Randomized-controlled Trial of Virtual Reality for Chronic Low Back Pain to Improve Patient-reported Outcomes and Physical Activity
Phase: NA
Conditions: Chronic Low Back Pain
Sponsor: Cedars-Sinai Medical Center

 
 
 
 
 
Randomized-controlled trial of virtual reality for chronic 
low back pain to improve patient-reported outcomes 
and physical activity 
Protocol Number: STUDY00000631 
National Clinical Trial (NCT) Identified Number:  NCT04409353 
Principal Investigator: Brennan Spiegel, MD  
Sponsor: NIAMS 
Funded by: NIH  
Version Number:  v.8.1 
Revision: 19 October 2023 
Original: 28 April 2020 
 
Summary of Changes from Previous Version: 
Affected 
Section(s) 
Summary of Revisions Made 
Rationale 
1.3, 8.1, 8.3.1 
Added Charlson Comorbidity Index to SoA and 
correction to SoA, harmonization of 8.1 with 1.1 
objectives, error found in 8.3.1 
Charlson Comorbidy Index was 
requested by BACPAC other changes 
were corrected to text.  
2.3.1,6.3, 7.1, 
8.2, 8.2.1, 
9.4.7, 10.1.1.2, 
• 
Stratified randomization by recruitment site.  
• 
Added method for flagging patients with 
severe depression and SUD symptoms 
• 
Revision showing AppliedVR server is HIPPA 
compliant 
• 
Addition of cannabinoids to comedications 
comprehensive list of measures for 
confidentiality added from MOP 
• 
Addition of mood disturbance and radicular 
pain added to sub-group analysis 
• 
A description of additional language added to 
consent is provided.  
These changes were made due to 
recommendations from the DSMB.  

 
 
 
 
1.1, 1.3, 5.4, 
5.5, 6.1.1, 
6.2.4, 7.2, 
8.2.1, 9.4.9,  
• 
Replacing Charge 3 for Charge 4 
• 
Additional surveys added to SoA 
• 
Revision to Screen Failure definition  
• 
Change in interval of review for the 
race/ethnicity data to monthly 
assessment 
• 
Updated definition of Skills-based VR 
intervention  
• 
Change in withdraw policy 
These changes were made to provide 
the most up-to-date technology for 
the participants as well as update the 
feasibility of the protocol.  
1.1, 1.3, 3.0, 
8.2.1, 9.4.9, 
8.1, 5.5 
• 
Addition of tertiary objective of interest 
sleep quality (seconds of light/deep 
sleep) from the Fitbit 
• 
An update was made to SoA showing 
increased frequency of Event assessment 
• 
Needed to remove the AppliedVR tablet 
for data collection as that will not be 
available.  
• 
Additional subgroups added to the 
subgroup analysis based on additional 
questions added to study 
• 
The plan for retention has been updated.  
• 
Information added for CURES application 
• 
A revision in patient compensation was 
made 
Changes were made to harmonize 
with the SAP and up-to-date 
information from the virtual reality 
vendor. We wanted to add in info 
related to our CURES application. We 
also improved the compensation to 
provide compensation earlier in the 
study.  
3, 7.3, 8.2, 
8.2.1, 8.3.3.1, 
10.1.1.2 
• 
Minor edits, updated language 
• 
AE assessment frequency “weekly” 
instead of “biweekly”. 
Minor edits  
5.5, 7.3, 8.2.1, 
11 
• 
Loss to follow-up definition revised 
• 
Added info regarding AppliedVR VR 
usage data  
• 
Addition of Appendix: Diversity, 
Inclusion, & Equity Supplement 
• 
Updated 5.5 to reflect updated 
recruitment diversity benchmarks 
Necessary changes to study 
operations, addition of supplemental 
funding initiatives as appendix 
11.2 
• 
Recruitment objectives modified to 
incorporate treating physician letter 
Protocol reflects procedures and new 
hybrid recruiting strategy 

 
 
 
 
• 
Diversity supplement interview 
methodology updated to reflect that we 
did not record interviews and we drew 
from PAB waitlist 
1, 8.2, 8.3.1 
• 
Depression alert procedures updated to 
include actions to take when telephone 
assessment cannot be made; approved 
by DSMB 
• 
Neck pain and rash added as a known 
risk, borrowing approved language from 
STUDY00001363. 
• 
Table of contents page numbers updated 
With DSMB guidance, created a 
contingency plan in the event that 
severely depressed individuals are 
lost to follow-up. List of known 
potential AEs updated to reflect 
oversight of known neck pain risk and 
to incorporate the incidence of allergy 
to face foam used in VR goggles. 
5.5, 8.2, 
10.1.1.2 
• 
Onboarding procedures modified to take 
into account new instructional videos 
• 
Compliance procedures clarified and 
modified to account for optional SMS 
text messaging via REDCap 
• 
Remove 7 day wait after emailing 
recruitment letter 
• 
Removal of procedure for mailing study 
flyer 
Onboarding procedures now 
incorporate clear video instructions, 
and compliance monitoring updated 
to reflect current streamlined 
practices. General housekeeping on 
procedures to align with other VR 
trials. 
7.2 
• 
Modified definition of replaceable 
participant to exclude individuals who 
used VR intervention before withdrawing 
from study 
Study adequately powered based on 
withdrawals to date, and analyses 
should include individuals who found 
the intervention unsatisfactory and 
subsequently withdrew 
7.2, 12 
• 
Clarified confusing language in 
replaceable participant definition from 
previous mod  
• 
Addition of Appendix B: Digital Divide 
Supplement 
Typos in language confused our new 
definition of a replaceable participant. 
Second sub-study added to appendix 
prior to initiation of new methods. 
13 
• 
Addition of Appendix C: Cultural Barriers 
to VR Supplement 
Third sub-study added to appendix. 

 
 
 
 
13.2, 13.3 
• 
Addition of post-interview 
quantitative “Interviewer Sentiment 
Scale” to Appendix C  
• 
Disclose payment and requirement to 
complete both interview and 
questionnaire 
Directly capture effectiveness of AI 
interviewer 
 
 
 
Abbreviations 
AE 
Adverse Event 
CFR 
Code of Federal Regulations 
cLBP 
Chronic Low Back Pain 
CONSORT Consolidated Standards of Reporting Trials 
CBT 
Cognitive Behavioral Therapy 
CRF 
Case Report Form 
DSMB 
Data and Safety Monitoring Board 
eCRF 
Electronic Case Report Forms 
EHR 
Electronic Health Record 
GLP 
Good Laboratory Practices 
HIPAA 
Health Insurance Portability and Accountability Act  
IRB 
Institutional Review Board 
ITQ 
Immersive Tendency Questionnaire 
LBP 
Lower Back Pain 
MOOP 
Manual of Operating Procedures 
MRN 
Medical Record Number 
NCT 
National Clinical Trial 
NIH  
National Institutes of Health 
OHRP 
Office for Human Research Protections 
PI 
Principal Investigator 
QA 
Quality Assurance 
QC 
Quality Control 
SAE 
Serious Adverse Event 
SAP 
Statistical Analysis Plan 
SOA 
Schedule of Activities 
UP 
Unanticipated Problem 
US 
United States 
VR 
Virtual Reality 
 
 
 

Randomized-controlled trial of virtual reality for chronic low back pain to improve patient-reported outcomes and physical 
activity 
Version 8.0 
Protocol  
October 2023 
BACPAC_protocol_v.8.1_19_October_2023 
 
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1 
TABLE OF CONTENTS 
STATEMENT OF COMPLIANCE ............................................................................................................................. 3 
1 
PROTOCOL SUMMARY ............................................................................................................................... 3 
1.1 
Synopsis ................................................................................................................................................ 3 
1.2 
Schema ................................................................................................................................................. 6 
1.3 
Schedule of Activities (SoA) ............................................................................................................... 7 
2 
INTRODUCTION ............................................................................................................................................ 9 
2.1 
Study Rationale .................................................................................................................................... 9 
2.2 
Background........................................................................................................................................... 9 
2.3 
Risk/Benefit Assessment .................................................................................................................. 11 
2.3.1 
Known Potential Risks ................................................................................................... 11 
2.3.2 
Known Potential Benefits .............................................................................................. 13 
2.3.3 
Assessment of Potential Risks and Benefits .............................................................. 13 
3 
OBJECTIVES AND ENDPOINTS .............................................................................................................. 14 
4 
STUDY DESIGN ........................................................................................................................................... 18 
4.1 
Overall Design .................................................................................................................................... 18 
4.2 
Scientific Rationale for Study Design.............................................................................................. 18 
4.3 
Justification for Dose ......................................................................................................................... 19 
4.4 
End of Study Definition ..................................................................................................................... 19 
5 
STUDY POPULATION ................................................................................................................................ 19 
5.1 
Inclusion Criteria ................................................................................................................................ 19 
5.2 
Exclusion Criteria ............................................................................................................................... 20 
5.3 
Lifestyle Considerations .................................................................................................................... 20 
5.4 
Screen Failures .................................................................................................................................. 20 
5.5 
Strategies for Recruitment and Retention ...................................................................................... 20 
6 
STUDY INTERVENTION ............................................................................................................................ 21 
6.1 
Study Intervention(s) Administration ............................................................................................... 21 
6.1.1 
Study Intervention Description ..................................................................................... 22 
6.1.2 
Dosing and Administration ............................................................................................ 23 
6.2 
Preparation/Handling/Storage/Accountability ................................................................................ 23 
6.2.1 
Acquisition and accountability ...................................................................................... 23 
6.2.2 
Formulation, Appearance, Packaging, and Labeling ................................................ 23 
6.2.3 
Product Storage and Stability ....................................................................................... 23 
6.2.4 
Preparation ...................................................................................................................... 23 
6.3 
Measures to Minimize Bias: Randomization and Blinding ........................................................... 24 
6.4 
Study Intervention Compliance ........................................................................................................ 24 
6.5 
Concomitant Therapy ........................................................................................................................ 24 
6.5.1 
Rescue Medicine ............................................................................................................ 25 
7 
STUDY INTERVENTION DISCONTINUATION AND PARTICIPANT 
DISCONTINUATION/WITHDRAWAL .................................................................................................................... 25 
7.1 
Discontinuation of Study Intervention ............................................................................................. 25 
7.2 
Participant Discontinuation/Withdrawal from the Study ............................................................... 25 
7.3 
Lost to Follow-Up ............................................................................................................................... 26 
8 
STUDY ASSESSMENTS AND PROCEDURES ..................................................................................... 26 
8.1 
Efficacy Assessments ....................................................................................................................... 26 
8.2 
Safety and Other Procedures .......................................................................................................... 27 

Randomized-controlled trial of virtual reality for chronic low back pain to improve patient-reported outcomes and physical 
activity 
Version 8.0 
Protocol  
October 2023 
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8.2.1 
Procedures ...................................................................................................................... 28 
8.3 
Adverse Events and Serious Adverse Events ............................................................................... 29 
8.3.1 
Definition of Adverse Events (AE) ............................................................................... 29 
8.3.2 
Definition of Serious Adverse Events (SAE) .............................................................. 29 
8.3.3 
Classification of an Adverse Event .............................................................................. 30 
8.3.4 
Time Period and Frequency for Event Assessment and Follow-Up ....................... 30 
8.3.5 
Adverse Event Reporting .............................................................................................. 31 
8.3.6 
Serious Adverse Event Reporting ............................................................................... 31 
8.3.7 
Reporting Events to Participants ................................................................................. 32 
8.3.8 
Events of Special Interest ............................................................................................. 32 
8.3.9 
Reporting of Pregnancy ................................................................................................ 32 
8.4 
Unanticipated Problems .................................................................................................................... 32 
8.4.1 
Definition of Unanticipated Problems (UP) ................................................................. 32 
8.4.2 
Unanticipated Problem Reporting ................................................................................ 32 
8.4.3 
Reporting Unanticipated Problems to Participants ................................................... 33 
9 
STATISTICAL CONSIDERATIONS .......................................................................................................... 33 
9.1 
Statistical Hypotheses ....................................................................................................................... 33 
9.2 
Sample Size Determination .............................................................................................................. 34 
9.3 
Populations for Analyses .................................................................................................................. 36 
9.4 
Statistical Analyses............................................................................................................................ 36 
9.4.1 
General Approach .......................................................................................................... 36 
9.4.2 
Analysis of the Primary Efficacy Endpoint(s) ............................................................. 36 
9.4.3 
Analysis of the Secondary Endpoint(s) ....................................................................... 37 
9.4.4 
Safety Analyses .............................................................................................................. 38 
9.4.5 
Baseline Descriptive Statistics ..................................................................................... 38 
9.4.6 
Planned Interim Analyses ............................................................................................. 39 
9.4.7 
Sub-Group Analyses ..................................................................................................... 39 
9.4.8 
Tabulation of Individual participant Data .................................................................... 40 
9.4.9 
Exploratory Outcomes ................................................................................................... 40 
10 
SUPPORTING DOCUMENTATION AND OPERATIONAL CONSIDERATIONS .............................. 41 
10.1 
Regulatory, Ethical, and Study Oversight Considerations ........................................................... 41 
10.1.1 
Informed Consent Process ........................................................................................... 41 
10.1.2 
Study Discontinuation and Closure ............................................................................. 42 
10.1.3 
Confidentiality and Privacy ........................................................................................... 42 
10.1.4 
Future Use of Stored Specimens and Data ............................................................... 42 
10.1.5 
Key Roles and Study Governance .............................................................................. 43 
10.1.6 
Safety Oversight ............................................................................................................. 43 
10.1.7 
Clinical Monitoring .......................................................................................................... 44 
10.1.8 
Quality Assurance and Quality Control ....................................................................... 44 
10.1.9 
Data Handling and Record Keeping ............................................................................ 45 
10.1.10 
Protocol Deviations ........................................................................................................ 46 
10.1.11 
Publication and Data Sharing Policy ........................................................................... 46 
10.1.12 
Conflict of Interest Policy .............................................................................................. 46 
10.2 
Additional Considerations ................................................................................................................. 47 
11 
APPENDIX A: RESEARCH SUPPLEMENT – ADVOCATING FOR UNDERREPRESENTED 
PATIENT POPULATIONS IN RESEARCH ........................................................................................................... 47 

Randomized-controlled trial of virtual reality for chronic low back pain to improve patient-reported outcomes and physical 
activity 
Version 8.0 
Protocol  
October 2023 
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11.1 
background and approach ................................................................................................................ 47 
11.2 
AIMS AND METHODOLOGY .......................................................................................................... 47 
11.3 
REVISED RECRUITMENT TARGETS .......................................................................................... 50 
11.4 
STRATEGIES TO ENSURE TARGETS ARE MET ...................................................................... 50 
12 
APPENDIX B: RESEARCH SUPPLEMENT – UNDERSTANDING PATIENT PREDICTORS OF 
RESPONSE (3UH3AR076573-03S2) .................................................................................................................... 51 
12.1 
background and approach ................................................................................................................ 51 
12.2 
AIMS AND METHODOLOGY .......................................................................................................... 51 
12.3 
Career development plan ................................................................................................................. 52 
13 
APPENDIX C: RESEARCH SUPPLEMENT – Investigating the Barriers to Implementation and the 
Appropriateness of VR Content Across Diverse Cultures: A Retrospective Mixed Methods Study ............. 53 
13.1 
Background and Approach ............................................................................................................... 53 
13.2 
aims and methodology ...................................................................................................................... 55 
13.3 
strategies to ensure targets are met ............................................................................................... 57 
14 
Protocol Amendment History ...................................................................................................................... 57 
15 
REFERENCES ............................................................................................................................................. 59 
 
STATEMENT OF COMPLIANCE 
 
The trial will be carried out in accordance with International Conference on Harmonisation Good Clinical 
Practice (ICH GCP) and the following:  
 
• 
United States (US) Code of Federal Regulations (CFR) applicable to clinical studies (45 CFR 
Part 46, 21 CFR Part 50, 21 CFR Part 56, 21 CFR Part 312, and/or 21 CFR Part 812)  
 
National Institutes of Health (NIH)-funded investigators and clinical trial site staff who are 
responsible for the conduct, management, or oversight of NIH-funded clinical trials have 
completed Human Subjects Protection and ICH GCP Training. 
 
The protocol, informed consent form(s), recruitment materials, and all participant materials will 
be submitted to the Cedars-Sinai Institutional Review Board (IRB) for review and approval.  
Approval of both the protocol and the consent form must be obtained before any participant is 
enrolled.  Any amendment to the protocol will require review and approval by the IRB before 
the changes are implemented to the study.  In addition, all changes to the consent form will be 
IRB-approved; a determination will be made regarding whether a new consent needs to be 
obtained from participants who provided consent, using a previously approved consent form. 
 
1 
 
PROTOCOL SUMMARY 
1.1 
SYNOPSIS  
 
 
 
 
 
Title: 
Randomized-controlled trial of virtual reality therapy for chronic low back 
pain to improve patient-reported outcomes and physical activity. 
 

Randomized-controlled trial of virtual reality for chronic low back pain to improve patient-reported outcomes and physical 
activity 
Version 8.0 
Protocol  
October 2023 
BACPAC_protocol_v.8.1_19_October_2023 
 
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Study Description: 
This study will test the efficacy of an evidence-based virtual reality (VR) 
therapy program as a non-pharmacological supplement to management of 
chronic lower back pain. Study participants will be randomized to receive 
one of three VR programs: Skills-Based VR, Distraction VR, or Sham VR. In 
addition to a VR headset, all participants will receive a Fitbit Charge 4 
watch. 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 90 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.  
 
 
Objectives: 
 
Primary Objective:   
To assess the efficacy of immersive Skills-Based VR and Distraction VR in 
improving perceived pain from baseline to Day 30. 
 
 
 
Secondary Objective:  
To assess the efficacy of immersive Skills-Based VR and Distraction VR in 
improving perceived pain interference from baseline to Day 60 and Day 
90.  
To assess the efficacy of Skills-Based and Distraction VR in improving self-
reported perceptions of sleep quality, sleep depth, and restoration 
associated with sleep from baseline to Day 90. 
To assess the efficacy of Skills-Based and Distraction VR in improving self-
reported perceptions of anxiety from baseline to Day 90. 
To assess the efficacy of Skills-Based and Distraction VR in improving self-
reported pain catastrophizing from baseline to Day 90. 
To assess the efficacy of Skills-Based and Distraction VR in reducing use of 
opioids from baseline to Day 90. 
 
 
Tertiary Objectives:  
To assess the efficacy of Skills-Based and Distraction VR in improving self-
reported physical function from baseline to Day 90. 
To assess the efficacy of Skills-Based and Distraction VR in improving self-
reported depression from baseline to Day 90. 
To assess the efficacy of Skills-Based and Distraction VR via patients’ global 
impression of change (PGIC). 
To assess the efficacy of Skills-Based and Distraction VR in improving 
wearable measures of physical activity from baseline to Day 90. 

Randomized-controlled trial of virtual reality for chronic low back pain to improve patient-reported outcomes and physical 
activity 
Version 8.0 
Protocol  
October 2023 
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To assess the efficacy of Skills-Based and Distraction VR in improving 
wearable measures of sleep quality from baseline to Day 90. 
To assess the effect of presence on the efficacy of Skills-Based and 
Distraction VR in improving measures of pain interference from baseline to 
Day 30. 
To assess the effect of Immersive Tendencies on the efficacy of Skills-
Based and Distraction VR in improving measures of pain interference from 
baseline to Day 30. 
To assess the effect of dose on the efficacy of Skills-Based and Distraction 
VR in improving measures of pain interference from baseline to Day 30. 
 
Endpoints: 
Primary Endpoint: Change in PROMIS Pain Interference  
Secondary Endpoints: Change in PROMIS Sleep Disturbance, PROMIS 
Anxiety, Pain Catastrophizing, MME usage. 
 
 
Study Population: 
Individuals ages 13 or older with an ongoing low back-pain problem that 
has persisted at least 3 months and has resulted in pain on at least half the 
days in the past 6 months.  
 
 
Phase: 
Phase 2 
 
 
Description of 
Sites/Facilities Enrolling 
Participants: 
Three outpatient clinic sites, including the Cedars-Sinai Orthopaedic Clinic, 
Cedars-Sinai Medical Network Chronic Pain Program, and Attune Health, a 
musculoskeletal clinic affiliated with Cedars-Sinai. In addition, participants 
may enroll remotely. 
 
 
Description of Study 
Intervention: 
All participants will receive a virtual reality headset with one of three 
software programs: 
- 
Immersive Skills-Based VR therapy  
- 
Immersive Distraction VR therapy  
Non-immersive Sham VR Therapy with 2-D videos 
Study Duration: 
48 months 
 
 
Participant Duration: 
90 days 
 
 

Randomized-controlled trial of virtual reality for chronic low back pain to improve patient-reported outcomes and physical 
activity 
Version 8.0 
Protocol  
October 2023 
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1.2 
SCHEMA 
 
 
 
Sham VR Arm: 
Non-immersive content 
(n=120) 
Skills Based VR Arm: 
Immersive VR with skills 
(n=120) 
Distraction VR Arm: 
360-degree videos 
(n=120) 
Pre-Screening  
Screening Week 
Day -8 to -2 
Enrollment  
Day -1 to 0 
 
Day 1 (+6 days) 
Day 1 to 89  
(+6 days) 
Day 90
Patient receives study intervention equipment.  
Final Assessments 
Participant uses VR therapy program and wears FitBit. Questionnaires are 
emailed based on schedule from Day 1 to Day 90.  
See Section 1.3 Schedule of Activities  
 
Remote Technical Support / Adverse Event Review and Reporting 
Randomize (n=360) 
Prospective patients identified by Deep 6 or provider registry.  
Contact patient by telephone. Confirm eligibility and obtain informed consent. 
Participants complete online baseline survey and 7-day pain intensity journal. 
See Section 1.3 Schedule of Activities  
Technical Onboarding Call 

Randomized-controlled trial of virtual reality for chronic low back pain to improve patient-reported outcomes and physical 
activity 
Version 8.0 
Protocol  
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1.3 
SCHEDULE OF ACTIVITIES (SOA) 
 
 
Procedures  
Pre-screening 
Screening Week 
Day -8 to -2 
Enrollment 
Day -1 to 0 
 Day 1  
(+ 6 days) 
Day 7  
(+ 6 days) 
Day 15 
(+ 6 days) 
Day 21 
(+ 6 days) 
Day 30 
(+6 days) 
Day 45 
(+ 6 days) 
Day 60 
(+ 6 days) 
Day 75 
(+ 6 days) 
Day 90 
(+ 6 days) 
Prospective patient identified (DEEP 6 or 
provider registry) 
X 
 
 
 
 
 
 
 
 
 
 
 
Confirm eligibility and Informed Consent 
via telephone and REDCap 
X 
 
 
 
 
 
 
 
 
 
 
 
Online Pain Intensity Journal (7 days) 
 
X 
 
 
 
 
 
 
 
 
 
X 
Screening Week Online Baseline Survey  
(see below) 
 
X 
 
 
 
 
 
 
 
 
 
 
Randomization  
 
 
X 
 
 
 
 
 
 
 
 
 
Participant receives study intervention kit 
 
 
X 
 
 
 
 
 
 
 
 
 
Technical onboarding call 
 
 
 
X 
 
 
 
 
 
 
 
 
Intervention: Participant uses VR therapy 
program and wears Fitbit Charge 4 watch 
 
 
 
X 
------------------------------------------------------------------------ 
X 
Online survey: NIH HEAL Minimum Dataset 
 
X 
 
 
 
 
 
 
 
 
 
X 
Immersive Tendency Questionnaire (ITQ)1 
and Motion Sickness Propensity Survey2 
 
X 
 
 
 
 
 
 
 
 
 
 
Treatment expectation question 
 
X 
 
 
 
 
 
 
 
 
 
 
Simulator Sickness Questionnaire (SSQ)3 
and Presence Survey 
 
 
 
X 
 
 
 
 
 
 
 
 
Online survey: Primary outcome: PROMIS® 
Pain Interference 
 
X 
 
 
X 
X 
X 
X 
X 
X 
X 
X 
Discontinuation of Treatment 
Questionnaire 
 
 
 
 
X 
X 
X 
X 
X 
X 
X 
X 
PROMIS® Physical Function4, Anxiety4, 
Depression4, Sleep disturbance4; Pain 
intensity/interference with Enjoyment of 
life/interference with General activity 
(PEG)5, PCS-66 
 
X 
 
 
 
X 
 
X 
X 
X 
X 
X 
EMR data: Charlson Comorbidity Index7, 
CURES and EMR: Prescription Data 
 
X 
 
 
 
 
 
 
 
 
 
X 
Perceived study arm question,  
treatments in the last 90 days question 
 
 
 
 
 
 
 
 
 
 
 
X 
Online survey: PHQ-2, GAD-2, PGIC, TAPS 
[1/2] 
 
X 
 
 
 
 
 
 
 
 
 
X 
Remote technical support 
 
 
 
X 
------------------------------------------------------------------------ 
X 
End of study procedure question 
 
 
 
 
 
 
 
 
 
 
 
x 

Randomized-controlled trial of virtual reality for chronic low back pain to improve patient-reported outcomes and physical 
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Version 8.0 
Protocol  
October 2023 
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Procedures  
Pre-screening 
Screening Week 
Day -8 to -2 
Enrollment 
Day -1 to 0 
 Day 1  
(+ 6 days) 
Day 7  
(+ 6 days) 
Day 15 
(+ 6 days) 
Day 21 
(+ 6 days) 
Day 30 
(+6 days) 
Day 45 
(+ 6 days) 
Day 60 
(+ 6 days) 
Day 75 
(+ 6 days) 
Day 90 
(+ 6 days) 
Event Assessment: AE, SAE and UP review 
and reporting 
 
 
 
X 
X  
X 
X  
X 
X 
X 
X 
X 
ITQ: Immersive Tendency Questionnaire 
PEG: Pain, Enjoyment, General Activity 
PCS-SF: Pain Catastrophizing Scale-Short Form 6 
PHQ-2: Patient Health Questionnaire-2 
GAD-2: Generalized Anxiety Disorder 2-item 
PGIC: Patient Global Impression of Change 
TAPS: Tobacco, Alcohol, Prescription Medication, and Other Substance Use 
AE: Adverse event 
SAE: Serious adverse event 
UP: Unanticipated Problem 
 
 
 

Randomized-controlled trial of virtual reality for chronic low back pain to improve patient-reported outcomes and physical 
activity 
Version 8.0 
Protocol  
October 2023 
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2 
 
INTRODUCTION 
 
2.1 
STUDY RATIONALE  
Chronic low back pain (cLBP) is a prevalent and costly condition that markedly impairs physical, 
emotional, and social function. The 2015 Global Burden of Disease Study estimated that the prevalence 
of cLBP increased by more than 17% between 2005 and 2015.8 In 2010, low back pain ranked third in 
disability-adjusted life years in North America, and the prevalence is expected to increase further due to 
the aging population and rise in obesity rates.8,9 The National Health Interview Survey found that more 
than a quarter of all workers reported low back pain in the prior 3 months.10 More than half reported 
the pain caused disability related to self-care, work, or social activities.11  
 
Diminished work productivity attributable to cLBP is conservatively estimated at more than $28 billion 
annually.12 Escalating treatment expenses include an increase of 423% in the cost of opioid prescriptions 
for patients with spinal disorders from 1997-2004, increases of 307% in the volume of lumbar MRI and 
231% in the number of spinal injections reimbursed by Medicare from 1994-2001, and a 220% increase 
in lumbar spinal fusion surgeries between 1990 and 2001.13 The Back Pain Survey administered as part 
of the National Health and Nutrition Examination Survey (NHANES) found that opioids were the most 
commonly prescribed pain medication taken by patients with cLBP (18.8%), followed by antidepressants 
(17.8%).14 More than three quarters of people using prescribed opioids took them long term. Yet, 
patients with cLBP often discover that opioids fall short in delivering meaningful pain reduction or 
improving health-related quality of life (HRQOL).14 Additionally, opioids are associated with a host of 
adverse effects, including but not limited to fall risk, constipation, sedation, physical dependency, opioid 
use disorder, and drug related mortality.15 Hence, there is a critical gap in pain management in cLBP; it is 
vital to address this evidence gap in a way that maximizes benefits for patients while minimizing harms 
from medical therapy. 
 
2.2 
BACKGROUND  
The dynamic nature of clinical medicine, coupled with limited time to spend with individual patients, 
pose challenges to offering holistic care for patients with pain. Treatment of pain is often focused on 
pharmacological management, which can yield inconsistent and sub-optimal pain control. However, 
extensive data reveal that adjunctive non-pharmacological techniques, such as cognitive behavioral 
therapy and relaxation techniques, can modify cognitions and behaviors that influence the perception of 
pain. Therapeutic virtual reality (VR) has emerged as a promising and evidence-based treatment 
modality for both acute and chronic pain.16-25 Users of VR wear a pair of goggles with a close-proximity 
stereoscopic screen that creates a sensation of being transported into lifelike, three-dimensional worlds 
that create a sense of “presence.” To date, VR has been used in numerous clinical settings to treat 
anxiety disorders, manage depression, support physical rehabilitation, and manage a wide range of 
acute and chronic pain syndromes.21,26-30 For example, VR coupled with medication is effective in 
decreasing pain during bandage changes for severe burns as an alternative to opioids.26,31 Similarly, VR 
reduces pain and provides positive distraction during routine procedures, such as intravenous line 
placements29 and dental procedures.27 Other studies reveal that VR helps manage chronic pain 
conditions such as complex regional pain syndrome,32 lower back pain,33,34 and chronic neck pain.35 
Multiple studies also demonstrate that VR offers clinical benefits in musculoskeletal pain, including cLBP. 
Recently, a randomized trial by Pozeg and colleagues revealed that VR is effective for managing 

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neuropathic pain from spinal injury.36 Similarly, Jones and colleagues employed a VR-based distraction 
therapy to manage patients with a wide variety of chronic musculoskeletal pain syndromes, including 
cLBP, and documented a 33% reduction in pain before vs. after VR therapy.33 In a separate study by 
Gromala and colleagues using a specialized  VR  game designed to empower patients with pain, VR 
reduced chronic musculoskeletal pain—again including cLBP patients—by 37% and outperformed a 
standard non-VR distraction intervention.34 Thomas and   colleagues evaluated a VR “dodgeball  
intervention” for cLBP and demonstrated that activating graded physical activity in a virtual game 
simulation improved lumbar spine flexion while reducing expectations of fear and harm vs. a non-VR 
control condition.37 A more recent randomized comparative effectiveness study conducted by our group 
at Cedars-Sinai also demonstrated the analgesic benefits of VR for inpatient management of acute and 
chronic pain, including patients with cLBP, demonstrated a 24% reduction in pain that outperformed a 
2D generic relaxation video.38 Sixty-five percent of VR patients achieved a clinically significant pain 
response vs. 40% of controls (p=0.01; NNT=4).38  
Beyond individual studies, there are now several meta-analyses evaluating the analgesia benefits of VR 
in both acute and chronic pain syndromes, and these studies reveal consistently significant benefits.17-22 
In  one systematic review of randomized controlled inpatient VR trials published by the Cedars-Sinai 
group, we identified 11 studies comparing VR vs. a control condition in diverse populations.21 VR was 
effective in most of these studies and well tolerated in all reports. However, the studies we identified 
were of mixed methodological quality. We concluded that the VR literature will benefit from larger, 
higher quality studies with a longer follow-up period, enhanced focus on long-term safety, and more 
robust efforts to identify patient-level predictors of efficacy, particularly in cLBP. In the meantime, the 
existing literature supports VR as a broadly effective therapy for both chronic and acute pain 
management across pain conditions, including cLBP.  
The mechanisms of action (MOAs) of VR analgesia have been extensively evaluated over the past twenty 
years. Research indicates that VR reduces pain through four MOAs: First, by stimulating the visual cortex 
while engaging other senses, VR acts as a distraction to limit the user’s processing of nociceptive 
stimuli.39 The result is a form of “inattentional blindness” where the prefrontal cortex redirects 
attentional bandwidth to the virtual environment, leaving diminished ability to attend to pain signals 
outside the “spotlight of attention.”40 By overwhelming the visual,  auditory, and proprioception  senses, 
VR is thought to create  an immersive  distraction that  restricts  the  brain from processing pain. Second, 
through gate control theory,41 VR is thought to activate descending inhibitory pathways and inhibit 
spinal transmission of peripheral afferent pain signals.42-44 Third, VR creates an illusion of time 
acceleration, effectively shortening the perception of pain episodes through its effects on prefrontal 
time perception.45-47 For example, controlled trials reveal that VR reduces the perceived length of labor 
and delivery during childbirth, episiotomy repair, endoscopic procedures, and chemotherapy infusions 
by an average of 30-50%.45-47 These effects have been demonstrated both clinically and experimentally. 
Hoffman and colleagues revealed that VR affects pain processing in the sensory and insular cortex, 
indicating it can reduce both the intensity of pain and the emotional response to pain.48,49 Moreover, the 
investigators found that VR has the same fMRI effects as hydromorphone, and was equally effective at 
blocking acute pain as the powerful opioid.48 Clinical trials also demonstrate reductions in sensory, 
cognitive, and affective components of pain, suggesting that the fMRI changes shown experimentally 
appear to translate into improved patient-centered outcomes across dimensions of pain. Investigators 
like Hoffman,24,31,50,51 Rizzo,52 Rothbaum,53-55 and Bordnick,56-58 among many others, are studying the 
neurobiological mechanisms of VR across a range of conditions.21,30 Fourth, VR offers an immersive 
platform through which patients can develop and practice specific skills. This mechanism may underlie 
VR’s established benefits in cognitive rehabilitation such as for phobia,59-65 anxiety66-68 and 

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depression69,70 management, where skills may be learned in VR and durably extended outside of the 
virtual environments. In short, VR has multiple analgesic MOAs that translate into clinically important 
patient benefits. Importantly, the ubiquity of mobile high-performance computing has now reduced 
both the size and cost of VR devices such that mobile VR units are feasible for everyday use. Our team at 
CSMC has employed therapeutic VR in over 3,000 patients throughout inpatient and outpatient settings 
and found that it is feasible and practical for patients to use the equipment. Our latest data reveal that 
VR analgesia is effective across ages, with a greater benefit for those over the age of 65, possibly due to 
differences in expectations surrounding digital technologies(in  press).We have also documented that VR 
is incrementally more effective  for those with the highest pain scores (>7 out of 10 on numeric rating 
scale), demonstrating benefits in those with the most severe symptoms (in press). In short, the field of 
therapeutic VR has gained traction in the past several years on the strength of less expensive, more 
scalable, and higher quality  VR equipment, meaningful advances in the clinical and translational  science 
of therapeutic VR, dissemination of methodological  guidance unique to VR trials, and evidence of 
patient acceptability of using the  equipment. However, there has been no research to date evaluating 
longer-term outpatient use and safety of VR for cLBP, and there are important unanswered questions 
about the durability of VR efficacy that warrant further research. 
In previous systematic reviews of VR RCTs, including our own analysis of the literature, many of the 
identified studies were limited by study design issues, such as improper control groups and incomplete 
PRO assessment.21 PROs, such as functional status, HRQOL, and satisfaction with care, are necessary to 
determine whether VR is an effective, sustainable intervention for cLBP management.71 Additionally, 
although evidence reveals that VR is effective as a short-term analgesic, it is less clear how or whether 
continued use of VR reduces the frequency, intensity, and experience of ongoing pain, predicts long-
term change in other PROs, or reduces opioid use. It also remains unknown whether different forms of 
VR have varying efficacy in cLBP. Important unanswered clinical questions include: (1) do skills-based VR 
programs that leverage the immersive qualities of VR to teach exportable skills using cognitive 
behavioral therapy (CBT), guided meditation, and biofeedback-based breathing exercises outperform 
conventional VR that employs distraction? (2) Are there patient-level characteristics that predict a 
clinical response to VR?  (3)  Are there usage patterns or engagement characteristics that predict 
enhanced response to VR?  (4) Can VR reduce pain while also reducing long-term opioid requirements? 
The current study will seek to answer these questions in cLBP. The long-term safety and tolerability of 
therapeutic VR is also largely untested. In short-term use, a minority of patients may develop transient 
dizziness, fatigue, or nausea—a syndrome called cybersickness—resulting from sensory mismatch 
between the visual and vestibular systems.72-75 The prevalence of cybersickness has fallen with dramatic 
improvements in hardware and software. Other technical advances have reduced eye strain, minimized 
physical discomfort of wearing the headset, and reduced unnecessary visual motion.74 Nonetheless, 
there are limited data monitoring the incidence of cybersickness over longer term usage, such as weeks 
or months. The current study will perform longer-term safety and tolerability assessments of 
therapeutic VR in cLBP. 
 
 
2.3 
RISK/BENEFIT ASSESSMENT   
 
2.3.1 KNOWN POTENTIAL RISKS  
This study poses minimal risk to participants. Immediate risks may include minor psychological distress 
from questionnaire items asking about health and employment status. There is also a small76 short-term 
risk of transient risk of VR-related “cybersickness.” Cybersickness is transient vertigo, nausea, or 

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headache. It results from sensory mismatch between the visual and vestibular systems72-75 and usually 
resolves within minutes of removing the VR headset. The prevalence of cybersickness has fallen with 
improvements in hardware and software. Technical advances have reduced eye strain, minimized 
physical discomfort of wearing a VR headset, and reduced unnecessary visual motion.74 In the 
therapeutic setting, we also choose slow-moving scenes rather than highly kinetic visuals. As a result, 
cybersickness has become less prevalent and significant for people using VR.74 In this study, each VR 
session lasts less than 20 minutes. Participants will be instructed to complete just one session during 
each use to reduce the risk of cybersickness. 
 
There are no anticipated long-term physical risks from participating in this study. There is a small risk of 
breach of confidentiality associated with the electronic collection and transmission of protected health 
information. This risk will be minimized by following proper procedures for assuring data integrity and 
confidentiality. 
 
The following is our list of study participant confidentiality safeguards:  
 
 
Electronic files – data identifying participants will be stored in status tracking 
logs within password-protected excel files on Cedars-Sinai encrypted shared 
drives e.  
 
Forms – survey forms and other pages containing personal identifying 
information will be saved within the REDCap system.  
 
Data listings - participant name, name code, hospital chart, record number, 
Social Security Number, or other unique identifiers will not be included in any 
published data listing.  
 
Data distribution - data listings containing PHI such as name, MRN, or other 
identifiers easily associated with a specific participant will not be distributed.  
 
Data disposal - computer listings that contain participant-
identifying information will be disposed of in accordance with institutional 
policies and procedures, after study completion.  
 
Access - participant records will not be accessible to 
persons/institutions outside those listed on the HIPAA form signed 
by  the participant.  
 
Storage - study forms and related documents retained during and after study 
completion will be stored within a secure Box folder accessible only by approved 
study staff. Some documents, such as survey exports, may be locally stored on a 
Cedars-Sinai encrypted shared drive or computer desktop during data analysis.  
 
Passwords – Multi-factor password authentication will be required to access 
documents stored on the cloud and on local desktops at Cedars-Sinai.  
 
User Training - study staff with access to clinical computer systems are trained 
and certified to maintain confidentiality prior to authorization by the Cedars- 
Sinai IRB.  
 
System Testing – new computer systems used by clinical staff are processed by 
the Cedars-Sinai IT (EIS) to ensure the password-activated systems perform as 
intended. 
 
Certificate of Confidentiality – NIH funded research that involves human 
subjects and collects information which may identify a person is automatically 

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protected by a Certificate of Confidentiality to prevent forced disclosures (e.g., 
subpoenas). 
 
Privacy Breach Reporting – In the rare instance where an accidental 
release of identifiable PHI may occur, it will be reported to the Cedars-
Sinai IRB and the Cedars-Sinai Privacy Office for adjudication and 
corrective actions.  
 
2.3.2 KNOWN POTENTIAL BENEFITS  
Potential immediate benefits include reduction of chronic low back pain and general improvement in 
psychological health. Potential long-term benefits include improved functionality, reduced opioid use, 
and improvements in overall physical and psychological health.  This research will contribute to societal 
knowledge about the safety and efficacy of therapeutic VR.  
 
 
2.3.3 ASSESSMENT OF POTENTIAL RISKS AND BENEFITS  
Virtual reality hardware and software has advanced significantly in the last decade.  Modern studies 
utilizing VR have found general satisfaction with devices among participants. The incidence and severity 
of VR-related side effects are low, and symptoms generally subside within minutes of taking off the 
headset.  
 
Participation in the study may alleviate pain among individuals who have previously relied on opioids, 
potentially enabling them to reduce opioid use and related side effects. Sustained pain relief also may 
allow individuals to return to work faster, improve physical mobility, and enhance biopsychosocial 
health. As a result, the short- and long-term anticipated benefits of participation outweigh the minimal 
short-term risks.  
 

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3 
OBJECTIVES AND ENDPOINTS 
 
OBJECTIVES 
ENDPOINTS 
JUSTIFICATION FOR 
ENDPOINTS 
Primary 
 
 
To assess the efficacy of 
immersive Skills-Based VR and 
Distraction VR in improving 
perceived pain from baseline 
to Day 30. The trial will be 
considered a success if there is 
statistical evidence of 
improvement in either VR 
group compared to sham VR. 
 
 
 
 
The change from study baseline to 
Day 30 in pain interference as 
measured by the 8-item PROMIS 
Pain Interference scale is the 
primary endpoint. This scale 
measures the consequences of 
pain on relevant aspects of life, 
including the extent to which pain 
hinders engagement with social, 
cognitive, emotional, physical, and 
recreational activities. 
The study will be considered a 
success if there is a statistically 
significant difference of 5 points in 
the Pain Interference score 
between participants in either the 
Skills-Based or Distraction VR arm 
compared with the Sham VR arm. 
 
The NIH Pain Consortium 
Research Task Force (RTF) draft 
standards for research on cLBP 
recommend a uniform minimal 
data set that includes self-
reported measures of pain 
interference.77 
The PROMIS PI scale is a 
validated instrument with 
excellent content validity, 
construct validity, and 
reliability in patients with 
chronic pain. Past work 
indicates that changes of 3.5 to 
5.5 points in PROMIS-PI scores 
of people with LBP can be 
considered meaningful.78,79  
 
 
 
Secondary 
 
 
To assess the efficacy of 
immersive Skills-Based VR and 
Distraction VR in improving 
perceived pain interference 
from baseline to Day 60 and 
Day 90. The objective will be 
considered achieved if there is 
statistical evidence of 
improvement in either VR 
group compared to control 
(sham) VR. 
 
The change from study baseline to 
day 60 and day 90 in pain 
interference as measured by the 
8-item PROMIS PI scale is a 
secondary endpoint. This scale 
measures the consequences of 
pain on relevant aspects of life, 
including the extent to which pain 
hinders engagement with social, 
cognitive, emotional, physical, and 
recreational activities. 
We will test for a statistically 
significant difference of 5 points in 
the PROMIS PI score from 
baseline, and compare differences 
between either VR group and 
control (sham) VR. 
The NIH Pain Consortium RTF 
draft standards for research on 
cLBP recommend a uniform 
minimal data set that includes 
self-reported measures of pain 
interference.77 
The PROMIS scale is a validated 
instrument with excellent 
content validity, construct 
validity, and reliability in 
patients with chronic pain.79 
Past work indicates that 
changes of 3.5 to 5.5 points in 
PROMIS-PI scores of people 
with LBP can be considered 
meaningful.78  

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OBJECTIVES 
ENDPOINTS 
JUSTIFICATION FOR 
ENDPOINTS 
To assess the efficacy of Skills-
Based and Distraction VR in 
improving self-reported 
perceptions of sleep quality, 
sleep depth, and restoration 
associated with sleep from 
baseline to Day 90. The 
objective will be considered 
achieved if there is statistical 
evidence of improvement in 
either VR group compared to 
control (sham) VR. 
 
The change from study baseline to 
day 90 in sleep disturbance as 
measured by the 6-item PROMIS 
Sleep Disturbance scale is a 
secondary endpoint. This scale 
assesses self-reported perceptions 
of sleep quality, sleep depth, and 
restoration associated with sleep. 
This includes perceived difficulties 
and concerns with getting to sleep 
or staying asleep, as well as 
perceptions of the adequacy of - 
and satisfaction with - sleep. 
We will test for a statistically 
significant difference of 5 points in 
the PROMIS Sleep Disturbance 
score from baseline, and compare 
differences between either VR 
group and control (sham) VR. 
The NIH Pain Consortium RTF 
draft standards for research on 
cLBP recommend a uniform 
minimal data set that includes 
self-reported measures of sleep 
disturbance.77 
The PROMIS sleep disturbance 
item banks display strong 
measurement properties for 
assessing general aspects of 
sleep and sleep related 
impairments in cLBP patients.80  
To assess the efficacy of Skills-
Based and Distraction VR in 
improving self-reported 
perceptions of anxiety from 
baseline to Day 90. The 
objective will be considered 
achieved if there is statistical 
evidence of improvement in 
either VR group compared to 
control (sham) VR. 
The change from study baseline to 
Day 90 in anxiety as measured by 
the 4-item PROMIS Anxiety scale 
is a secondary endpoint. This scale 
assesses self-reported perceptions 
of fear, anxious misery (worry, 
dread), hyperarousal, and somatic 
symptoms related to arousal.  
We will test for a statistically 
significant difference of 5 points in 
the PROMIS anxiety score from 
baseline, and compare differences 
between either VR group and 
control (sham) VR. 
While not included in the 
recommended minimal data 
set, the NIH Pain Consortium 
RTF considers anxiety a 
conceptually relevant construct 
associated with cLBP.77 
The PROMIS Anxiety item 
banks have demonstrated 
strong measurement properties 
for assessing general aspects of 
anxiety in cLBP patients.81  
To assess the efficacy of Skills-
Based and Distraction VR in 
improving self-reported pain 
catastrophizing from baseline 
to Day 90. The objective will be 
considered achieved if there is 
statistical evidence of 
improvement in either VR 
group compared to control 
(sham) VR. 
The change from study baseline to 
Day 90 in pain catastrophizing as 
measured by PCS SF-6 is a 
secondary endpoint.  
We will test for a difference in 
rates of high catastrophizing as 
defined by a score of ≥7 on the 
PCS-SF6, and compare these 
differences between either VR 
group and control (sham) VR. 
 
The NIH Pain Consortium RTF 
draft standards for research on 
cLBP recommend a uniform 
minimal data set that includes 
self-report measures of pain 
catastrophizing.77 Further, 
changes in catastrophizing are 
associated with improvement 
in multidisciplinary pain 
treatment.82 
 

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OBJECTIVES 
ENDPOINTS 
JUSTIFICATION FOR 
ENDPOINTS 
To assess the efficacy of Skills-
Based and Distraction VR in 
reducing use of opioids from 
baseline to Day 90. The 
objective will be considered 
achieved if there is statistical 
evidence of improvement in 
either VR group compared to 
control (sham) VR. 
The change from study baseline to 
Day 90 in weekly average opioid 
dosage calculated as a 7-day 
average of daily maximum 
milligrams morphine equivalent 
(MME) is a secondary endpoint. 
We will test for a greater than .5 
SD in change from baseline, and 
compare differences between 
either VR group and control 
(sham) VR. 
Despite some evidence from 
randomized controlled trials 
(RCTs) on the efficacy of 
opioids in the short-term 
treatment of low back pain, 
little evidence is available on 
long term efficacy and safety. 
Lowering MME as prescribed 
while lowering pain is an 
important goal of cLBP 
treatments.83  
Tertiary/Exploratory  
 
 
To assess the efficacy of Skills-
Based and Distraction VR in 
improving self-reported 
physical function from 
baseline to Day 90. The 
objective will be considered 
achieved if there is statistical 
evidence of improvement in 
either VR group compared to 
control (sham) VR. 
The change from study baseline to 
Day 90 in physical function as 
measured by the 6-item PROMIS 
Physical Function scale is an 
exploratory endpoint. This scale 
measures self-reported 
functioning of one’s upper 
extremities (dexterity), lower 
extremities (walking or mobility), 
and central regions (neck, back), 
as well as instrumental activities 
of daily living. 
We will test for a statistically 
significant difference of 5 points in 
the PROMIS Physical Function 
score from baseline, and compare 
differences between either VR 
group and control (sham) VR. 
The NIH Pain Consortium RTF 
draft standards for research on 
cLBP recommend a uniform 
minimal data set that includes 
self-reported measures of 
physical function.77 
The PROMIS physical function 
item banks display excellent 
measurement properties for 
assessing general aspects of 
physical function in cLBP 
patients.80     
To assess the efficacy of Skills-
Based and Distraction VR in 
improving self-reported 
depression from baseline to 
Day 90. The objective will be 
considered achieved if there is 
statistical evidence of 
improvement in either VR 
group compared to control 
(sham) VR. 
The change from study baseline to 
Day 90 in physical function as 
measured by the 4-item PROMIS 
Depression scale is an exploratory 
endpoint. This scale measures self-
reported negative mood (sadness, 
guilt), views of self (self-criticism, 
worthlessness), and social 
cognition (loneliness, interpersonal 
alienation), as well as decreased 
positive affect and engagement 
(loss of interest, meaning, and 
purpose). 
We will test for a statistically 
significant difference of 5 points in 
The NIH Pain Consortium RTF 
draft standards for research on 
cLBP recommend a uniform 
minimal data set that includes 
self-report measures of 
depression.77 
The PROMIS depression item 
banks display excellent 
measurement properties for 
assessing general aspects of 
depression in cLBP 
patients.79,80,84  

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OBJECTIVES 
ENDPOINTS 
JUSTIFICATION FOR 
ENDPOINTS 
the PROMIS Depression score 
from baseline, and compare 
differences between either VR 
group and control (sham) VR. 
To assess the efficacy of Skills-
Based and Distraction VR via 
patients’ global impression of 
change (PGIC). The objective 
will be considered achieved if 
there is statistical evidence of 
higher rates of self-reported 
improvement in either VR 
group compared to control 
(sham) VR. 
The overall effect of treatment 
from study baseline to Day 90 as 
measured by the PGIC is an 
exploratory endpoint. This scale 
measures self-reported belief 
regarding efficacy of treatment.  
A favorable response of 5-7 on the 
PGIC indicates significant 
improvement occurred over the 
course of the study. 
We will test for a statistically 
significant difference in PGIC 
responses between either VR 
group and control (sham) VR. 
This exploratory endpoint will 
act as a check on internal 
validity for Primary and 
Secondary endpoints, and a 
general assessment of 
satisfaction with 
treatment.79,80,84  
The PGIC has established 
validity in measuring self-
reported global change in cLBP 
trials.85,86  
To assess the efficacy of 
Skills-Based and Distraction 
VR in improving wearable 
measures of physical activity 
from baseline to Day 90. The 
objective will be considered 
achieved if there is statistical 
evidence of measured 
improvement in either VR 
group compared to control 
(sham) VR. 
The change from study baseline to 
Day 90 in weekly total steps as 
measured by FitBit is an 
exploratory endpoint. Change in 
steps will also be examined for 
interaction effects on the primary 
outcome.  
There is evidence that physical 
activity can improve 
mood, sleep, and general health, 
yet persons with chronic pain 
may limit their activity because 
of their pain.87 Evidence 
suggests that activity monitors 
encourage increased function 
and correlate with 
improvements in mood among 
patients with chronic pain.88,89 
To assess the efficacy of 
Skills-Based and Distraction 
VR in improving wearable 
measures of sleep from 
baseline to Day 90. The 
objective will be considered 
achieved if there is statistical 
evidence of measured 
improvement in either VR 
group compared to control 
(sham) VR. 
The change from study baseline to 
Day 90 in sleep quantity (total 
minutes asleep as well as “sleep 
efficiency”, see Section 4.6.3 for 
more info) as measured by FitBit 
is an exploratory endpoint. 
Changes in the seconds in sleep 
will also be examined for 
interaction effects on the primary 
outcome. 
There is evidence that physical 
activity can improve 
mood, sleep, and general health, 
yet persons with chronic pain 
may limit their activity because 
of their pain.87  
Previous versions of the skills-
based program used in this 
study showed improvements in 
the sleep subscale of a pain 
interference measure.90  
 
 
Exploratory Subanalysis 
 
 
To assess subgroup analyses 
for the change from baseline 
in PROMIS-PI. An MMRM 
The impact of the following 
variables mentioned in section 
See Section 9.4.7 for details.  

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OBJECTIVES 
ENDPOINTS 
JUSTIFICATION FOR 
ENDPOINTS 
model will be used to test for 
treatment by subgroup 
interactions. 
9.4.7 will be assessed to changes 
in the primary outcome. 
 
 
 
4 
STUDY DESIGN  
 
4.1 
OVERALL DESIGN 
 
This research will be conducted as randomized, double-blind, sham-controlled, 3-arm Phase 2 study. 
Two immersive VR arms use a skills-based VR therapy program, EaseVRx, and a distraction-based VR 
therapy program, EaseVRx-Distraction, while the sham VR arm uses a VR headset to deliver two-
dimensional (non-immersive) content. The primary hypothesis is that participants randomized to either 
skills-based VR therapy or distraction VR therapy will report meaningful improvements in PROs, 
improved biometric outcomes, and reduced opioid use compared to participants receiving a non-
immersive sham VR control intervention.  It is currently planned as a single-site study. However, the self-
administered nature of the intervention and remote data collection would accommodate additional 
sites from the BACPAC consortium if deemed necessary in time.  
 
Review of the VR clinical research literature indicates that the principal source of bias in this research 
has been lack of a control arm that effectively blinds the participant to the treatment allocation. This is 
the first study, to our knowledge, in which participants randomized to the control arm will use a VR 
headset that enables participants to experience the novelty of the hardware but limits their viewing to 
content that is neither immersive nor interactive. The experience of using EaseVRx-Sham is similar to 
watching a large-screen TV. Rather than viewing 360-degree, 3D, interactive content, participants in the 
sham arm can choose among 2D nature experiences accompanied by music selected to be neither 
relaxing nor distracting. EaseVRx- Sham has the same number and duration of experiences as EaseVRx, 
and the functionality of the user interface to access the experiences is the same. Modifications were 
made to the appearance of the user interface in order to remove aspects that were added for 
therapeutic benefit. Thus, the use of this specially designed sham program enables us to isolate the 
effect of VR immersion.35 We also expect that receiving a real VR headset will reduce attrition among 
participants randomized to the control arm. 
 
4.2 
SCIENTIFIC RATIONALE FOR STUDY DESIGN 
The three-arm study design will allow us to determine whether a skills-based VR program that teaches 
exportable skills using CBT, guided meditation, and biofeedback-based breathing exercises outperforms 
conventional, distraction-based VR therapy in reducing cLBP. The 90-day study duration was chosen to 
assess whether VR therapy’s efficacy extends beyond short-term analgesia and reduces the frequency 
and intensity of ongoing LBP through continuous use over a longer period. It also will enable us to 
evaluate longer-term change in other PROs and whether continued use of VR reduces opioid use. The 

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active control group (Sham VR) was designed to minimize bias related to the novelty of the hardware, 
addressing one of the deficits of prior studies. 
 
4.3 
JUSTIFICATION FOR DOSE 
Prior research has shown that daily use of VR for 10 to 15 minutes is effective in managing pain, plus use  
as needed for breakthrough flares of pain. The skills-based VR therapy program, EaseVRx, is a 
standardized 56-day program consisting of scheduled daily virtual experiences. Each VR treatment 
experience lasts between 2-16 minutes, with an average duration of 6 minutes. To minimize the risk of 
cybersickness, participants are instructed to complete one VR treatment experience at a time. Given the 
low-risk nature of VR, they also may repeat experiences such as relaxation, breathing exercises, and 
games at other times during the day, in response to their pain. After the 56-day program is completed, 
participants in this arm are instructed to continue daily use, choosing from among the treatment 
experiences. Participants in the distraction-based VR (EaseVRx-Distraction) and the sham VR also will be 
instructed to use the VR headset at least once daily, choosing from among the experiences available in 
their devices. 
 
4.4 
END OF STUDY DEFINITION 
A participant is considered to have completed the study if he or she has completed the online survey 
questionnaire that is emailed on Day 90, as shown in the Schedule of Activities (SoA), Section 1.3. The 
end of the study is defined as 96 days after the last participant is enrolled or when that participant 
completes the Day 90 survey questionnaire, whichever is sooner.  
 
5 
STUDY POPULATION 
 
5.1 
INCLUSION CRITERIA 
In order to be eligible to participate in this study, an individual must meet all of the following criteria: 
 
1. Able to provide consent to participate in research 
2. Stated willingness to comply with all study procedures and availability for the duration of the 
study  
3. Male or female, age 13 or older 
4. An ongoing low back-pain problem that has persisted at least 3 months and has resulted in pain 
on at least half the days in the past 6 months. 
5. Ability to comprehend spoken and written English 
6. Owns a compatible android or iOS smartphone, or personal laptop or desktop computer 
(excluding tablets) to complete surveys and has access to email. 
 

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5.2 
EXCLUSION CRITERIA 
An individual who meets any of the following criteria will be excluded from participation in this study: 
1. Presents with a condition that interferes with VR usage, including history of seizure, facial injury 
precluding safe placement of headset, significant visual or hearing impairment that impacts 
ability to see the VR images or follow audio instructions  
2. Are being recommended for long-term hospitalization that would require more than three-week 
stay in the hospital  
3. Received surgical procedure within the previous 8 weeks  
4. Surgery is planned within the next 3 months  
5. Is currently using a spinal cord stimulator 
6. Has LBP attributable to a recognizable, specific pathology, including spinal infection, cancer, 
fracture, or inflammatory spondylopathies, consistent with the NIH Task force on Research 
Standards for cLBP 
7. Previously participated in a VR clinical trial 
Women who are currently pregnant or planning to become pregnant will not be excluded from the 
study  
5.3 
LIFESTYLE CONSIDERATIONS 
NA 
 
5.4 
SCREEN FAILURES 
All aspects of this study are conducted remotely, including the participants’ use of a VR therapy headset 
and FitBit watch at home and collection of all PROs via survey questionnaires administered 
electronically. In addition, the VR headset has independent value. To ascertain their willingness and 
ability to respond to survey questionnaires delivered by email, potential participants are required to 
respond to a daily electronic, one-item, “Pain Diary” question and complete the baseline survey 
questionnaires over the course of a “Screening Week,” following informed consent but prior to 
randomization. A screen failure is defined as a participant who completes fewer than 86 items on the 
large survey on the 4th day of the screener week as well less than 5 daily “pain diary questions. 
Participants are required to complete this by the 7th day of the screener week or within 48hrs of being 
sent a reminder email to complete the survey. Participants will be sent a manual reminder email if they 
complete less than 80% of the large survey on the 4th day of screener week as that patient population 
would not get reminder otherwise from the REDCap system. Age, race, and Hispanic ethnicity are some 
of the information that will be collected for all participants even if they fail to complete the Screening 
Week questionnaires. Individuals who inform investigators during the Screening Week that they are no 
longer able or willing to participate in the study for any reason or who are discovered to meet any of the 
exclusion criteria will be recorded. Individuals who satisfactorily complete the Pain Diary and baseline 
survey questionnaires will be enrolled and randomized.   
 
5.5 
STRATEGIES FOR RECRUITMENT AND RETENTION  
 
The target sample size is 360. We expect a representative sample of the chronic low back pain patient 
population seen at Cedars-Sinai. Approximately 58% are female and 42% male. For the first half of the 

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study, we anticipated patients who identify as white to make up about 76% of the study population, 
with 12% black or African American, 5% Asian, and 6% who identify as multiracial. Approximately 11% 
were expected to be Hispanic or Latino. For the second half of the project, per supplementary funding to 
improve study diversity to better reflect the greater Los Angeles population (see Section 11), we aim to 
recruit a second-half cohort to be 35% non-Hispanic white, 17% non-Hispanic black, and 40% Hispanic. 
We expect to randomize 10 participants per month over 36 months.  
Prospective participants will be referred by physicians at the designated clinical sites or identified using 
the Deep 6 AI® cohort building software, which uses natural language processing to search the Cedars-
Sinai EHR for patients who meet the study’s inclusion and exclusion criteria. We anticipate screening 800 
potential participants in order to randomize 360. Recruitment of women is not expected to be a 
problem, because patients seeking care for cLBP are disproportionately female. Women who are 
pregnant or planning to become pregnant are not excluded from participating. Race and ethnicity of 
enrolled participants will be tracked monthly. If the proportion of minority participants appears to be 
lagging, the number contacted will be increased.  
 
Eligible potential participants will be sent an IRB- approved recruitment letter explaining the study via 
email. For individuals identified via cohort builders who have seen a physician partnered with the study 
staff, a personalized letter bearing their treating physician’s voice and signature will be used; all other 
cohort builder identified individuals will be sent a letter from the primary investigator. An informational 
study brochure will also be attached. The recipient may opt-out of further contact by replying to the 
email.  
 
Research coordinators will monitor participant compliance with the survey questionnaires using an 
automated dashboard. Participants will be encouraged to remain in the study and complete the 
questionnaires using a combination of email reminders, telephone calls, and/or SMS text messages. 
from research coordinators. Study coordinators will contact the participant following non-
completion of a survey if >1 week has elapsed since the initial survey send date.  Technical 
support will be available throughout the study.  
 
Participants will be eligible for up to $225 in Amazon gift card codes throughout the study after 
randomization. After completing 80% of the first month of surveys, participants will be sent a $25 
Amazon gift card code. After completing 75% of the second month of surveys, participants will be sent 
another $25 Amazon gift card code. Once the participant completes 80% of the surveys in the 3rd 
month and returns the equipment, they will be sent a $175 Amazon gift card code along with 
recommendation for VR equipment that could be purchased after the end of the study. The $175 
Amazon code compensation will not be released until the audiovisual headset and Fitbit device has been 
returned.  
 
Participants will be emailed recommendations for hardware and software that can be used after the 
study once the equipment has been returned in the email with the Amazon codes.  
 
A detailed description of the recruitment and retention process is in section 5.1 and 5.2 of the MOOP. 
 
6 
STUDY INTERVENTION 
 
6.1 
STUDY INTERVENTION(S) ADMINISTRATION 
 

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6.1.1 STUDY INTERVENTION DESCRIPTION 
The two active interventions evaluated in this study are 360-degree, 3-D therapeutic visualization 
programs (EaseVRx and EaseVRx-Distration) delivered via a commercially available VR headset. The 
control intervention consists of 2-D visualizations delivered by the same VR headset. The three software 
programs were developed by AppliedVR. The EaseVRx programs are not currently regulated by the FDA. 
In September 2019, AppliedVR was awarded two grants by NIDA to conduct proof-of-concept studies to 
evaluate EaseVRx and EaseVRx-Distraction as opioid-sparing tools for acute and chronic pain. The results 
of these studies will inform the company’s regulatory pathway with the FDA. Following are descriptions 
of the three programs: 
Skills-Based VR: EaseVRx 
EaseVRx was developed by AppliedVR in partnership with pain psychologist Beth Darnall, PhD, Associate 
Professor of Anesthesiology, Perioperative and Pain Medicine at Stanford University and an NIH- and 
PCORI-funded investigator in the use of VR for pain management. EaseVRx incorporates the evidence-
based principles of CBT, mindful meditation, and physiologic biofeedback therapy using embedded 
biometric sensors. It combines psychoeducation, pain education, breathing training, relaxation 
exercises, and executive functioning games to provide a mind-body approach toward living better with 
chronic pain. The standardized, prescriptive, and reproducible 56-day program delivers a combination of 
skills training and CBT-related treatments through scheduled daily virtual experiences. The participants 
are allowed to complete as many sessions as they would like. In addition to the prescribed schedule of 
content the participant will have access to the full library of content. Each VR experience lasts between 
2-16 minutes, with an average duration of 6 minutes. The VR treatment modules are designed to 
minimize triggers of emotional distress or cybersickness. There are 5 types of modules:  
 
● Interoceptive: These modules are designed to help the user understand and perceive what is 
happening inside the body. They provide a biofeedback-like platform in which the changes in the 
observed environment reflect a progressively enhanced state of relaxation. 
● Education: Help the user understand why the VR exercises are relevant to their pain, as well as 
teaching specific topics often used in pain psychology, including the neurobiology of pain, the 
role of mood and stress in pain, pain catastrophizing, activity pacing and setting goals. The goal 
is for the user to create self-management steps and a toolkit of strategies they can use to 
manage their response to pain. 
● 360-degree videos: High-quality 360 videos with voiceovers, music, and sound effects that are 
designed to maximize relaxation and engagement of users. 
● Game modules: Games are designed to maximize distraction and engagement, increasing the 
cognitive load on patients, and decreasing their perception of pain. 
● Dynamic breathing: These modules are based on evidence-based biofeedback training designed 
to enhance awareness of one’s physiological response to pain and to self-regulate that 
response. In a virtual world, the user experiences a gamified biofeedback session in which they 
are introduced to awareness of their breath via visualization in the form of air bubbles. In 
multiple sessions, the user receives increasingly challenging tasks to practice diaphragmatic 
breathing while interacting with the virtual environment. The user is also asked to pace their 
breath according to an expanding and contracting ring in the environment to slow the breath 
and create physiological changes associated with relaxation. The user’s exhale is measured by 
the microphone embedded in the headset, offering biodata-enabled immersive therapeutics. 
 
Distraction-Based VR: EaseVRx-Distraction 

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EaseVRx-Distraction has the same number of experiences, the same approximate duration of 
experiences, and the identical user interface as EaseVRx, with a linear prescribed sequence of 
experiences. The key difference is that instead of offering a variety of VR experiences including 
education, games, and breath biofeedback, EaseVRx Distraction only includes 360-degree videos - which 
are also present in EaseVRx. This is intended to remove the effect of education and skills-based training, 
while preserving the immersive experience of 360- degree VR. 
 
Sham VR: EaseVRx-Sham 
EaseVRx Sham software includes 2D nature footage accompanied by neutral music that is selected to be 
neither relaxing nor distracting, rather than 360-degree, 3D, interactive content specially selected for 
efficacy. The experience of using EaseVRx-Sham is similar to watching a large-screen TV, but it is not 
interactive or immersive. EaseVRx Sham has the same number and duration of experiences as EaseVRx, 
and the functionality of the user interface used to access the experiences is the same. Modifications 
were made to the appearance of the user interface in order to remove aspects that were added for 
therapeutic benefit. 
The study intervention will be delivered using a commercially available VR headset, the PICO G2 4K 
(https://www.pico-interactive.com/us/G2_4K.html). The headset battery requires recharging after 
approximately 2.5 hours of use.   
AppliedVR has created videos to help participants understand how to use the headset and cover 
trouble-shooting issues with the headset and software. The Cedars-Sinai study team also will provide 
technical support.  
6.1.2 DOSING AND ADMINISTRATION 
All participants are instructed to use the VR program at least once a day and as needed throughout the 
first eight weeks. Thereafter, the participant can use the program as needed.  Section 4.3 provides the 
justification of dose.  
 
6.2 
PREPARATION/HANDLING/STORAGE/ACCOUNTABILITY 
 
6.2.1 ACQUISITION AND ACCOUNTABILITY 
The PICO VR headsets loaded with the EaseVRx software programs will be provided by AppliedVR. The 
devices will be managed by the research team at Cedars-Sinai Medical Center.  
 
6.2.2 FORMULATION, APPEARANCE, PACKAGING, AND LABELING 
N/A 
 
6.2.3 PRODUCT STORAGE AND STABILITY 
The PICO VR headsets will remain in the boxes supplied by AppliedVR until they are shipped to 
participants.  
 
6.2.4 PREPARATION 

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Prior to shipping the VR headset to a study participant, the headset battery will be checked to make sure 
it is fully charged. Any headsets that are handled by staff will be sanitized by cleaning the fabric surfaces 
using Virex, the plastic housing using Sani-Wipes, and the glass lenses using alcohol-based lens cleaner. 
 
6.3 
MEASURES TO MINIMIZE BIAS: RANDOMIZATION AND BLINDING  
We will allocate study participants using a random number generator to assign blocks of 3, 6, 9, or 12 to 
ensure there is an equal distribution in the EaseVRx skills-based group vs. the EaseVRx-Distraction group 
vs. the EaseVRx-Sham group. Participants, their clinical providers, and study statisticians will be blinded 
to the study arm. The groups will be labeled as A, B or C at random. A clinical research coordinator will 
ship the headset containing the assigned program to the participant and enter the group label into the 
log of enrolled participants. Datasets will be provided to the statistician using these group labels. The 
research coordinator who maintains the list of randomization assignments will not call participants on 
the telephone. Because the intervention is conducted in participants’ homes and the data are collected 
remotely, the participants will not encounter each other and thus will be less likely to guess their study 
arm assignment. We anticipate there will be no circumstances during the study that require unblinding 
of an individual participant or a whole group because we do not expect any related SAEs to occur with 
this low risk intervention.  
We have restructured the block randomization module within REDCap with stratification based on the 4 
sites of recruitment (1 – pain clinic, 2 spine clinic, 3 – rheumatology clinic, 4 – Deep6). Randomization 
will be performed on a 1:1:1 basis across the 3 treatment groups and stratified across the 4 treatment 
sites with random block sizes (3, 6, 9, or 12). Allocation tables will be generated using STATA v16 
software and uploaded into REDcap for patient allocation. 
 
6.4 
STUDY INTERVENTION COMPLIANCE   
Data collection will be monitored daily by the study team. Participants initially will be sent a reminder 
email when they have completed no survey questionnaires 2 days after the survey is distributed. If the 
participant does not respond to the email  two additional 48-hr reminders will be sent. S team member 
will call the participant on the next business day If no data are received. They will be asked why they 
have missed all three reminders and encouraged to continue to complete surveys as they are sent. If the 
participant does not complete any surveys in the nexty 72hrs they will be sent a final email with a link to 
last survey. The participant will not be contacted again until the end of study to request a return of 
equipment.  
6.5 
CONCOMITANT THERAPY  
Participants in the study maybe receiving ongoing treatment for their chronic pain, as listed in the table 
below.  
 
Category  
Specific therapy 
Procedures 
Injections (steroid, facet joints, radio frequency 
ablations, sacroiliac joint injections, Epidural 
injections, inter laminar or transforaminal) 
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Blocks (facet blocks, medial branch blocks, trigger 
point injections) 
Acupuncture 
 
Physical Therapy 
Physical Therapy and Aqua therapy 
Chiropractic care 
 
Psychotherapy 
CBT 
Biofeedback 
Screening and management of 
depression/anxiety 
 
Medications 
Benzodiazepine tapering program 
Opioid maintenance and tapering program 
Tylenol 
Muscle Relaxants 
Narcotics 
Gabapentin/pregabalin 
NSAIDS  
Cannabinoids 
 
 
6.5.1 RESCUE MEDICINE 
NA 
 
7 
STUDY INTERVENTION DISCONTINUATION AND PARTICIPANT 
DISCONTINUATION/WITHDRAWAL 
 
7.1 
DISCONTINUATION OF STUDY INTERVENTION 
 
We do not anticipate any events that would cause the study intervention to be discontinued. 
 
7.2 
PARTICIPANT DISCONTINUATION/WITHDRAWAL FROM THE STUDY  
Participants are free to withdraw from the study at any time upon request. Participants request to 
withdraw will be asked to clarify whether they wish to discontinue the intervention but still complete 
the periodic survey questionnaires. In this case, the participant would not be considered withdrawn. 
An investigator may withdraw a participant who develops any of the exclusions criteria in section 5. The 
reason for participant discontinuation or withdrawal from the study will be recorded.   
Subjects who signed the informed consent form, were randomized and received the study intervention, 
and subsequently withdraw, or are withdrawn or discontinued from the study without engaging with 
the VR intervention will be replaced. Participants are considered to have engaged with the VR 
intervention if there is any self-reported VR usage in survey questionnaires or if any metadata are 
recorded in a participant’s headset during their possession of the VR headset. 
 

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7.3 
LOST TO FOLLOW-UP   
A participant will be considered lost to follow-up if he or she fails to schedule an onboarding phone call 
within 30 days of device delivery or if he or she fails to complete the initial SSQ+ survey within 30 days of 
onboarding completion. For participants who complete the initial SSQ+ survey, fail to complete >80% of 
future surveys, and become unreachable by phone or email, the participant will be considered lost to 
follow-up 6 days following the email date of the participant’s Day 90 survey. 
 
If a participant fails to complete the Day 90 survey within six days, the following actions will be taken: 
 
• 
The research coordinator will attempt to contact the participant and counsel them on the 
importance of completing surveys and returning the equipment to be eligible for the gift card.   
• 
Before a participant is deemed lost to follow-up, the investigator or designee will make every 
effort to regain contact with the participant (where possible, 3 telephone calls and, if necessary, 
a certified letter to the participant’s last known mailing address or local equivalent methods). 
Contact attempts will be documented in the participant’s study record.  
• 
Should the participant continue to be unreachable, he or she will be considered to have 
withdrawn from the study with a primary reason of lost to follow-up. 
 
8 
STUDY ASSESSMENTS AND PROCEDURES 
 
8.1 
EFFICACY ASSESSMENTS    
We will capture all survey data via REDCap. REDCap is a secure web application for building and 
managing online surveys and databases. While REDCap can be used to collect virtually any type of data 
(including 21 CFR Part 11, FISMA, and HIPAA-compliant environments), it is specifically geared to 
support online or offline data capture for research studies and operations. If subjects do not complete 
the surveys, they will be sent a reminder prompt.  
Primary Outcome  
The change from study baseline to Day 30 in pain interference as measured by the 8-item PROMIS Pain 
Interference scale is the primary endpoint. The scale is rendered using a T-statistic, where a score of 50 
represents the population mean and 10 points is a standard deviation (SD). Scoring of the instrument 
will occur in a SAS/STATA environment in which study statisticians are blinded to the study arm. 
Secondary Outcomes 
The change from study baseline to day 90 in pain interference as measured by the 8-item PROMIS PI 
scale is a secondary endpoint.  The scale is rendered using a T-statistic, where a score of 50 represents 
the population mean and 10 points is a standard deviation (SD). Scoring of the instrument will occur in a 
SAS/STATA environment in which study statisticians are blinded to the study arm. 
The change from study baseline to Day 90 in pain catastrophizing as measured by PCS SF-6 is a 
secondary endpoint. The Pain Catastrophizing scale (PCS) short form measures rates of high 
catastrophizing as defined by a score of ≥7. Scoring of the instrument will occur in a SAS/STATA 
environment in which study statisticians are blinded to the study arm.  

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The change from study baseline to Day 90 in anxiety as measured by the 6-item PROMIS Anxiety scale is 
a secondary endpoint. The scale is rendered using a T-statistic, where a score of 50 represents the 
population mean and 10 points is a standard deviation (SD). Scoring of the instrument will occur in a 
SAS/STATA environment in which study statisticians are blinded to the study arm. 
The change from study baseline to day 90 in sleep disturbance as measured by the 6-item PROMIS Sleep 
Disturbance scale is a secondary endpoint. The scale is rendered using a T-statistic, where a score of 50 
represents the population mean and 10 points is a standard deviation (SD). Scoring of the instrument 
will occur in a SAS/STATA environment in which study statisticians are blinded to the study arm. 
The change from study baseline to Day 90 in 7-day average of daily maximum milligrams morphine 
equivalent (MME) is a secondary endpoint. Prescription data will be extracted from the EHR at baseline 
and again at Day 90 and may be supplemented by data from CURES. While daily MME of prescriptions is 
a calculated field in the EHR, calculation of the 7-day average will occur in a SAS/STATA environment in 
which study statisticians are blinded to the study arm. 
 
CURES is the California Controlled Substance Utilization Review and Evaluation System, a database of 
Schedule II, III and IV controlled substance prescriptions dispensed in California. It is administered by the 
California Department of Justice (CA DOJ). We will request prescription data from the CURES database 
for each randomized patient from 90 days before enrollment until 90 days after the completion of the 
study. This will allow us to assess prescription changes that might be made right before or after the 
study ends. The data from CURES  will only be used for research purposes and will comply with all 
requirements of the California Confidentiality of Medical Information Act and the Health Insurance  
Portability and Accountability Act of 1996 (HIPAA), including the HIPAA  regulations in 45 Code of 
Federal Regulations parts 160 and 164. We will randomize the patients between 10/1/2020 to 9/5/2023. 
We will submit all consent forms with the request for data by 9/25/2023. The “CURES Access Period” 
will be designated from 9/1/2023 to 7/1/2024. We will provide CURES with the first name, last name, 
DOB, and copy of consent for every participant that we request information. The CA DOJ will be notified 
upon completion of the study, which is anticipated to be 7/30/2024. Per CURES regulations, the “CURES 
Data Destruction Date” will be 10/30/2029. On that date the dataset from CURES will be deleted and a 
notification will be sent to CURES.  The CA DOJ will be provided with an advance copy of any manuscript 
or presentation that uses the CURES data, as well as a copy of final publications. The CA DOJ also will be 
notified when a team member is added to or removed from the study. 
 
8.2 
SAFETY AND OTHER PROCEDURES    
Safety will be monitored by following up with participants for any adverse events (AE), assessment of 
adherence, monitoring of biometric information, and questionnaires by support staff. 
 
Participant safety - Severe Depression & Substance Use Disorders  
 
Study participants will complete the PROMIS Depression questionnaire at baseline and every two weeks 
throughout the study. Because the surveys are completed electronically, scoring takes place 
immediately. In a study comparing PROMIS Depression scores with the PHQ-9 commonly used to screen 
for depression, a t-score greater than 70 indicates severe depression. The REDCap system will be 
programmed to alert the study team via email if a participant’s score is higher than 70.  A physician 
investigator will contact the participant and conduct a clinical assessment of suicide risk, provide 
education on the importance of a safe treatment plan, direct them to emergency services if indicated, 
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threshold can not be contacted by a physician investigator for a phone assessment, the individual will be 
emailed a list of available resources. 
 
Substance use disorders will be screened using the TAPS 1&2 at baseline and then at week 12. The 
REDCap system has been calibrated to alert the team when the patient achieves a score >2 on the 
combined assessment. The research team will then email the patient a list of available resources.   
 
8.2.1 PROCEDURES  
Virtual Reality Headset data 
Data from the PICO G2 4K device will be aggregated by AppliedVR’s cloud-based software solution that 
implements robust industry standards to maintain secure databases and keep data private. The 
AppliedVR cloud server is a HIPAA compliant platform. The device account that corresponds with each 
device will be created using a clinical trial number that is only linked to the patient via our office list of 
patients enrolled in the study. AppliedVR does not collect personally identifiable information and does 
not collect IP addresses from synced participant devices in our database. Data will be stored and 
indexed in the AppliedVR server database whenever devices upload batches of analytic events, and the 
analytic events are timestamped. The data collected by the device will include time of use, date of use, 
and the module selected. Our database servers are IP firewalled and whitelisted such that they refuse 
any connection from IP addresses not preprogrammed by our team.  
 
Fitbit data 
Data from the Charge 4 device will be aggregated by Fitabase, a fully hosted, cloud-based software 
solution that implements robust industry standards to maintain secure databases and keep data private. 
Accordingly, the Charge 4 account that corresponds with each device will be created using an 
anonymous email address not linked to a real person. Fitabase does not collect personally identifiable 
information and does not collect IP addresses from synced participant devices. Data will be stored and 
indexed in the Fitabase SQL Server database in day total, hour, and minute-by-minute intervals. Our 
database servers are IP firewalled and whitelisted such that they refuse any connection from IP 
addresses not preprogrammed by our team.   
Technical Support 
Patients in all three arms will receive remote technical support from the research team. The idea is that 
issuing devices is usually insufficient to achieve behavior change; supporting those devices with high-
touch yet scalable care is a vital component. 
Patients will be provided with onboarding material as well as emails with a link to our study website. The 
study website was based on experience from previous remote VR therapy clinical trial and feedback 
from patients within it. On the website we will have instructional videos as well an extensive FAQ page. 
The patient will have an onboarding phone call once the device is delivered to their home. During this 
call, patients will be asked if they reviewed the onboarding video that was linked in the device tracking 
information email, and coordinators will answer any remaining questions and guide participants through 
the device or program if necessary. Contact information will be provided for technical support 
throughout the remainder of the participant’s study enrollment. 

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Redcap survey data will also be monitored. We will assign two technical support staff members to 
monitor patients in all three arms. Patients will receive a telephone number and email to contact 
support staff as needed.  
 
VR device metadata will be provided monthly by AppliedVR as CSV files containing timestamped records 
of content accessed at the individual device level. It will provide the amount of time the patient spent 
on the device and the modules that they completed.  
 
   
8.3 
ADVERSE EVENTS AND SERIOUS ADVERSE EVENTS  
 
8.3.1 DEFINITION OF ADVERSE EVENTS (AE) 
An adverse event (AE) is defined as any untoward medical occurrence associated with the use of an 
intervention in humans, whether or not considered intervention-related (21 CFR 312.32 (a)). Short-term 
AEs associated with the study include “cybersickness,”76 a transient form of motion sickness that affects 
up to one in four people upon entering a VR environment. Cybersickness most commonly presents with 
a short-term feeling of dizziness that typically subsides quickly.  There are no anticipated long-term AEs 
from participating in this study. A comprehensive list of all potential cybersickness symptoms can be 
found below:  
• 
Nausea 
• 
Fatigue  
• 
Eyestrain  
• 
Blurred vision  
• 
Difficulty focusing  
• 
Dizziness  
• 
Vertigo (a sensation of spinning dizziness, as though the room or surrounding environment is 
spinning)  
• 
Headache  
• 
Fullness of the head  
• 
Difficulty concentrating  
• 
Postural instability  
In addition, in rare situations, one may have an allergy to the facial interface that generates a rash, 
which typically resolves without any medication in under 24 hours. There is also the possibility of a 
participant experiencing neck pain as a result of using the headset for an extended period of time. 
Participants will be informed of ways to mitigate the possibility of neck pain while using the headset. 
 
8.3.2 DEFINITION OF SERIOUS ADVERSE EVENTS (SAE)  
A serious adverse event (SAE) or suspected adverse reaction is considered "serious" if, in the view of 
either the investigator or sponsor, it results in any of the following outcomes: death, a life-threatening 
adverse event, inpatient hospitalization or prolongation of existing hospitalization, a persistent or 
significant incapacity or substantial disruption of the ability to conduct normal life functions. Important 
medical events that may not result in death, be life-threatening, or require hospitalization may be 
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participant and may require medical or surgical intervention to prevent one of the outcomes listed in 
this definition. We do not expect any serious adverse events with a virtual reality intervention.  
 
8.3.3 CLASSIFICATION OF AN ADVERSE EVENT 
 
8.3.3.1 SEVERITY OF EVENT 
For adverse events (AEs) the following guidelines will be used to describe severity.  
 
• 
Mild – Events require minimal or no treatment and do not interfere with the participant’s daily 
activities.  
• 
Moderate – Events result in a low level of inconvenience or concern with the therapeutic 
measures. Moderate events may cause some interference with functioning. 
• 
Severe – Events interrupt a participant’s usual daily activity and may require systemic drug 
therapy or other treatment. Severe events are usually potentially life-threatening or 
incapacitating.  Of note, the term “severe” does not necessarily equate to “serious”. 
 
Research staff will call the patient if an event is noted in an event assessment that is sent on a weekly 
basis. Nothing more than mild side effects that do not require medical treatment are expected.  
 
8.3.3.2 RELATIONSHIP TO STUDY INTERVENTION 
All adverse events (AEs) must have their relationship to study intervention assessed by the clinician who 
examines and evaluates the participant based on temporal relationship and his/her clinical judgment. 
The degree of certainty about causality will be graded using the categories below. In a clinical trial, the 
study product must always be suspect.  
 
• 
Related – The AE is known to occur with the study intervention, there is a reasonable possibility 
that the study intervention caused the AE, or there is a temporal relationship between the study 
intervention and event. Reasonable possibility means that there is evidence to suggest a causal 
relationship between the study intervention and the AE. 
• 
Not Related – There is not a reasonable possibility that the administration of the study 
intervention caused the event, there is no temporal relationship between the study intervention 
and event onset, or an alternate etiology has been established. 
 
8.3.3.3 EXPECTEDNESS  
Research staff will be responsible for determining whether an adverse event (AE) is expected or 
unexpected.  An AE will be considered unexpected if the nature, severity, or frequency of the event is 
not consistent with the risk information previously described for the study intervention. A detailed 
description of expectedness is provided in DSMP section 1.2.3.  
8.3.4 TIME PERIOD AND FREQUENCY FOR EVENT ASSESSMENT AND FOLLOW-UP 
The occurrence of an adverse event (AE) or serious adverse event (SAE) may come to the attention of 
study personnel during review of weekly event assessments by a study team member as well as on Day 
1. We will employ a general question to allow the patient to provide an event description without bias 
by presupposing the nature of the event, as follows: 

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1) 
During the past 14 days, have you experienced anything uncomfortable, distressing or upsetting 
as a result of using the VR headset?  
a. 
Yes 
b. 
No 
2) 
If Yes please describe what happened. A research staff member will follow-up up with you as 
soon as possible to learn more.  
a. 
[open text] 
 
A designated CRC will review the REDCap dashboard for completed AE assessments on a daily basis 
throughout the work week. Once they find a completed event assessment form, they will follow-up with 
a phone call. The following information be obtained from the patient during the call: onset of potential 
adverse event, event description, when they last used the VR headset, how long they used the headset, 
when they stopped using the headset, severity of the potential AE, outcome of the potential AE (see 
categories, below), time until resolution/stabilization of event, the perceived relationship of the event to 
the study intervention, whether or not the event was expected (Y/N), whether it was serious.  
 
The outcome can be labeled using one of the following categories:  
• 
Recovered, without treatment  
• 
Recovered, with treatment  
• 
Still Present, no treatment  
• 
Still Present, being treated  
• 
Residual effect(s) present-no treatment  
• 
Residual effect(s) present-being treated  
 
Research staff will record all reportable events with start dates occurring any time after informed 
consent is obtained until 7 (for non-serious AEs) or 30 days (for SAEs) after the last day of study 
participation.  Please see section 1.3 in DSMP for instructions on how events will be followed for 
outcome information until resolution or stabilization. 
 
8.3.5 ADVERSE EVENT REPORTING   
 
Cedars-Sinai IRB 
If a mild or moderate event occurs it does not need to be submitted to the Reportable New 
Information (RNI). If the event is an unexpected (not usually associated VR side effects) or 
severe event (requiring treatment), an AE will be submitted to the IRB as soon as possible but 
within at least 10 working days.  
 
DSMB 
All AEs, regardless of their severity, relatedness or expectedness, are reported in aggregate as 
part of the routine Data and Safety Monitoring Report to the NIAMS and DSMB, twice per year.   
 
A detailed description of procedure for collecting event is in section 1.2.3 of the DSMP. 
 
8.3.6 SERIOUS ADVERSE EVENT REPORTING  
SAEs will be submitted to the Cedars-Sinai IRB via RNI as soon as possible by study coordinators, but no 
later than 10 business days from the Principal Investigator’s or study team’s awareness of the event, 

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incident, information or outcome. In addition, SAEs will be reported to the DSMB and NIAMS via the 
NIAMS executive secretary within 48 hours of becoming aware of the event.  
 
8.3.7 REPORTING EVENTS TO PARTICIPANTS  
N/A  
 
8.3.8 EVENTS OF SPECIAL INTEREST  
N/A 
 
8.3.9 REPORTING OF PREGNANCY  
N/A 
 
8.4 
UNANTICIPATED PROBLEMS 
 
8.4.1 DEFINITION OF UNANTICIPATED PROBLEMS (UP) 
The Office for Human Research Protections (OHRP) considers unanticipated problems involving risks to 
participants or others to include, in general, any incident, experience, or outcome that meets all of the 
following criteria: 
 
• 
Unexpected in terms of nature, severity, or frequency given (a) the research procedures that are 
described in the protocol-related documents, such as the Institutional Review Board (IRB)-
approved research protocol and informed consent document; and (b) the characteristics of the 
participant population being studied; 
• 
Related or possibly related to participation in the research (“possibly related” means there is a 
reasonable possibility that the incident, experience, or outcome may have been caused by the 
procedures involved in the research); and 
• 
Suggests that the research places participants or others at a greater risk of harm (including 
physical, psychological, economic, or social harm) than was previously known or recognized. 
 
This definition could include an unanticipated adverse device effect, any serious adverse effect on 
health or safety or any life-threatening problem or death caused by, or associated with, a device, if that 
effect, problem, or death was not previously identified in nature, severity, or degree of incidence in the 
investigational plan or application (including a supplementary plan or application), or any other 
unanticipated serious problem associated with a device that relates to the rights, safety, or welfare of 
subjects (21 CFR 812.3(s)). 
 
8.4.2  UNANTICIPATED PROBLEM REPORTING  
Study coordinators will report unanticipated problems (UPs) to the Cedars-Sinai IRB as a RNI submission 
as soon as possible by study coordinators, but no later than 10 business days from the Principal 
Investigator’s or study team’s awareness of the event, incident, information or outcome. UPs include 
SAEs and AEs, which are both unexpected and possibly related to the research as well as SAEs and AEs 
that meet the definition of a Research-Related Subject Injury (RRSI) – a medical condition that is caused 
by and/or directly related to the research study (i.e., the condition would not have existed “but for” the 
subject’s participation in the study), and requires diagnosis or treatment.    
The UP report will include the following information: 

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• 
Protocol identifying information: protocol title and number, PI’s name, and the IRB project 
number; 
• 
A detailed description of the event, incident, experience, or outcome;  
• 
An explanation of the basis for determining that the event, incident, experience, or outcome 
represents an UP;  
• 
A description of any changes to the protocol or other corrective actions that have been taken or 
are proposed in response to the UP. 
 
UPs will also be reported to NIAMS and the DSMB via the NIAMS executive secretary within 48 hours of 
the PI becoming aware of the event. 
 
8.4.3 REPORTING UNANTICIPATED PROBLEMS TO PARTICIPANTS  
N/A 
 
9 
STATISTICAL CONSIDERATIONS  
 
9.1 
STATISTICAL HYPOTHESES 
 
 
• 
Primary Efficacy Endpoint(s):   
 
Primary Outcome: Pain interference over time as measured by PROMIS-Pain Interference 8a (T-Scored, 
Continuous). 
 
Hypothesis: Immersive VR (Skills-based VR or Distraction VR) will lead to a greater improvement in pain 
interference than Sham VR over 30-day period. 
 
Comparisons: Superiority for both of the following (1) Distraction VR therapy vs. sham VR therapy; (2) 
skills-based VR therapy vs. sham VR therapy.  
 
Additional comparison: If there is a statistically significant difference in Skills based VR vs Sham VR, then 
a third test will be completed (3) Skills-based VR therapy vs Distraction VR therapy. 
 
 
• 
Secondary Efficacy Endpoint(s): 
 
Secondary Outcome: Pain interference over time as measured by PROMIS-Pain Interference 8a (T-
Scored, Continuous). 
 
Hypothesis: Immersive VR (Skills-based VR or Distraction VR) will lead to a greater improvement in pain 
interference than Sham VR at Day 60 and Day 90.  
 
Comparisons: Superiority for both of the following (1) Distraction VR therapy vs. sham VR therapy; (2) 
skills-based VR therapy vs. sham VR therapy.  
 

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Additional comparison: If there is a statistically significant difference in Skills based VR vs Sham VR then 
a third test will be completed (3) Skills-based VR therapy vs Distraction VR therapy. 
 
Secondary Outcome: Pain catastrophizing over time as measured by Pain Catastrophizing scale (PCS) 
short form. 
Hypothesis: Skills-based VR will lead to a greater improvement in Pain catastrophizing than distraction-
based VR or Sham VR.  
Comparisons: Superiority for both of the following (1) Distraction VR therapy vs. sham VR therapy; (2) 
skills-based VR therapy vs. sham VR therapy, if there is a statistically significant difference in Skills based 
VR vs Sham VR then a third test will be completed (3) Skills-based VR therapy vs Distraction VR therapy 
Secondary Outcome:  Anxiety over time as measured by PROMIS Anxiety.  
Hypothesis: Skills-based VR will lead to a greater improvement in PROMIS Anxiety than distraction based 
VR or Sham VR.  
Comparisons: Superiority for both of the following (1) Distraction VR therapy vs. sham VR therapy; (2) 
skills-based VR therapy vs. sham VR therapy, if there is a statistically significant difference in Skills based 
VR vs Sham VR then a third test will be completed (3) Skills-based VR therapy vs Distraction VR therapy 
 
Secondary Outcome:  Quality of sleep over time as measured by PROMIS Sleep Disturbance.  
Hypothesis: Skills-based VR will lead to a greater improvement in sleep quality than distraction based VR 
or Sham VR.  
Comparisons: Superiority for both of the following (1) Distraction VR therapy vs. sham VR therapy; (2) 
skills-based VR therapy vs. sham VR therapy, if there is a statistically significant difference in Skills based 
VR vs Sham VR then a third test will be completed (3) Skills-based VR therapy vs Distraction VR therapy 
Secondary Outcome: Comparing the change from study baseline to Day 90 in weekly MME of prescribed 
medication.  
Question: Which intervention is more effective in reducing opioid prescriptions of Morphine Milligram 
Equivalents (MME) or greater? 
Hypothesis: We believe that Skills-based VR will have a statistically significant decrease in opioid use in 
comparison to distraction-based VR and Sham VR. 
Comparisons: Superiority for both of the following (1) Distraction VR therapy vs. sham VR therapy; (2) 
skills-based VR therapy vs. sham VR therapy, if there is a statistically significant difference in Skills based 
VR vs Sham VR then a third test will be completed (3) Skills-based VR therapy vs Distraction VR therapy 
 
9.2 
SAMPLE SIZE DETERMINATION 
 
Sample Size calculations 

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The primary goal of this aim is to test the efficacy of immersive VR in improving perceived pain. The trial 
will be a success if there is statistical evidence that either immersive VR group is better than control or 
sham VR. Preliminary studies showed that the PROMIS pain interference scale has a SD of 10. Assuming 
that the SD at baseline (SD0) and at 30 days (SD1) are similar and equal to 10 for this population, the 
variance for the difference in PROMIS from baseline to 30 days after intervention is Vardiff= SD02 +SD12 ˗ 2 
ρ SD0 SD1, where ρ is the correlation coefficient between measurements at baseline and 30 days. A 
conservative estimate of this variance is achieved when ρ = 0. Therefore, the estimate SDdiff = (102 + 
102)0.5 = 14.14. Let mc, mv1, and mv2 be the mean change in PROMIS score from baseline to 30 days for 
the control, VR1, and VR2 groups, respectively.  
 
We estimate power by simulating 10000 trial replicates and testing the null hypothesis that Ho: mc = mv1 
= mv2 versus the alternative hypothesis that H1: mc ≠ mv1 or mc ≠ mv2. To maintain the familywise error 
rate at 0.05, a two-sample t-test is used to compare the control arm to each VR arm and the test is 
declared statistically significant if the p-value of the two-sided test is less than 0.025. Under the 
alternative hypothesis that | mc - mv1| = | mc – mv2| = 5, data from 120 patients in each of the three 
arms achieve 83% power to detect a clinically meaningful effect 5 units in the PROMIS score. The actual 
type I error rate is 0.049. For the secondary outcome of comparison between the two VR arms, we test 
the null hypothesis that Ho: mv1 = mv2 versus the alternative hypothesis that H1: mv1 ≠ mv2 at the two-
sided 0.05 level of significance if there is statistical evidence that both VR arms are better than control. 
Using the same assumptions as above and simulating 10000 trial replicates, then if both VR arms are 
better than the control arm, we can achieve 71.4% power to detect 5 units in PROMIS score between 
the two VR arms. This power was derived under the alternative hypothesis | mc - mv1|= 5 and | mv1 – 
mv2| = 5. The actual type I error rate for this conditional test is 0.02. 
 
Power Estimation 
We estimate power to assess the effect of VR type on treatment response using logistic 
regression, accounting for all possible confounding factors as described in Aim 1. The outcome variable 
in treatment response (binary) and the predictor of interest is VR type, traditional versus enhanced. 
Table 1 gives the minimum odds ratio that can be detected with 80% power with the two-sided 0.05 
level of significance as a function of baseline probability of positive response when a patient is treated 
with traditional VR and R2, the proportion of variability in the predictor of interest (VR type) that is 
explained by all relevant baseline covariates in the model using data from 120 patients in the traditional 
VR arm and 120 in the enhanced VR arm. For example, data from 240 patients achieve 80% power to 
detect an odds ratio of 2.19 if the probability of positive response when a patient is treated with 
traditional VR is 0.3 and 10% of the variability in VR type is explained by all other baseline covariates in 
the model. These odds ratios vary between 2.01 and 2.8 and are clinically meaningful. Therefore, we 
have enough power to test statistical significance of predictors of interest in the multivariable logistic 
regression model. 
 
Table 1.  Minimum detectable odds ratio as a function of the proportion of variability in VR type 
variable that is explained by all other relevant covariates in the model and the baseline probability of 
positive treatment response. 
Baseline probability 
R2 
0.0 
0.1 
0.2 
0.4 
0.2 
2.26 
2.36 
2.48 
2.82 
0.3 
2.11 
2.19 
2.30 
2.61 
0.5 
2.01 
2.18 
2.30 
2.64 

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9.3 
POPULATIONS FOR ANALYSES   
All efficacy and safety data summaries and analyses will be performed by study arm using an Intent-to-
Treat (ITT) population defined as all randomized patients.  
 
The number of patients identified as candidates will be reported, as will the number screened (i.e. 
consented). The number and percentage of patients randomized, patient population (ITT), and treatment 
status (completed, discontinued/withdrew) will be summarized both by treatment group and overall. 
Reasons for discontinuation/withdrawal will be presented. 
 
An exploratory, per protocol (PP) analysis will focus on patients who use the assigned intervention on at 
least 50% of days during the first 30-day period. Usage meta-data on the headsets will facilitate sample 
definition in this population. If headset meta-data is not available, we will rely on weekly self-report usage 
surveys.   
 
9.4 
STATISTICAL ANALYSES 
 
 
9.4.1 GENERAL APPROACH 
All statistical analyses will be performed jointly by the Cedars-Sinai Biostatistics Core and the Cedars-Sinai 
Center for Outcomes Research and Education (CS_CORE) using SAS® software version 9.3 or higher (SAS 
Institute, Cary, NC, USA), R pack3.5.0 (R Foundation for Statistical Computing, Vienna, Austria)or Stata 
software version 14 or higher (StataCorp LLC, College Station, TX, USA).  
Continuous variables will be summarized using descriptive statistics (N, mean, standard deviation, 
minimum, median, and maximum). Categorical variables will be summarized using the number and 
percentage of patients in each category. Data will be summarized with respect to patient demographic 
and baseline characteristics both across the study and by study-arm. The efficacy endpoints, safety 
assessments, and other outcome results for each treatment group will be summarized descriptively unless 
otherwise indicated. In addition, statistical model estimates of least squares means, treatment 
differences, p-values and 95% confidence intervals will also be provided where relevant. The fit of linear 
models will be assessed using residual plots and/or other diagnostic plots as appropriate. The fit of logistic 
models will be assessed using Hosmer-Lemeshow goodness-of-fit and/or receiver operating characteristic 
(ROC) curves as appropriate. All statistical tests will be 2-sided and performed at the 0.05 level of 
significance unless stated otherwise. Baseline is defined as the value at the screening week (Day -8 to Day 
-2) for all parameters, unless specified otherwise.  
 
9.4.2 ANALYSIS OF THE PRIMARY EFFICACY ENDPOINT(S) 
The goal of this analysis is to test the effectiveness of immersive VR in improving measures of pain 
interference. The trial will be a success if there is statistical evidence that either immersive VR group is 
better than sham VR.  
The primary efficacy endpoint is the change from study baseline to Day 30 in pain interference as 
measured by PROMIS-PI t-score. The primary analysis will compare each treatment group separately to 
the control group using a linear mixed model repeated measures (MMRM) analysis.1 The repeated 
measures are the change from baseline PROMIS-PI t-score obtained at Days 7, 15, and 21, respectively. 
The model will include fixed categorical effects for treatment, week, treatment by week interaction, and 
the baseline PROMIS-PI t-score as a continuous covariate. We will employ the Stata xtmixed command 

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with restricted maximum likelihood estimation (REML) and an unstructured within-patient covariance 
structure for this model. We will evaluate the assumptions of the model, including normality, using 
residual and other diagnostic plots of model fit.  
From this model, we will estimate least squares means, standard errors, treatment differences in least 
squares means, and 95% confidence intervals for each time period. Primary inference will be based on the 
treatment comparison of least squares means for Day 30, and a p-value will be presented for this time 
period only. The null hypothesis is that the mean difference in the primary endpoint between the 
treatment groups and the sham control group is zero, versus the alternative hypothesis that these 
differences are not zero. The hypotheses can be expressed as follows: 
H0a: μSB - μcontrol = 0 versus H1a: μSB - μcontrol ≠ 0 
H0b: μD - μcontrol = 0 versus H1b: μD - μcontrol ≠ 0 
Where μSB refers to the mean change from baseline to Day 30 in Promis-PI t-score in the Skills-based VR 
treatment group, μcontrol refers to the mean change from baseline to Visit Day 30  in Promis-PI t-score 
in the sham treatment group, and μD refers to the mean change from baseline to Day 30 in Promis-PI t-
score in the Distraction VR treatment group. The test will be performed using the final MMRM model with 
a two-sided significance level of 5%. Estimated least squares means for change from baseline and the 
observed absolute values (± SE) by treatment group will be plotted over time. 
 
9.4.3 ANALYSIS OF THE SECONDARY ENDPOINT(S) 
PROMIS-Pain Interference 
The change from study baseline to Day 60 and 90 in pain interference as measured by PROMIS-Pain 
Interference is a secondary endpoint. This analysis will compare the treatment groups, separately, to the 
control group using a MMRM analysis. The repeated measures are the change from baseline PROMIS-Pain 
Interference score obtained for Day 60 and 90, respectively. The model will include fixed categorical 
effects for treatment, week, treatment by week interaction, and the baseline PROMIS-Pain Interference 
score as a continuous covariate. We will employ the Stata xtmixed command with REML and an 
unstructured within-patient covariance structure for this model. We will evaluate the assumptions of the 
model, including normality, using residual and other diagnostic plots of model fit.  
From this model, we will estimate least squares means, standard errors, treatment differences in least 
squares means, and 95% confidence intervals for each time point. Primary inference will be based on the 
treatment comparison of least squares means for Day 90, and a p-value will be presented for this time 
period only. The null hypothesis is that the mean difference in the primary endpoint between the 
experimental arms and the sham arm is zero, versus the alternative hypothesis that this difference is not 
zero.  
PROMIS-Sleep Disturbance  
The change from study baseline to Day 90 in sleep disturbance as measured by PROMIS-Sleep Disturbance 
is a secondary endpoint. This analysis will compare the treatment groups, separately, to the control group 
using a MMRM analysis. The repeated measures are the change from baseline PROMIS-Sleep Disturbance 
score obtained at Days 15, 30, 60, and 90, respectively. The model will include fixed categorical effects for 
treatment, week, treatment by week interaction, and the baseline PROMIS-Sleep Disturbance score as a 
continuous covariate. We will employ the Stata xtmixed command with REML and an unstructured within-
patient covariance structure for this model. We will evaluate the assumptions of this model, including 
normality, using residual and other diagnostic plots of model fit.  

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From this model, we will estimate least squares means, standard errors, treatment differences in least 
squares means, and 95% confidence intervals for each time point. Primary inference will be based on the 
treatment comparison of least squares means for Day 90 from this model, and a p-value will be presented 
for this time period only. The null hypothesis is that the mean difference in the primary endpoint between 
the experimental arms and the sham arm is zero, versus the alternative hypothesis that this difference is 
not zero.  
PROMIS-Anxiety 
The analysis approach for this endpoint mirrors the above description for PROMIS-Anxiety 
PCS SF-6 
The change from study baseline to Day 90 in pain catastrophizing as measured by PCS SF-6 is a secondary 
endpoint. This analysis will compare the treatment groups, separately, to the control group using a 
MMRM analysis. The repeated measures are the change from baseline PCS SF-6 score obtained for Day 
15, 30, 60, and 90, respectively. The model will include fixed categorical effects for treatment, week, 
treatment by week interaction, and the baseline PCS SF-6 score as a continuous covariate. We will employ 
the Stata xtmixed command with REML and an unstructured within-patient covariance structure for this 
model. We will evaluate the assumptions of this model, including normality, using residual and other 
diagnostic plots of model fit.  
From this model, we will estimate least squares means, standard errors, treatment differences in least 
squares means, and 95% confidence intervals for each time point. Primary inference will be based on the 
treatment comparison of least squares means for Day 90 from this model, and a p-value will be presented 
for this time period only. The null hypothesis is that the mean difference in the primary endpoint between 
the experimental arms and the sham arm is zero, versus the alternative hypothesis that this difference is 
not zero. 
The change from study baseline to Day 90 in weekly MME of prescribed medication is a secondary 
endpoint. Descriptive summary statistics will be presented for weekly MME of prescribed medication at 
two timepoints: baseline and Day 90. Analysis of this endpoint will compare the difference in weekly 
MME of prescribed medication between the treatment groups and control group at baseline and Day 90 
using analysis of covariance (ANCOVA), adjusting for baseline MME. We will assess the assumptions 
underpinning the ANCOVA model graphically and will undertake appropriate transformation of the 
weekly average MME outcome as deemed appropriate. If no suitable transformations can be found, 
bootstrapped confidence intervals for the between-group differences in weekly MME will be produced. 
Both adjusted and unadjusted between-group comparisons will be presented with 95% confidence 
intervals. 
 
9.4.4 SAFETY ANALYSES 
All safety analyses will be descriptive. No statistical testing will be performed. 
 
9.4.5 BASELINE DESCRIPTIVE STATISTICS 
We will summarize demographic and baseline characteristics both by treatment group and overall.  Any 
time-to-event counts will be measured from the day of randomization. Body Mass Index (BMI) will be 
calculated according to: BMI=weight (kg)/(height (m))2. Age will be calculated according to: Age=(date 
of event-birth date+1)/365.25. Weekly average opioid dosage will be calculated as a 7-day average of 
daily maximum milligrams morphine equivalent (MME) as prescribed. Mean activity measures will be 
calculated as weekly averages (e.g. weekly steps, weekly sleep minutes). Activity classification (i.e. 

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sedentary versus light versus moderate, etc.) will be provided by FitBit and reported as such. Zip code 
will be matched to median income using census data as an aggregate measure of socio-economic status.  
 
9.4.6 PLANNED INTERIM ANALYSES  
No formal interim analysis or interim statistical testing for treatment comparisons is planned.  
 
9.4.7 SUB-GROUP ANALYSES 
Subgroup analyses are planned for the change from baseline in PROMIS-PI. An MMRM model will be 
used to test for treatment by subgroup interactions. Interactions with a significance level of less than 
10% will be considered potentially important and flagged for further assessment. In general, the models 
will include fixed categorical effects for treatment, week, treatment by week interaction, subgroup, and 
treatment by subgroup interaction. The p-values of interaction terms will be presented, as well as the 
least squares means and 95% confidence intervals by treatment and subgroup classification factor. 
Descriptive statistics of the observed and change from baseline PROMIS-PI t-score will also be presented 
by treatment and week within each subgroup. 
 
Subgroup analyses will be performed for the following subgroups: 
 
• 
Dosage of VR (minutes per week) 
• 
Previous experience with VR 
• 
ITQ score 
• 
Presence score 
• 
Patient comorbidities 
• 
History of spinal surgery 
• 
Pain severity and duration  
• 
Sociodemographics (i.e. age, sex, race, ethnicity, workers comp, marital status, education) 
• 
Other treatments (see section 6.5) 
• 
TAPS-1, TAPS-2 
• 
Mood disturbances (e.g., current depressive disorder or not, severely depressed mood vs. non-
depressed, etc.) 
• 
Radicular vs. non-radicular back pain 
• SSQ Cutoff (Score of >15) 
• Treatment Expectation Question  
• Perception of arm of study question 
• Motion Sickness Propensity Survey 
 
The primary MMRM models will be re-fit to include terms describing subgroups. The change from 
baseline PROMIS-PI score obtained at Day 30 will be compared between the treatment groups using 
MMRM analysis. The repeated measures are the change from baseline PROMIS-PI score obtained for 
Day 7, 15, 21, and 30, respectively. The model will include fixed categorical effects for treatment, week, 
treatment by week interaction, relevant subgroup, treatment by subgroup interaction, and the baseline 
PROMIS-PI score as a continuous covariate. The estimated least squares means and 95% confidence 
intervals on the treatment comparison for Day 7, 15, 21, and 30, will be presented in forest plots for 
each subgroup of relevance. 
 
See Section 9.4.9 under exploratory analysis for more detail.  

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9.4.8 TABULATION OF INDIVIDUAL PARTICIPANT DATA 
We will tabulate individual participant data according to the Clinical Data Interchange Standards 
Consortium (CDISC) Study Data Tabulation Model (SDTM) as specified by the Data Integration, Algorithm 
Development and Operations Management Center (DAC).  
 
9.4.9 EXPLORATORY OUTCOMES 
 
A few exploratory hypotheses have been considered: 
 
Exploratory Outcome: Global impression of change with pain treatment using PGIC  
Question: Which intervention is associated with patient’s perceived change in condition due to 
treatment? 
Dependent variable: patient’s perceived change in condition as assessed by PGIC 
Comparisons: Superiority for both of the following (1) Distraction VR therapy vs. sham VR therapy; (2) 
skills-based VR therapy vs. sham VR therapy, if there is a statistically significant difference in Skills based 
VR vs Sham VR then a third test will be completed (3) Skills-based VR therapy vs Distraction VR therapy 
 
Exploratory Outcome:  Quality of sleep over time by biometric data on Fitbit Charge 4 (total minutes 
asleep and sleep efficiency per night))  
Hypothesis: Skills-based VR will lead to a greater improvement in sleep quality than distraction based VR 
or Sham VR.  
Comparisons: Superiority for both of the following (1) Distraction VR therapy vs. sham VR therapy; (2) 
skills-based VR therapy vs. sham VR therapy, if there is a statistically significant difference in Skills based 
VR vs Sham VR then a third test will be completed (3) Skills-based VR therapy vs Distraction VR therapy 
 
Exploratory Outcome:  Depression over time as measured by PROMIS Depression (version 4) 
Hypothesis: Skills-based VR will lead to a greater improvement in PROMIS Depression than distraction-
based VR or Sham VR.  
Comparisons: Superiority for both of the following (1) Distraction VR therapy vs. sham VR therapy; (2) 
skills-based VR therapy vs. sham VR therapy, if there is a statistically significant difference in Skills based 
VR vs Sham VR then a third test will be completed (3) Skills-based VR therapy vs Distraction VR therapy 
 
Exploratory Outcome:  Increased physical function over time as measured by total steps using biometric 
data 
Hypothesis: Skills-based VR will lead to a greater improvement in physical activity than distraction-based 
VR or Sham VR.  
Comparisons: Superiority for both of the following (1) Distraction VR therapy vs. sham VR therapy; (2) 
skills-based VR therapy vs. sham VR therapy, if there is a statistically significant difference in Skills based 
VR vs Sham VR then a third test will be completed (3) Skills-based VR therapy vs Distraction VR therapy 
 
Exploratory Outcome: Improvement in physical function as measured by PROMIS physical function 
(version 6b) 
Hypothesis: Skills-based VR will lead to a greater improvement in physical activity than distraction-based 
VR or Sham VR.  

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Comparisons: Superiority for both of the following (1) Distraction VR therapy vs. sham VR therapy; (2) 
skills-based VR therapy vs. sham VR therapy, if there is a statistically significant difference in Skills based 
VR vs Sham VR then a third test will be completed (3) Skills-based VR therapy vs Distraction VR therapy 
See Section 4.6.3 of the SAP for details on the assessment of each the above outcomes.  
 
 
10 SUPPORTING DOCUMENTATION AND OPERATIONAL CONSIDERATIONS 
 
10.1 REGULATORY, ETHICAL, AND STUDY OVERSIGHT CONSIDERATIONS 
 
10.1.1 INFORMED CONSENT PROCESS 
 
10.1.1.1 CONSENT/ASSENT AND OTHER INFORMATIONAL DOCUMENTS PROVIDED TO 
PARTICIPANTS 
Consent forms describing in detail the study intervention, study procedures, and risks are given to the 
participant and electronic documentation of informed consent is required prior to starting screener 
week procedures.  
 
10.1.1.2 CONSENT PROCEDURES AND DOCUMENTATION 
All eligible participants identified either by their treating physician or by Deep6 will be contacted by a 
research coordinator using an IRB approved recruitment email that will explain the study. The patient 
will be able to reply to the communication with a request to opt-out of further communication. A 
research coordinator will telephone individuals who do not opt out to discuss their interest in study 
participation. An IRB-approved script will explain the study in lay language, including the purpose, 
procedures, and potential risks of the study and research rights as a participant. Study Coordinators will 
ensure the identity of the person on the phone call is indeed the prospective participant that was 
intended. REDCap will be used to email the IRB approved electronic consent form to the patient. 
Participants will have the opportunity to carefully review the electronic consent form and ask questions 
prior to signing. Participants will complete their consent forms electronically using the 21 CFR 11-
compliant online platform, REDCap. A child assent form will be included as part of the informed consent 
to allow for adolescent participants to be enrolled. Every subject will be informed of the approximate 
time to complete the consent process. A copy of the informed consent documents will be provided to 
participants for their records via email. The informed consent will be signed by the patient and the 
designated investigator before the participant undergoes any study-specific procedures. The rights and 
welfare of the participants will be protected, and it will be emphasized that their medical care will not 
be adversely affected in any way if they decline to participate in this study. 
All patients will be able to opt-out of the study via email or by phone. We request removal of an official 
wait time between sending the email/letter and contacting subjects by phone. Our justification is that, to 
date, in the rural chronic pain study alone, 153 recruitment letters have been sent to Cedars-Sinai 
patients. However, none of them have contacted our study staff prior to the 7-day period, and of the 33 
individuals who were sent a recruitment letter and later declined, only two declined by email. 98.7% of 
recruitment letters have not obviated the need for a follow-up recruitment call, and this response rate 
compares to our other trials. Most individuals do not recall seeing or reading the letter when finally 
reached by phone.  

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A verbal explanation will be provided in terms suited to the participant’s comprehension of the 
purposes, procedures, and potential risks of the study and of their rights as research participants. 
Participants will have the opportunity to carefully review the electronic consent form and ask questions 
prior to signing. The participants should have the opportunity to discuss the study with their family or 
surrogates or think about it prior to agreeing to participate. The participant will sign the informed 
consent document prior to starting the screening week surveys. Participants must be informed that 
participation is voluntary and that they may withdraw from the study at any time, without prejudice.  
The informed consent states that any changes in pain management should be made with the 
participants treating physician.  
10.1.2 STUDY DISCONTINUATION AND CLOSURE  
We do not anticipate any events that would warrant study discontinuation and closure. 
 
10.1.3 CONFIDENTIALITY AND PRIVACY   
Participant privacy is strictly held in trust by the participating investigators, their staff, and their 
interventions. Therefore, the study protocol, documentation, data, and all other information generated 
will be held in strict confidence. No information concerning the study or the data will be released to any 
unauthorized third party without prior written approval of the sponsor.  
 
Representatives of the IRB or regulatory agencies may inspect all documents and records required to be 
maintained by the investigator for the participants in this study. The clinical study site will permit access 
to such records as needed. 
 
Data in the study is collected in three ways: in real-time, at infrequent intervals throughout the study, 
and through medical record queries. Real-time data, including biometrics and survey data delivered via 
mobile device, will be stored on secure servers hosted by Amazon Web Services (AWS) and will contain 
only a unique identifier for each participant. Virtual reality adherence data will also be tracked in real-
time and hosted on secure servers by AppliedVR; a separate unique ID will be assigned to each 
participant. Data collected at infrequent intervals throughout the study, such as entry, 14-day interval 
assessments, and exit questionnaires will be stored on secure CSMC servers with unique ID's for each 
participant. Data collected from medical record numbers, such as opioid prescriptions and physician 
history, will reside on secure CSMC servers and an ID will be assigned to each individual in order to 
abstract PHI/PII and the medical record number. Each dataset will utilize different unique ID's and a list 
linking each unique ID to each participant will be stored internally on the secured CSMC network. The 
linking list allows a researcher with access to the secured files to merge all data using statistical 
software, while maintaining data confidentiality. 
 
To minimize risk of breaches in confidentiality associated with the access and recording of protected 
health information, study staff will be assigned unique passwords and usernames to access secure 
servers. Additionally, identifiable information for participants will be obfuscated using unique ID 
numbers and a linking list will be held in a secure location. 
 
A detailed list of procedures that protect confidentiality is in section 20.1 of the MOOP. 
 
10.1.4 FUTURE USE OF STORED SPECIMENS AND DATA  
N/A 

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10.1.5 KEY ROLES AND STUDY GOVERNANCE    
Principal Investigator 
Brennan Spiegel, MD, MSHS 
Director of Health Services Research   
Cedars-Sinai Medical Center  
116 N. Robertson Blvd, Suite 800  
Los Angeles, CA 90048 
310.423.6784 
Brennan.Spiegel@cshs.org 
 
 
As shown in Figure 1, below, the PI oversees the grant and interacts with all the key stakeholders, including 
NIAMS, KAI Research and associated DSMB, the Cedars-Sinai IRB, and members of the Clinical Research 
Team, Data Management Team, and the Study Statisticians.  
 
 
10.1.6 SAFETY OVERSIGHT     
Safety oversight will be under the direction of a DSMB composed of individuals with the appropriate 
expertise. The DSMB will be appointed by and serve as advisory to the NIAMS. Members of the DSMB 
should be independent from the study conduct and free of conflict of interest, or measures should be in 
place to minimize perceived conflict of interest.  The DSMB will meet at least semiannually to assess 
safety and efficacy data on each arm of the study. The DMSB will operate under the rules of an 
approved charter that will be written and reviewed at the organizational meeting of the DSMB. At this 
time, each data element that the DSMB needs to assess will be clearly defined. The NIH will provide its 
input to specify the study sponsor National Institutes of Health staff.  
 
 

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10.1.7 CLINICAL MONITORING 
As the intervention in this trial is not greater than minimal risk, a designated member of the study team 
will conduct periodic monitoring every 6 months and review safety data such as AEs reported, using 
DSM reports attached in DSMP. The compiled reports will be discussed amongst the study team at the 
earliest opportunity. These reports will also be submitted to executive secretary and NIAMS via the 
semiannual DSMB report. The study team will compile with any requested action by the DSMB.  
 
10.1.8 QUALITY ASSURANCE AND QUALITY CONTROL 
Our quality assurance (QA) and control (QC) procedures are designed to support adherence to the 
protocol, obtain complete follow-up data for all participants enrolled, and establish and maintain high 
standards for validity in collected data ahead of analysis. We approach QA as processes and safeguards 
for the prevention of data errors, and QC as mitigation efforts reducing impact from errors that have 
occurred during data capture and/or processing. While much of the QA effort occurs ahead of study 
launch, both efforts will require real-time and periodic tasks conducted through the duration of the 
study to ensure consistent checks of data integrity, completeness, and correctness. 
QA via error prevention will focus largely on the REDCap system. Before data is entered into REDCap, 
study personnel will:  
• 
Indicate units in question stems and use field validation whenever possible; 
• 
Define and enforce range minimum/maximum where applicable; 
• 
Ensure uniformity in date formatting across all REDCap date fields; 
• 
Program pre-defined multiple-choice fields whenever possible (as opposed to free text); 
• 
Indicate specific, standardized choices to identify data as intentionally missing (e.g “Not 
Applicable,” “Don’t Know”) as opposed to blank fields; 
• 
Enforce skip/no-skip logic where appropriate; 
• 
Standardize assignment of raw values. (i.e. if “Yes” is coded as a ‘1’ in one field, it should be 
coded as ‘1’ in all other project fields); and 
• 
Use case and punctuation consistently across all field labels. 
Each aspect of the REDCap data collection system will be tested before actual study data is collected. 
Study personnel will enter mock data into REDCap forms, serving as the “User” for acceptance testing. 
We will document the success or failure of a) the user interface for data entry, b) the on-line univariate 
and range data validation checks, and c) custom functions and coding. This mock data will be exported 
as SAS/STATA datasets by the research coordinator and subjected to QC procedures.  
Our fundamental QC approach prioritizes error detection. Automated QC will occur in a SAS/STATA 
programming environment and will be tested/iterated on mock data before being employed monthly to 
exported datasets from both REDCap and the EHR. These QC programs will target potential data 
anomalies including: 
• Missing data or forms; 
• Out-of-range or erroneous data; 
• Inconsistent, improperly formatted, or out-of-range dates; and 
•Fields on a "completed form" not completed.  

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Once the study begins, routine QC reports will be prepared monthly (with 2 weeks lead-time before 
proposed monthly uploads to DAC) by the study statisticians. These reports will describe target and 
actual enrollment, eligibles screened with reasons for screen failure, and participant disposition 
(enrolled; active, completed, discontinued treatment, and lost to followup). These reports will also 
provide proportions of forms completed/missing, as well as summaries of problems identified by QC 
processes. Changes to QC programming will be documented and re-tested for accuracy. 
Finally, daily monitoring for data completeness will be undertaken by the study team as a QA effort. 
Patients will initially be sent a reminder email when they have not submitted data after 2 days. If no 
response is given two additional 48-hr reminders will be sent. Research staff will attempt to contact the 
patient up to 3 times in one week.  
 
10.1.9 DATA HANDLING AND RECORD KEEPING  
 
10.1.9.1 DATA COLLECTION AND MANAGEMENT RESPONSIBILITIES  
Study staff will develop, test, and maintain the data capture system using a web-based data collection 
system, REDCap, as the primary source of data entry and storage. Developed by Vanderbilt University, 
REDCap is a software toolset and workflow methodology for electronic collection and management of 
research and clinical trial data. The REDCap system provides a secure, web-based application that is 
flexible and provides: 1) an intuitive interface for users to enter data and have real time validation rules 
(with automated data type and range checks) at the time of entry; 2) HIPAA compliant audit trails for 
tracking page views, data manipulation and export procedures; 3) record locking and electronic 
signature functions; 4) control over user rights to view and manipulate data; 5) a report builder capable 
of querying patient records; and 6) automated export procedures for SAS/STATA datasets.  
 
The REDCap system complies with all applicable guidelines to ensure patient confidentiality, data 
integrity, and reliability. Quality assurance and control procedures will be applied to ensure the 
completeness, validity, and accuracy of the study database. The MOOP describes data collection 
processes, database development procedures, quality control processes, and reporting in greater detail. 
 
EHR data will be retrieved by the Research Informatics and Scientific Computing Core (RISCC) at Cedars-
Sinai, which facilitates interaction between the research community and the Epic data warehouse and 
production environment. We will collaborate with RISCC to design queries for portions of participants’ 
records as defined in the data dictionary. The data extracts issuing from these queries will be delivered 
monthly as CSV files via Box, a HIPAA compliant cloud content management system. These will then be 
converted to SAS/STATA data sets and subjected to QC procedures in a SAS/STATA environment. 
 
VR device metadata will be provided monthly by AppliedVR as CSV files containing timestamped records 
of content accessed at the individual device level. These records will feature a device-ID unique to each 
patient. A linking list containing study-IDs and device-IDs will be stored on a secure server behind the 
Cedars-Sinai firewall, and only associated with other study data following database lock. In order to 
monitor weekly adherence, study-staff will access a subset of the metadata limited to study-ID and 
timestamps of usage. These data will be subjected to QC procedures in a SAS/STATA environment. 
 
Deidentified Fitbit data will be stored by a research-grade, IRB-approved service (Fitabase, San Diego, 
CA) as minute level data from Fitbit servers for all participants. This data will be retrieved as CSV files 
and linked to study data in a secure SAS/STATA environment before being subjected to QC procedures. 
 

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In order to maintain standard data definitions and structures, the data dictionary and proposed 
database structures reflect the Standard Clinical Data Interchange Standards Consortium’s (CDISC) Study 
Data Tabulation Model (SDTM). The data elements and relationships described by this standard will 
facilitate information exchange with DAC. Furthermore, we will employ DAC’s forthcoming approach to 
data cleanliness and completeness standards and notation.  
 
10.1.9.2 STUDY RECORDS RETENTION  
In compliance with Protection of Human Subjects regulations, records related to the conduct of this 
trial, including but not limited to source documentation, informed consent forms, essential study 
documentation, and documentation of IRB activities, will be retained by the Investigator for a period of 
3 years following the official close of the study.  
 
10.1.10 
PROTOCOL DEVIATIONS  
A protocol deviation is any noncompliance with the clinical trial protocol. The noncompliance may be 
either on the part of the participant, the investigator, or the study site staff. As a result of deviations, 
corrective actions are to be developed by the site and implemented promptly.  
 
These practices are consistent with ICH GCP:  
• 
4.5 Compliance with Protocol, sections 4.5.1, 4.5.2, and 4.5.3  
• 
5.1 Quality Assurance and Quality Control, section 5.1.1  
• 
5.20 Noncompliance, sections 5.20.1, and 5.20.2.  
 
Protocol deviations/violations impacting participant safety will be reported to NIAMS and the DSMB 
Safety Officer through the NIAMS Executive Secretary within 48 hours of the investigator becoming 
aware of the event; all other deviations/violations that do not impact participant safety can be reported 
as part of the routine DSMB meeting report. The investigator will also report deviations within 5 working 
days of identification of the protocol deviation to the IRB.  All deviations must be addressed in study 
source documents and reported to NIAMS.  Protocol deviations must be sent to the reviewing 
Institutional Review Board (IRB) per their policies. The principal investigator is responsible for knowing 
and adhering to the IRB requirements.  
 
10.1.11 
PUBLICATION AND DATA SHARING POLICY 
This study will be conducted in accordance with the following publication and data sharing policies and 
regulations: 
 
This trial will be registered at ClinicalTrials.gov, and results information from this trial will be submitted 
to ClinicalTrials.gov. In addition, every attempt will be made to publish results in peer-reviewed journals.  
Data from this study may be requested from other researchers 3 years after the completion of the 
primary endpoint by contacting the Cedars-Sinai Center for Outcomes Research and Education. 
 
We will also comply with the data sharing policy at NIH under NOT-OD-08-033. We will submit the final 
manuscripts to the NIH National Library of Medicine PubMed central for archiving upon acceptance for 
publication. 
 
10.1.12 
CONFLICT OF INTEREST POLICY 

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The independence of this study from any actual or perceived influence is critical.  The Cedars-Sinai 
Identifying and Disclosing Researchers’ Financial Interests in Research Policy: Human Research 
Protection Program requires the Principal Investigator and all members of the study team to disclose 
their, their spouses’/domestic partners’, and dependent children’s financial interests in the research 
regardless of the source of funding. Additional disclosure requirements may apply to investigators 
involved in Federally-funded research as described in the Cedars-Sinai Management of Industry 
Relations and Conflicts of Interest Program Policy: Corporate Integrity Program. The Cedars-Sinai 
Institutional Review Board (IRB) retains authority to determine if the research is allowed to proceed 
under the terms of the management plan developed by IR/COI considering the potential impact on the 
process and documentation of informed consent and the equitable selection of subjects. Review of 
disclosed COIs associated with a human research protocol by IR/COI is requested through submission of 
the CS-IRB COI Disclosure Form, which details IRB-supported guidelines on methods to manage, 
mitigate, or eliminate COIs.  
 
10.2 ADDITIONAL CONSIDERATIONS 
NA 
11 APPENDIX A: RESEARCH SUPPLEMENT – ADVOCATING FOR UNDERREPRESENTED 
PATIENT POPULATIONS IN RESEARCH 
 
11.1 BACKGROUND AND APPROACH 
Black and Hispanic patients are up to five times less likely to have access to digital health 
information than non-Hispanic whites. In addition to disparities in access and adoption of digital 
health interventions, there are known disparities in the incidence and reporting of pain by racial 
and ethnic minorities. This Diversity, Inclusion and Engagement Supplement aims to develop a 
framework to advance diversity and inclusion efforts for future digital health trials at our medical 
center and beyond. Further, it will enhance the parent study by seeking to increase the 
proportion of participants with historically less access to and familiarity with digital technologies 
while enhancing overall participant racial and ethnic diversity.  
Approach  
The scientific approach of this supplemental grant will be inspired by the NIH Stage Model for 
Behavioral Intervention Development (Figure 1). 
First, we will conduct focus groups with non-Hispanic Black and Hispanic patients with cLBP to 
identify the most important content areas to be included in our two sets of culturally tailored 
study materials, described below. Then, we will employ insights from our patient partners to 
craft culturally tailored and engaging study materials and will then iteratively optimize the 
materials through cognitive de-briefing interviews, described below. Finally, we will assess 
whether implementation of culturally tailored study materials leads to a higher proportion of non-
Hispanic Black and Hispanic participants when coupled with a novel study-participant cohort 
building tool, discussed below.  
 
11.2 AIMS AND METHODOLOGY 

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Aim 1: Tailor recruitment materials for non-Hispanic Black and Hispanic patients with 
cLBP in partnership with representative patient advisory boards (PABs).  
To achieve this aim, we will update current study materials, including informational flyers, 
consent forms, email templates, VR cognitive debriefing manuals, and instructions for use of 
assigned hardware and software to better reflect the knowledge, attitudes, beliefs, and 
preferences of non-Hispanic Black and Hispanic study participants. Our goal will be to create 
two separate sets of culturally tailored materials, one per target group, to supplement existing 
non-tailored materials. This will be accomplished through a set of representative PAB focus 
groups to generate themes and concepts for study materials, integration of PAB input to modify 
materials, and iterative optimization of the materials through one-on-one cognitive debriefing 
interviews.  
PAB Focus Groups: We will conduct foundational research with representative groups of non-
Hispanic Black and Hispanic individuals with cLBP to inform development of culturally tailored 
study materials. We will convene 4 focus groups, including 2 groups each of non-Hispanic Black 
and Hispanic participants, each comprising 4-6 individuals for a total of 16-24 focus group 
participants. PAB members will be recruited through a combination of former study participants 
from the parent study, including both completers and participants who withdrew, along with 
additional participants naïve to the study identified through the Cedars-Sinai Patient 
Engagement Office and the Cedars-Sinai Medical Network. We will also seek participants from 
outside of Cedars-Sinai through patient advocacy groups as well as online and print ads. Given 
the high prevalence of cLBP in the population at large, the high prevalence of non-Hispanic 
Blacks and Hispanic populations in Southern California, and our successful track record of 
exceeding study recruitment goals to date, we do not anticipate challenges identifying up to 24 
participants to join the PAB focus groups. In constructing the groups, we will seek to diversify 
the PABs across age, sex, education, and SES strata, where possible, to reflect different life 
experiences and perspectives within the target populations.  
PAB focus groups will be held online using Zoom and will capture audio (not video) recordings 
of the proceedings after obtaining participant consent. Before the focus groups, we will develop 
a guide with participant instructions, open-ended think-aloud exercises, and scripted probes. 
Participants will also receive PDF or print copies of all current study materials prior to the focus 
groups (according to participant preference to receive materials by email or paper mail), and 
they will be asked to review the materials in advance of the meeting. A licensed neurosurgeon 
and/or PhD social scientist will moderate each focus group, with assistance from other members 
of study staff who will facilitate and take notes. Each focus group is expected to last 
approximately 90 minutes. Audio recordings will be transcribed by a third party (Keystrokes, 
Santa Monica, CA) for subsequent analysis by the study team.  
Participants will initially be asked to react to the existing study materials in their own words and 
without prompting. The moderator will then follow scripted probes to expand on themes, 
concepts, and specific language or visuals suggested by the participants. Through group 
interaction, we will seek to identify unique relevant language with the goal of later incorporating 
the PAB input into modifying and culturally tailoring the materials, including both visual and 
textual elements. We will conduct multiple groups to ensure that interactions of a single group 
do not bias any one conclusion and to provide greater generalizability of our findings.  
Upon completion of the focus groups, trained social scientists will qualitatively analyze the 
transcripts using ATLAS.ti software, including coding of patient language and classification of 

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vocabulary into major and minor concepts. The evaluation process will generate key words, 
phrases, and quotes to be used in developing tailored study materials for each group. To be 
considered credible, concepts for adoption will ideally be raised by more than one participant 
and by participants in more than one group, although individual decisions will be made using the 
discretion of the research team and with recognition that materials will undergo subsequent 
modifications based on the cognitive debriefings. We will use ATLAS.ti to generate code count 
histograms within major and minor concepts and will develop a network to depict a framework 
describing the breadth and depth of concepts to consider integrating into the study materials. 
The result will be a detailed “blueprint” for updating the study materials.  
Updating Study Materials: We will next develop and refine tailored study materials. After 
conducting the PAB focus groups, abstracting and organizing themes and concepts, and 
collecting suggestions for language and visuals, we will develop draft study materials for each 
targeted group: one set for non-Hispanic Blacks, and one for Hispanic participants, with cLBP. 
In developing the materials, we will aim to not exceed a sixth-grade reading level based on the 
validated “simple measure of gobbledygook” (SMOG) calculator, an approach we also followed 
in creating item banks for the NIH Patient Reported Outcome Measurement Information System 
(PROMIS). As with any study materials, we will also seek to minimize ambiguity or cognitive 
difficulty, avoid multi-barreled questions, and use language that is as concise and simply 
worded as possible while attempting to use common English words and avoiding slang unless 
considered appropriate or warranted by PAB members.  
Cognitive Debriefing Interviews: Once the study materials have been modified using input 
from the PAB focus groups, we will conduct patient cognitive debriefing interviews to assess for 
content validity, clarity, comprehensiveness and appropriateness of the resulting materials. We 
will prepare a scripted interview guide to elicit patient feedback on the draft materials. One-on-
one interviews will be conducted via telephone with the same moderator who conducted the 
PAB meetings. For these individual interviews, we will sequentially recruit as many as 10 
participants from each targeted group, drawing from PAB participants and the PAB waitlist, and 
will evaluate perceptions about the verbiage, images, and appearance of the draft materials. 
These interviews will not berecorded.. We will then iteratively update the materials until they are 
optimized, as evidenced by receiving fewer actionable suggestions over the course of the 
interviews (with modifications made after each interview). If we encounter a substantial number 
of actionable suggestions for improvement after 10 interviews, indicating lack of thematic 
saturation, then we will conduct up to 5 additional interviews, drawing again from PAB focus 
group participants. Through this process, we will fine-tune the materials and be prepared to 
deliver them as part of Aim 2 of the supplemental research, described below.  
Aim 2. Oversample non-Hispanic Black and Hispanic participants in parent study using a 
cohort building tool housed within the electronic health record (EHR).  
After developing two sets of culturally tailored study materials, we will next seek to deliver those 
materials to eligible study participants. This, in turn, will require us to identify enough non-
Hispanic Black and Hispanic participants with cLBP to meet our target goals, described later in 
this section. To achieve this aim, we will employ Deep6 AI® (Pasadena, CA), a natural 
language processing (NLP) cohort building tool, and enlist Cedars-Sinai’s Enterprise Information 
Services (EIS), to oversample non-Hispanic Black and Hispanic participants from throughout 
Cedars-Sinai and our participating recruitment sites. Deep6 specifically integrates with our EHR 
to search both structured and unstructured data to build cohorts for clinical trials, and EIS will 
conduct SQL queries based on exclusionary criteria, race and ethnicity, and visits with recruiting 
physicians to capture additional participants not included in the Deep6 sample. Although Deep6 
is already part of our protocol, it is not currently being used to specifically target study 

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participants by race or ethnicity. Further, it can only provide a maximum of 7,500 qualifying 
patients per pull.  In this supplement, we will oversample target populations using Deep6 and 
EIS, then deliver the appropriate set of tailored recruitment materials developed in Aim 1 to 
these identified prospective participants. We will monitor outcomes by comparing actual 
recruitment against target oversampling goals, as discussed, below.  
 
11.3 REVISED RECRUITMENT TARGETS 
Current and Revised Recruitment Targets: Currently, the target sample size for the 
parent study is 360 participants. Regarding Hispanic participants, although we are meeting 
our original recruitment goal which was set at 11% to reflect U.S. Census data, there is a much 
higher prevalence of Hispanic/Latinx individuals in Southern California where the 2019 Los 
Angeles County Census revealed a 48% prevalence of this group. We intend to implement 
these new recruitment materials and strategies once we have randomized 50% of the 
overall study cohort. Because certain participants are eligible for replacement if they are 
withdrawn after randomization, this will occur at approximately participant #200 based on 
current rates of withdrawal. Specifically, beginning at this point, we will seek to recruit a second-
half study sample that is 17% non-Hispanic black (previous target 12%), 40% Hispanic 
(previous target 11%), and 35% non-Hispanic white (previous target 76%).  
 
11.4 STRATEGIES TO ENSURE TARGETS ARE MET 
Monitoring Recruitment Progress: The research team will meet weekly during the study to 
monitor progress towards achieving target goals and will track progress using tables and visual 
dashboards. If the performance line falls below the target line for three consecutive weeks, then 
we will initiate a three-pronged strategy to course-correct as needed:  
Strategy 1—Adjust Deep6 and EIS search algorithms and sample rates: If recruitment tracking 
reveals projections that we are falling short of target goals, then we will consult with Deep6 NLP 
and EIS specialists to fine-tune the parameters of the search algorithm. For example, if 
race/ethnicity fields are inaccurate or incomplete for some records, there may be other viable 
approaches such as NLP searches of clinician-inputted text within notes indicating race or 
ethnicity. Further, if we find specific groups are disproportionately unable to complete the 
screening process, we will further oversample the ratio of these participants contacted within the 
cohort builder lists to ensure enrollment rates meet our new target proportions. 
Strategy 2—Interviews of non-enrolled patients: If necessary, we will seek consent to interview 
non-Hispanic Black and Hispanic patients who were invited to participate in the study, received 
the tailored recruitment materials, but nonetheless opted not to enroll in the trial. We will 
conduct individual cognitive debriefing interviews using the same techniques described under 
Aim 2, but here focus on individuals who experienced the recruitment materials first-hand. We 
will update recruitment materials further if these interviews elicit specific and actionable 
feedback that is incremental to the Aim 1 results.  
Strategy 3—Interviews of patients who withdrew from the study: In addition to interviewing 
patients who declined to enroll, we will also seek consent to interview non-Hispanic Black and 
Hispanic participants who enrolled in the study but later dropped out before completion despite 
receiving tailored post-enrolment materials. These study participants may have a different 

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perspective from those who never enrolled and will also have experienced a broader range of 
study materials beyond the recruitment flyer and consent form (e.g., surveys, VR debriefing 
manual, instructions for hardware/software usage). We will again use the same cognitive 
interviews techniques previously described, and will further modify study materials, as needed, 
based on these additional de-briefing interviews. 
12 APPENDIX B: RESEARCH SUPPLEMENT – UNDERSTANDING PATIENT PREDICTORS OF 
RESPONSE (3UH3AR076573-03S2) 
 
12.1 BACKGROUND AND APPROACH 
Although digital health technologies are now widely available for both therapeutic and monitoring 
applications, there are wide variations in patient knowledge, attitudes, beliefs and preferences 
regarding the uptake and effectiveness of digital health interventions. In addition, there are 
sociodemographic variations in willingness to engage in digital health studies, both for chronic pain and 
other common disorders. A recent study published in the Journal of Racial and Ethnic Health Disparities 
in February of 2021 found that older, less educated, and economically disadvantaged Black and Hispanic 
patients were up to five times less likely to have access to digital health information. Additionally, a 
2016 study exploring the trends of uptake by Medicare beneficiaries found that digital health 
information has not yet fully reached the elderly. There have been few efforts to systematically examine 
patient-level predictors of digital health uptake and benefit among diverse patients with chronic pain. 
This substudy will identify specific patient characteristics that influence enrollment in and completion of 
the parent study by employing mixed methods to examine variations in demographics, engagement, and 
benefit among diverse participants. The project will also offer mentorship, research training, and 
authorship experience to support early career development for Lindsey Ross, MD, MHDS. 
 
12.2 AIMS AND METHODOLOGY 
Aim 1: To identify explicit and latent variables associated with membership in subgroups of 
participants in the parent RCT of VR therapy for cLBP.  
The Digital Divide (DD) can be explained as separating patients into overarching subgroups or “classes” – 
those who enroll in and complete studies like the parent VR study and subsequently use the technology 
in their daily lives to manage pain, and those who do not. Our hypothesis is twofold: first, that there are 
patient-level, explicitly measured variables associated with enrollment in and successful completion of 
these types of studies (Hypothesis1). Second, the DD in study completeness will be further explained by 
latent (unobservable) “classes” of patients (Hypothesis2); membership in these latent classes is 
predicated upon unobservable or latent patient-level variables. Analyzing the explicit variables identified 
in H1 in conjunction with the identified latent classes, we hope to gain a better understanding of what 
explicit measures or combinations of measures may be missing or need further consideration for 
inclusion in studies testing VR for cLBP, or other related technologies or outcomes.  
To test H1, we will identify important patient-level (measured) variables associated with enrollment in 
and the successful completion of the parent RCT, as well as those associated with the decision not to 
enroll. Specifically, we will implement a two-part regression model. The first part with a logistic 

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regression analysis modeling a binary outcome of enrollment, then the second part with a generalized 
linear regression for modeling study completeness.  
To test H2, explicit variables including demographic variables and patient reported outcomes will be 
used in a latent class analysis (LCA) aimed at determining whether there are latent classes of patients 
and, if so, what explicit measures may be associated with class membership. LCA uses underlying 
patterns in the data (e.g., unobserved characteristics often associated with knowledge, attitudes, and 
beliefs) to identify latent classes (unidentified subgroups) of patients. Latent classes help guide 
qualitative investigation of surrounding phenomenology and determination of explicit variables that 
predict membership in a latent class. 
 
  
Aim 2: Explicate patient experiences on both sides of the Digital Divide (DD), including understanding 
how they arrived on a given side, by describing phenomenology surrounding enrollment in and 
successful completion of an RCT studying VR as treatment for cLBP. 
Semi-structured focus groups will be conducted separately among classes on either side of the DD as 
well as among the intent-to-treat sample (those randomized) and participants who chose not to enroll 
or were otherwise withdrawn or discontinued prior to randomization to investigate and attempt to 
identify the underlying constructs perpetuating membership in one vs. the other groups of patients. We 
will investigate the influence of knowledge, attitudes, and beliefs on the use of novel technology such as 
VR and wearable biosensors (as the parent study uses Fitbit) in the management of cLBP, ascertain 
difficulties and limitations with the use of digital technology, and explore areas for improvement in 
designing trials of this kind. Separately, from among the listed groups of participants, we aim to recruit 
N=24 (4 focus groups of up to 6 members each). Focus group data will include and qualitative data 
elicited through discussions characterizing experiences of using VR and describing how these factors 
have or have not influenced patients to preclude, decrease, continue, or increase use. 
Participants who were contacted for participation in the parent study will first be approached by email 
recruitment letter, then a phone call, for participation in this study. Participants expressing interest will 
be contacted again with a list of possible dates and times to participate. Prior to the scheduled focus 
group, participants will also be emailed an information sheet describing the risks and benefits of 
participating in the sub-study, and at the start of the focus group session, present participants will be 
asked to verbally confirm that they have read and understood the information sheet. Participants will be 
reimbursed with a $100 Amazon e-gift card for their participation once they have completed the focus 
group, which should take no longer than 60 minutes.  
 
12.3 CAREER DEVELOPMENT PLAN 
The supplemental funding mechanism included a career development and mentoring plan, centered 
around holistic growth as a future physician scientist. The primary goals for Dr. Ross’ career 
development plan include (1) learning to independently lead and coordinate a scientific research 
project; (2) communicate and manage a large research team; and (3) produce high-quality research 
manuscripts and presentations of findings on national platforms.  

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The research timeline, presented below, includes the primary goals of improving scientific research 
knowledge and production of manuscripts and long-term goals of ultimately completing a K08 grant 
application by 2024. 
Research Timeline 
Year 
Year 1 
Year 2 
Year 3 
Year 4 
Skills 
Data management and 
methods skill building 
Quantitative/Qualitative 
analysis methods 
Manuscript production 
Presentations and future 
funding 
Aims 
DEI supplemental 
qualitative and 
quantitative methods 
and manuscript 
production 
 
Preparation for data 
analysis to start at 
completion of parent 
study 
Aim 1: Initiate semi-
structured interviews 
 
Aim 2: Complete data 
collection and analysis 
Complete manuscript of 
supplemental data 
 
Apply for additional 
funding with 
preliminary data 
Complete manuscript 
assistance for parent 
data grant 
 
Submit K08 with 
supplemental data 
Mentorship 
Dr. Brennan Spiegel 
 
13 APPENDIX C: RESEARCH SUPPLEMENT – INVESTIGATING THE BARRIERS TO 
IMPLEMENTATION AND THE APPROPRIATENESS OF VR CONTENT ACROSS DIVERSE 
CULTURES: A RETROSPECTIVE MIXED METHODS STUDY 
13.1 BACKGROUND AND APPROACH 
Digital therapeutics such as virtual reality (VR) technologies have the potential to expand our approach to 
chronic pain management. While this novel modality continues to be investigated, there are discrepancies 
across individuals of differing sociodemographic backgrounds in their engagement and use of VR. A 
recent study published in the Journal of Racial and Ethnic Health Disparities found that Black and 
Hispanic patients were up to five times less likely to have access to digital health information. Another 
recently published article in The Lancet stressed the need for designing digital health applications to meet 
the needs of women − especially with racial or ethnic minority backgrounds. Other studies reported similar 
differential uptake, interaction, and use of virtual reality based on geography and age. Beyond general 
digital medicine, virtual reality as an end consumer product has been found to be subject to similar 
disparities in uptake and use across multiple sociodemographic factors. 
Understanding barriers to uptake of novel therapeutic technologies is essential for formulating solutions 
that can establish equity and inclusiveness when deploying VR in healthcare to a diverse population. 
Failure to address these sociodemographic disparities can result in disadvantaged groups being unable 
to optimally utilize alternative non-opioid digital treatments and thus may require more traditional 
treatments including opioids. To achieve equity, we must verify that the digital therapeutic content is 
appropriate and accessible across diverse cultures—an investigation that is instrumentally important for 
the development of future VR applications. To that end, in this supplemental, mixed methods study we 
seek to correlate PRO data collected in the parent study with newly collected and subsequently quantized 
qualitative data acquired from individual participant interviews. 
Approach  
An NIH commissioned report on a “best practices” approach of mixed methods research (MMR) 
described MMR as “focusing on research questions that call for real-life contextual understandings, multi-
level perspectives, and cultural influences…It is a systematic and rigorous form of inquiry that uses 

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methods of data collection such as in-depth interviews, ethnographic observation, and review of 
documents.”  
In this supplemental study, we will conduct MMR employing NIH best practice methodology to better 
understand the barriers to VR implementation and the appropriateness of VR content across diverse 
cultures. This process will follow an embedded mixed methods design (QUAL(quan)) in which we will 
sample up to 35 individuals who have completed their participation in the skills-based VR therapy 
treatment arm of either the parent study (STUDY00000631) or another concurrently running study that 
employs the same intervention in its treatment arm (STUDY00001262). We plan to sample from this 
additional source (STUDY00001262) to ensure the maximal sampling of the targeted subgroups as 
identified by this supplement.  
Potential subjects will be identified and considered eligible for participation in this study based on their 
current timepoint of participation within the respective study they are currently enrolled in 
(STUDY00001262 or STUDY00000631). For the parent study (STUDY00000631), this is defined as any 
participant in the active treatment arm that has completed their day 60 PROMIS Pain Interference survey. 
For the concurrently running study (STUDY00001262), this is defined as any participant in the active 
treatment arm that has completed their week 8 PROMIS Pain Interference survey. The rationale for these 
criteria is the time-equivalency of data points, as this measure shall be used in further analyses within this 
supplemental study. The other criterion for eligibility is that the individual is 18 years or older. All 
participants that meet these criteria will be considered for participation in this sub-study.  
All identified potential participants will be contacted via phone calls (see phone script in local files). Within 
this call, subjects will be informed on the goals and methods of this study and their anonymity and 
compensation should they agree to participate. Finally, they will be informed on the possibility of being 
assigned to an AI-powered interviewer and the data protection measures that have been emplaced for 
such a modality. At the end of the call, verbal consent will be obtained from the participant and said 
consent will be documented within research notes. An interview time and date will be scheduled with the 
participant and a follow-up confirmation email will be sent to them directly after the call that has the 
information sheet for this study attached. Two days before their scheduled interview, participants will be 
sent a reminder email that restates the date and time of their interview and includes the link to the Zoom 
call on which the interview will be held. 
These individuals will subsequently be randomized into two groups to participate in a one-on-one (1:1) 
semi-structured interview exploring their beliefs and experiences of the VR intervention during their time 
in the parent study. Considering the subject and focus of this interview, no PHI is intended to be asked of 
the participants nor recorded for the purposes of this study. The first group will have standard 1:1 semi-
structured interviews led by a trained social scientist. Participants in the second group will also have 1:1 
semi-structured interviews, but these interviews will be led by an artificial intelligence (AI)-powered virtual 
social scientist. This AI interviewer is a version of GPT4 that has been iteratively refined by the study 
team to follow best practices in conducting 1:1 semi-structured interviews through prompt parameters. 
The refined prompt parameters and set interview questions will be automatically given to GPT-4 upon 
each initialization of the GPT4-powered AI interviewer. These prompt parameters and interview guide are 
set or “locked”, as it is not intended for the purposes of this investigation to implement revisions or 
improvements of the AI interviewer based on the data received during any of the interviews. Regarding 
collected data, all information collected during the interview (e.g., interview transcripts) and all data 
uploads/downloads between the interview software and GPT4 will be encrypted, transmitted, and stored 
in Microsoft Azure services with whom we have an executed business agreement that all data storage will 
meet or exceed HIPAA requirements. 
 Transcripts created by this process will be coded and analyzed independently by both AI and human 
social scientists. This analysis will follow a general, open-coding approach wherein first level codes will be 
created inductively from the data with refined second-level codes created from the first level. Results 
yielded from these analyses will be compared qualitatively to assess the thematic coverage, breadth and 
overlap between the results generated by the AI and human social scientists. 

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A later analysis will use only the second-level codes generated by the human social scientists. The 
human-generated second-level codes will be quantized by calculating their frequencies of occurrence in 
each transcript. These code frequencies will be used to identify qualitative factors that may be correlated 
with the participants’ PRO data from the parent study. Additionally, we will compare how these significant 
factors and the overarching qualitative themes differ across the demographic groups of interest. 
Successful completion of this supplemental study will guide future VR development and research to be 
more inclusive of and sensitive to diverse racial/ethnic, socioeconomic, geographic, gender, and age 
populations. Finally, we will evaluate the feasibility of using an AI-powered virtual social scientist to both 
collect and analyze qualitative data. 
 
13.2 AIMS AND METHODOLOGY 
Aim 1: Understand any barriers to implementing therapeutic VR technologies across diverse 
populations and learn how cultural differences influence perception of the VR content.  
To achieve this aim, we will interview a subset of participants by employing purposive sampling; 
participants who were enrolled in the skills-based VR arm of the parent study will be chosen based on 
criteria to maximize diversity across race/ethnicity, socioeconomic brackets, geography (based on zip-
code: rural and non-rural), gender, and age. Interviews will be performed via Zoom video conferencing 
platform, and only the audio (not video) of the interviews will be captured. Interviews will be semi-
structured to accommodate open, constructive dialogue. Prior to the first interview, we will develop a 
guide for interviewers that includes participant instructions, open-ended questions, and scripted probes to 
expand on themes. Interview questions will be tailored to target what barriers interviewees experienced 
while using VR and how they perceived the VR content in terms of their own cultural framework. Each 
interview is expected to last  no more than 60 minutes. The audio recordings will be transcribed for 
subsequent analyses. Each subgroup will attempt to include at least five participants; to accommodate 
this diversity, at least 30 subjects will be recruited. Recruitment will continue until 1) at least 30 subjects 
have been interviewed and 2) thematic saturation has been established as defined by 3 consecutive 
interviews with no new emergent themes. 
Upon completion of the interviews, trained social scientists will perform a general qualitative analysis via 
the open coding of the transcripts using ATLAS.ti software, including coding of participant language and 
classification of vocabulary into major and minor concepts. The evaluation process will generate recurring 
key words, phrases, and quotes, which can further be divided and compared among the subgroups. All 
participants will be assigned to five subgroups: race/ethnicity, socioeconomic bracket, geography, gender, 
and age. For each of these subgroups, we will use ATLAS.ti to generate code count histograms within 
major and minor concepts and will develop a network to depict a framework describing the breadth and 
depth of concepts. The result will identify differences among the subgroups and provide feedback for 
developing future, more inclusive VR content. 
 
Aim 2. Explore the relationships of how diverse groups differentially use VR technologies and how 
PROs correlate with quantized qualitative data. 
To achieve this aim, we will quantize the qualitative data derived from interview transcripts by calculating 
the frequency of qualitative code reoccurrences within each participants’ interview transcripts. Then, we 
will correlate the entire sample’s quantized count data with their corresponding PRO scores as recorded 
in the parent study. To account for the non-normal, discrete nature of the count data, we will calculate 
Spearman’s rho to assess the strength and directionality of the relationship between the constructed 
codes and the PRO scores (see Figure 1 below for power justification). Codes that are found to have a 
significant correlation with the PRO scores will be compared between the demographic subgroups of 
interest. This shall be performed through a combination of visual analysis and Kruskal-Wallis tests (when 
sample size allows).   

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Figure 1: Power Estimate for Spearman Correlation at n = 30 
 
Finally, we will complete the qualitative analysis process by constructing overarching cross-group themes 
that illustrate the views, opinions, and experiences of utilizing the skills-based VR intervention. This 
process will also include an exploration of how both the significantly correlated qualitative codes and the 
cross-group themes differ in context and content across the demographic subgroups of interest. 
By following this process, we hope to identify demographic-specific factors that both promote and inhibit 
the therapeutic efficacy of skills-based VR pain management. Awareness of these relationships will be 
necessary for improving the equity and inclusiveness of future VR therapeutics. 
 
Aim 3. Investigate the feasibility of AI to conduct 1:1 semi-structured interviews. 
To achieve this aim, participants will be randomly assigned to one of two groups that are differentiated by 
the type of interview they will receive. In one group, participants will have a 1:1 semi-structured interview 
via Zoom with a human social scientist that is trained in qualitative interview approaches (A.C.). The other 
group shall undergo the same process but with a virtual AI-powered interviewer whose avatar and voice 
will come across through Zoom. Both groups will be interviewed using the same set of probe questions 
for a maximum time per interview of 60 minutes. Only the audio from the interviews will be recorded and 
subsequently transcribed. Upon completion of the interviews and subsequent transcription process, all 
the transcripts will undergo qualitative data analysis by both AI and trained human social scientists 
independently. As such, this qualitative data analysis is expected to yield two sets of results that are 
respective to the analyst type (AI and human). Following completion of the interview, participants will be 
asked to complete a 10-item “Interviewer Sentiment Scale” questionnaire, delivered through REDCap. 
These results will be compared qualitatively for differences in thematic breadth and depth as well as the 
comparison of inductively created codes between the two results sets.  
 

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13.3 STRATEGIES TO ENSURE TARGETS ARE MET 
Monitoring Recruitment Progress: The research team will meet weekly for the duration of the study to 
monitor progress towards achieving target goals and will track progress using tables and visual 
dashboards. During these meetings, potential interviewees will be identified based on their subgroup 
profile. The meeting will also include discussions on addressing any unexpected barriers to participant 
recruitment. Should we have difficulties in recruiting participants, we will contact and attempt to recruit 
patients who withdrew from their respective study. These study participants may have a different 
perspective from those who completed their participation in the study and will also have views, opinions, 
and rationales as to why they chose to discontinue their role in the study. We will again use the same 1:1 
interview techniques previously described and will include the data collected from these participants’ 
transcripts within the main qualitative and subsequent mixed-methods analysis as described above. To 
motivate participation, we will offer reimbursement with a $100 Amazon e-gift card for completion of the 
interview and follow-up questionnaire. 
 
14 PROTOCOL AMENDMENT HISTORY 
 
Version 
Date 
Description of Change  
Brief Rationale 
2 
Revisions 
6/8/20 
 
General Updates 
Clarifications and consistency 
with other study documents. 
3.1 
8/31/20 
Necessary updates to sample size 
estimation & randomization. Additional 
edits incorporated from DSMB 
recommendations.   
Revisions recommended from 
DSMB. 
3.2 
9/16/20 
 
Charge 2 replaced with Charge 4, 
increased interval of review of 
race/ethnicity, updated description of the 
VR program. 
Changes made to reflect up-
to-date technology and update 
feasibility of protocol. 
4 
10/23/20, 
11/10/20 
Necessary updates to SoA table, 
included additional sub-groups to sub-
group analysis, updated objectives 
section, removed AppliedVR tablet from 
data collection for will not be available. 
Revisions to patient compensation, 
information added regarding CURES 
application.  
Changes were made to 
harmonize with the SAP and 
up-to-date information from 
the virtual reality vendor. 
5 
5/20/21 
Edits made to update AE assessment 
frequency, minor edits. 
Minor edits. 
6 
11/5/21 
Revised loss to follow-up definition, 
added info regarding AppliedVR VR 
usage data. 
Edits made to diversity benchmarks and 
addition of DIE supplement. 
 
Overhaul in study second half 
recruitment strategies require 
updating parent study 
protocol; too much 
harmonization between the 
two to necessitate brand new 
IRB project. 
6.1 
4/25/22 
Recruitment objectives modified to 
incorporate treating physician letter. 
Diversity supplement interview 
methodology updated to reflect that we 
Protocol reflects procedures 
and new hybrid recruiting 
strategy. 

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did not record interviews and we drew 
from PAB waitlist. 
6.2 
7/11/2022 
Depression alert procedures updated to 
include actions to take when telephone 
assessment cannot be made; approved 
by DSMB. Neck pain and rash added as 
a known risk, borrowing approved 
language from STUDY00001363. 
Table of contents page numbers 
updated. 
With DSMB guidance, 
created a contingency plan in 
the event that severely 
depressed individuals are lost 
to follow-up. List of known 
potential AEs updated to 
reflect oversight of known 
neck pain risk and to 
incorporate the incidence of 
allergy to face foam used in 
VR goggles. 
6.3 
10/24/2022 
Onboarding procedures modified to take 
into account new instructional videos. 
Compliance procedures clarified and 
modified to account for optional SMS 
text messaging via REDCap. Remove 7 
day wait after emailing recruitment 
letter. 
Removal of procedure for mailing study 
flyer. 
Onboarding procedures now 
incorporate clear video 
instructions, and compliance 
monitoring updated to reflect 
current streamlined practices. 
General housekeeping on 
procedures to align with other 
VR trials. 
6.4 
7/14/2023 
Modified definition of replaceable 
participant to exclude individuals who 
used VR intervention before 
withdrawing from study. 
Study adequately powered 
based on withdrawals to date, 
and analyses should include 
individuals who found the 
intervention unsatisfactory 
and subsequently withdrew. 
7.0 
8/29/2023 
Clarified confusing language in 
replaceable participant definition from 
previous mod. 
Addition of Appendix B: Digital Divide 
Supplement. 
Typos in language confused 
our new definition of a 
replaceable participant. 
Second sub-study added to 
appendix prior to initiation of 
new methods. 
8.0 
9/12/2023 
Addition of Appendix C: Cultural 
Barriers to VR Supplement. 
Third sub-study added to 
appendix. 
8.1 
10/17/23 
Addition of post-interview quantitative 
“Interviewer Sentiment Scale” to 
Appendix C  
Directly capture effectiveness 
of AI interviewer 
 
 
 
 
 
 
 
 
 
 
 

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