existing evidence-based treatments. Self-report measures—the current gold-standard for monitoring the pain experience— are limited in their use as a single point-of-care assessment and vulnerability to recall bias. The ubiquitous adoption of wearable technology presents a promising solution for improved monitoring of the pain experience via real-time tracking through a multi-systemic lens. </sec> <sec> <title>OBJECTIVE</title> The purpose of this study is 1) to develop a digital biosignature of the pain experience in youth with chronic MSK pain, and 2) assess feasibility, acceptability, and appropriateness of captured data for future applications. </sec> <sec> <title>METHODS</title> All aspects of this study were designed in partnership with people with lived experience and patient advocacy partners. This is a longitudinal observational cohort study, with all study activities taking place remotely over a 12-week period. Up to 500 youth (14-24 years old) with chronic MSK pain will be enrolled through a multipronged recruitment strategy to ensure a representative sample. Participants will wear an Apple Watch throughout the study for continuous monitoring of physiological, sleep, and physical activity metrics. In addition, participants will complete brief ‘Daily Check-In’ surveys that include gold-standard measures of the pain experience (e.g., pain interference, mood, fatigue) and the option to report a ‘pain flare’ (i.e., temporary but noticeable worsening of usual symptoms). Participants will also complete a modified online Trier Social Stress Test and 30 second sit-to-stand task to capture individual responses to standardized challenges. Traditional machine learning and deep representation learning methods will be used to develop a digital biosignature of the pain experience. Accuracy of the biosignature will be assessed through measures of model performance as compared to gold-standard self-reports. </sec> <sec> <title>RESULTS</title> This study was funded in September 2024, with data collection beginning March 2025. As of August 2025, 132 participants are enrolled, with data collection and analysis ongoing. </sec> <sec> <title>CONCLUSIONS</title> This is the first study to leverage wearable health technology for real-time monitoring of the pain experience in youth with chronic MSK pain. Resulting digital endpoints are expected to heighten the rigor of clinical trials and provide opportunities for individually-tailored interventions. The second phase of this study will investigate the implementation of ‘wellness-alerts’ triggered by abnormal smartwatch readings. Alerts would empower users toward preemptive self-management strategies, thereby enhancing self-efficacy in those living with chronic MSK pain. </sec> <sec> <title>CLINICALTRIAL</title> ClinicalTrials.gov NCT06867757 https://clinicaltrials.gov/study/NCT06867757 </sec>