Transcending COVID-19 Barriers to Pain Care in Rural America: Pragmatic Comparative Effectiveness Trial of Evidence-based, On-demand, Digital Behavioral Treatments for Chronic Pain

We performed a two-arm, multi-center, virtual randomized controlled trial (vRCT) in a geographically diverse group of patients with mixed-etiology chronic pain. Using a random number generator, patients were allocated in a 1:1 ratio between two self-administered, remotely deployed CBT delivery platforms, stratified by site: (1) a 2D mHealth app called PainTRAINER; and (2) 3D virtual reality (VR) app called EaseVRx+. The primary analysis compared changes in pain intensity over two months upon completion of the standardized 8-week digital CBT protocols. Secondary outcomes include pain catastrophizing, anxiety, pain interference, self-efficacy, and opioid use. Patient blinding is not possible in VR versus non-VR studies; however, researchers exhibited equipoise when describing the competing interventions, Investigators and data analysts were blinded to patient allocation; coordinators administering the intervention were unblinded in order onboard participants to their assigned program and troubleshoot any difficulties throughout the study.

The population eligible for the study include individuals with any of more than 130 ICD codes for chronic pain conditions, including somatic, musculoskeletal, neuropathic, and visceral pain who also recorded an average pain intensity of 4 or greater on a standard 0-10 numeric rating scale (NRS) over the past week. Patients were recruited from three major sites: (1) Cedars-Sinai Health System (CSHS); (2) Ochsner Health; (3) UAB. All sites used search tools to identify participants within their respective electronic health record (EHR) with at least one of the inclusionary chronic pain ICD codes and who did not meet several coded ineligibility criteria, included but not limited to ongoing end-of-life care and an age less than 13 years old. Patients meeting preliminary eligibility were chart reviewed for confirmation, then contacted through methods approved by each respective site's IRB, which included combinations of email, physical mail, and patient-portal notifications. Patients were offered an opportunity to opt-in or opt-out, and those who do not respond were contacted by phone call to assess interest and eligibility.

This trial was conducted remotely using patient identification, screening, and monitoring processes developed by the study team and applied in many trials involving virtual reality, including other NIH-sponsored trials using VR therapies for pain (NCT04409353, NCT04907643). Participants who provided eConsent and completed a 7-day "screener week" on REDCap were randomized and sent study materials by mail. Study onboarding was performed over the phone and did not require in-person interactions with the study team.

We employed a biopsychosocial conceptual framework for monitoring outcomes in the trial, focusing on pain intensity as the primary outcome, and included a range of other relevant PROs selected in partnership with our patient partners. PROs were collected via REDCap. Pain intensity was measured using a standard 11-point numeric rating scale (NRS) with a 24-hour recall. Consistent with NIH Helping to End Addiction Long-Term (HEAL) guidance, we measured daily pain NRS for 7-days during baseline (week 0), and again during the final week of the digital program study (week 8). Intention-to-Treat (ITT) analysis of the primary endpoint involved comparing the proportion of individuals who recorded a minimally clinically importance difference (MCID) of two on the average pain NRS recorded between Week 8 and Week 0. Secondary outcomes include the 4-item short form pain catastrophizing scale, 4-item NIH PROMIS Anxiety scale, 4-item NIH PROMIS Pain Interference scale, 2-item Pain Self-Efficacy Questionnaire, and average opioid usage derived from total morphine milligram equivalents (MMEs) in self-reported medication use. In addition, VR presence and cybersickness at the start of intervention use using the Presence Scale and Simulator Sickness Questionnaire (SSQ), respectively.