Pragmatic Comparative Effectiveness Trial of Evidence-based, On-demand, Digital Behavioral Treatments for Chronic Pain

This study will compare two available, evidence-based, digital pain treatment programs that patients can use at home. The goal is to see if one approach is better than the other, and whether certain patients respond to one more than the other. Study participants will be randomized to receive one of two treatment programs: Skills-Based VR or painTRAINER. Study devices will be delivered to the participant's home with instructions for use via FedEx; participants will receive remote technical support. They will be followed for 60 days and complete Patient Reported Outcome (PRO) questionnaires to assess functional status, pain levels, and use of pain medications (including opioids). Participants will also be asked to provide consent/authorization to access medical records from their treating facility.

We will perform a two-arm, multi-center, vRCT in a geographically diverse group of patients with mixed-etiology chronic pain. Using a random number generator, patients will be 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 VR app called EaseVRx. The primary analysis will compare changes in pain intensity over two months upon completion of the standardized 8-week digital CBT protocols. Secondary outcomes will include pain catastrophizing, Coronavirus-related anxiety, pain interference, self-efficacy, and opioid use. Although complete patient blinding can be challenging in digital health studies, particularly those using VR, we will follow the VR-CORE guidance and previous VR trial precedent by informing patients that researchers are testing the effect of "two types of audiovisual experiences on the perception of pain". Because it is important for researchers to exhibit equipoise when describing the competing interventions, we will prepare a script that uses neutral language regarding the two interventions, as per previous VR research. In addition, data analysts will be blinded to patient allocation.

We will employ broad inclusion criteria to maximize the external validity of the study and generalizability of results. In consulting with our patient partners who co-developed this application, we opted to study pain and distress for individuals with all forms of chronic pain except active cancer treatment and end-of-life care. The population impacted by this research thus broadly encompasses individuals with many different types of chronic pain conditions, including somatic, musculoskeletal, neuropathic, and visceral pain. More than 60% of individuals with chronic pain are women, and although the point prevalence for chronic pain increases with age, 35% of individuals 45-54 years of age report some form of chronic pain condition, and often multiple pain conditions. In terms of race and ethnicity, 81-85% report their race and ethnicity as non-Hispanic White, 8-9% identify as non-Hispanic Black, and 5-9% as Hispanic.

This vRCT will be conducted remotely using a process our team has developed and applied in many previous virtual trials, including in a current NIH-sponsored trial for chronic lower back pain. Patients will be recruited using pre-existing large registries within our consortium and will complete consent forms, receive study materials, and speak with study staff all from their home without requiring in-person visits. Patients will be recruited from three major sites: (1) Cedars-Sinai Health System (CSHS); (2) Ochsner Health; (3) UAB. At all sites, participants identified by search tools will be contacted by a combination of mail, email, and patient-portal notifications and offered an opportunity to opt-in or opt-out; those who do not respond will receive a follow-up phone call.

We will compare two digital platforms, both currently in wide use and supported by evidence, that deliver self-administered, 8-week, home-based CBT-based treatment programs for patients with chronic pain and distress: PainTRAINER (2D mHealth intervention) and EaseVRx (3D VR intervention).

We will employ a biopsychosocial conceptual framework for monitoring outcomes in the trial, focusing on pain intensity as the primary outcome, and including a range of other relevant PROs selected in partnership with our patient partners. PROs will be collected via REDCap. Pain intensity will be 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 will measure daily pain NRS for 7-days during baseline week 0, and again during the final week of the study (week 8). The minimally clinically importance difference (MCID) on the pain NRS is 2 points. Secondary Outcomes: Secondary outcomes will include the 4-item short form pain catastrophizing scale, 5-item Coronavirus Anxiety Scale, 8-item NIH PROMIS Pain Interference scale, 2-item Pain Self-Efficacy Questionnaire, and opioid usage in morphine milligram equivalents (MMEs). In addition, we will measure satisfaction with assigned treatment using the Pain Treatment Satisfaction Scale and will monitor for VR cybersickness using the Simulator Sickness Questionnaire (SSQ).

To learn more about the study and to assess your eligibility, please visit our study website at https://virtualmedicine.org/research/current/tech4pain

Eligibility Criteria:
We will recruit patients who: (1) have chronic pain, from any underlying condition, using the administrative definition of ICD-10 code series G89.X or one or more of 134 chronic overlapping pain condition codes, as previously standardized and validated by an expert panel; (2) have experienced average pain intensity of \>3 out of 10 within the previous week; (3) are ≥13 years of age; (4) are able to read/write English; (5) have either a personal computer or a smartphone; and (6) live in a designated rural zip code as defined by the Federal Office of Rural Health Policy (FORHP) data.

We will exclude patients who: (1) have a condition that interferes with use of the intervention (e.g., visual impairment); (2) are hospitalized; (3) are receiving active cancer treatment; (4) are receiving end-of-life care; or (5) have cognitive impairment that affects participation. We will stratify analyses across key patient characteristics, including type of pain condition, sex, age, race, ethnicity, State and zip code, Rural-Urban Commuting Area (RUCA) codes (a composite measure of population density, urbanization, and daily commuting), pain severity, opioid use, comorbidities, social support, and COVID-19 impacts (unemployment, financial hardship, family or personal COVID-19 diagnosis).