JMIR FORMATIVE RESEARCH

Darnall et al

Original Paper

Self-Administered Skills-Based Virtual Reality Intervention for
Chronic Pain: Randomized Controlled Pilot Study
Beth D Darnall1, PhD; Parthasarathy Krishnamurthy2, MBA, PhD; Jeannette Tsuei3, MA; Jorge D Minor4, MD
1

Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA, United States

2

C.T. Bauer College of Business, University of Houston, Houston, TX, United States

3

AppliedVR, Inc, Los Angeles, CA, United States

4

L.A. Pain & Wellness Institute, Los Angeles, CA, United States

Corresponding Author:
Beth D Darnall, PhD
Department of Anesthesiology, Perioperative and Pain Medicine
Stanford University School of Medicine
1070 Arastradero Road
Suite 200, MC 5596
Palo Alto, CA, 94304
United States
Phone: 1 (650) 725 9642
Email: bdarnall@stanford.edu

Abstract
Background: Patients with chronic pain often have limited access to comprehensive care that includes behavioral pain management
strategies. Virtual reality (VR) is an immersive technology and emerging digital behavioral pain therapy with analgesic efficacy
for acute pain. We found no scientific literature on skills-based VR behavioral programs for chronic pain populations.
Objective: The primary aim of this study is to evaluate the feasibility of a self-administered VR program that included content
and skills informed by evidence-based behavioral treatment for chronic pain. The secondary aim is to determine the preliminary
efficacy of the VR program in terms of average pain intensity and pain-related interference with activity, stress, mood, and sleep,and its impact on pain-related cognition and self-efficacy. The tertiary aim was to conduct a randomized controlled trial (RCT)and compare the VR treatment with an audio-only treatment. This comparison isolated the immersive effects of the VR program,
thereby informing potential mechanisms of effect.
Methods: We conducted an RCT involving a web-based convenience sample of adults (N=97) aged 18-75 years with self-reported
chronic nonmalignant low back pain or fibromyalgia, with an average pain intensity >4 over the past month and chronic pain
duration >6 months. Enrolled participants were randomly assigned to 1 of 2 unblinded treatments: (1) VR: a 21-day, skills-based
VR program for chronic pain; and (2) audio: an audio-only version of the 21-day VR program. The analytic data set included
participants who completed at least 1 of 8 surveys administered during the intervention period: VR (n=39) and audio (n=35).
Results: The VR and audio groups launched a total of 1067 and 1048 sessions, respectively. The majority of VR participants(n=19/25, 76%) reported no nausea or motion sickness. High satisfaction ratings were reported for VR (n=24/29, 83%) and audio(n=26/33, 72%). For VR efficacy, symptom improvement over time was found for each pain variable (all P<.001), with results
strengthening after 2 weeks. Importantly, significant time×group effects were found in favor of the VR group for average pain
intensity (P=.04), pain-related inference with activity (P=.005), sleep (P<.001), mood (P<.001), and stress (P=.003). For pain
catastrophizing and pain self-efficacy, we found a significant declining trend for both treatment groups.
Conclusions: High engagement and satisfaction combined with low levels of adverse effects support the feasibility andacceptability of at-home skills-based VR for chronic pain. A significant reduction in pain outcomes over the course of the 21-day
treatment both within the VR group and compared with an audio-only version suggests that VR has the potential to provide
enhanced treatment and greater improvement across a range of pain outcomes. These findings provide a foundation for future
research on VR behavioral interventions for chronic pain.
(JMIR Form Res 2020;4(7):e17293) doi: 10.2196/17293

https://formative.jmir.org/2020/7/e17293

XSL• FO
RenderX

JMIR Form Res 2020 | vol. 4 | iss. 7 | e17293 | p. 1
(page number not for citation purposes)

JMIR FORMATIVE RESEARCH

Darnall et al

KEYWORDS
chronic pain; virtual reality; behavioral medicine; self-management; mobile phone; randomized controlled trial

Introduction
Background
The US Department of Health and Human Services [1,2], theInstitute of Medicine [3], the National Institutes of Health, andthe Centers for Disease Control and Prevention have called forthe integration of evidence-based behavioral medicine strategies
into the treatment of acute and chronic pain. These unified
recommendations reflect a common understanding that pain isa biopsychosocial experience that requires a comprehensive
treatment approach to equip individuals with skills to actively
self-manage pain and symptoms [4].
Evidence-based behavioral pain treatments include cognitive
behavioral therapy (CBT) for chronic pain [5-7], acceptanceand commitment therapy [8], and mindfulness-based stress
reduction [5,6]. Treatments typically include didactic content,
goal setting, and experiential skills practice within sessions andskills practice between sessions. Effective chronic pain
management techniques include biofeedback and relaxation
training, with the latter being the mainstay of every effective
behavioral treatment for chronic pain [9]. Evidence-based
behavioral medicine treatments are commonly delivered
individually or in group format, during treatment classes orsessions that are 1 to 2 hours in duration, with a course oftreatment lasting 8-11 weeks [7]. Behavioral treatments forchronic pain have been shown to be effective for reducing pain
bothersomeness [5,6], symptoms of depression [7,8], andpain-specific cognitive and emotional distress (eg, pain
catastrophizing) [5-7], although these treatments have not beeneffective in reducing pain intensity. Behavioral treatments havealso been shown to be effective for improving pain-related
self-efficacy or confidence in one’s ability to self-manage painand engage in meaningful activities [5,6].
Despite the availability of efficacy data for behavioral
treatments, multiple barriers may prevent patients from broadly
accessing low-risk, integrative, nonpharmacologic pain
self-management tools that address the psychosocial aspects ofchronic pain [10]. Such barriers may include few skilled local
therapists, poor insurance coverage, copayments associated withclinic visits, travel costs, and treatment time [10]. Even when
delivered to participants at no cost, in-person behavioral
medicine treatments can have poor patient engagement [11],thereby suggesting that new methods of treatment delivery are
required to meet the needs of a broad range of patients.
Accordingly, research has demonstrated preliminary efficacy
for an ultrabrief, single-session, skills-based behavioral
treatment class for chronic pain [12] as well as for mobile healthteleconference-delivered multisession behavioral pain treatment[13]. Although both options offer new conveniences andpossibly expanded access to care, particularly for patients withmobility limitations, the patient remains dependent on a therapist
for the delivery of the treatment.
Digital therapeutics offer independent, home-based, on-demand
access to behavioral treatment for acute and chronic pain. For
https://formative.jmir.org/2020/7/e17293

XSL• FO
RenderX

instance, a brief, web-based, 90-min, skilled-based pain
treatment was shown to reduce postsurgical opioid use in women
who underwent surgery for breast cancer [14]. For chronic pain,
digital multisession interventions have been shown to beeffective [15-17]. Despite these successes, any one modality
will not meet the needs of everyone; indeed, even web-based
pain treatments that are offered at no cost have <60%
engagement rates [14], thus underscoring the need to offer adiverse range of accessible treatment options for chronic pain
and, in particular, to identify treatments that may yield superior
outcomes.
Virtual reality (VR) has emerged as an effective digital treatment
for acute pain. With VR, the user wears a headset that fully
restricts the vision field to the content displayed inside theheadset screen, and auditory perception is directed to the audiodelivered through the device (although not fully restricted;
Figure 1). VR provides a multisensory, 3D immersive
environment that stimulates the visual, auditory, andproprioception senses, thus engendering the perceptual
experience that one is physically located inside and engaged
with the virtual environment they are viewing [18,19], such as
swimming with dolphins (Figure 2). VR has been used innumerous clinical settings and health conditions to treat anxiety
and mental disorders [20-22], aids physical rehabilitation[23,24], and supports postsurgical recovery. Evidence suggeststhat VR is effective for managing acute pain, including pain
elicited during medical procedures [25-29], and burn woundcare [30,31] and in hospitalized patients [32,33].
Although several studies have investigated VR for chronic pain,
the literature to date is limited. Promising studies have used VR
to reduce pain and improve outcomes in complex regional pain
syndrome [34], chronic headache/migraine pain [35],fibromyalgia [36,37], and chronic musculoskeletal pain [38,39].
Two recent reviews and meta-analyses reported the efficacy of
VR for physical rehabilitation from painful spinal conditions[24] and for orthopedic rehabilitation in terms of reduced painand disability [40]. In such studies, the user may engage withinteractive VR alone or within the context of kinematic training.
The literature to date is limited by studies that are conducted inexperimental or clinical settings, do not compare to a non-VRgroup, or include very small samples. Most importantly, theVR studies to date are focused primarily on distraction or
physical rehabilitation and do not include pain management
education or cultivation of behavioral pain self-management
skills (eg, diaphragmatic breathing or cognition and emotion
regulation). Crucially, if found to be effectively delivered by
VR, such content could serve as either a replacement or
treatment extender for in-person behavioral medicine clinic
visits. Studies are needed to determine whether behavioral pain
management skills-based VR is effective and can facilitatesustained pain relief through skills mastery and increased
self-efficacy for pain self-management. The VR platform could
transcend many current barriers to care and potentially provide
a scalable way to deliver on-demand home-based behavioral
treatment for chronic pain.
JMIR Form Res 2020 | vol. 4 | iss. 7 | e17293 | p. 2
(page number not for citation purposes)

JMIR FORMATIVE RESEARCH

Darnall et al

Figure 1. Oculus Go virtual reality headset.

Figure 2. Image of Pain Care virtual reality content (swimming with dolphins).

Objectives
Building on the nascent literature on VR for chronic pain, we
aim to evaluate a skills-based behavioral medicine VR programfor chronic low back pain and fibromyalgia to provide
preliminary data on its utility and efficacy as a stand-alone
home-based treatment for people in the community. To
accomplish this goal, we conducted an exploratory randomized
controlled trial (RCT) with 3 main aims: (1) to determine thefeasibility and satisfaction of a self-administered, at-home,skills-based 21-day VR intervention (pain care VR) for chronic
pain; (2) to evaluate the preliminary efficacy of VR intervention
for reducing average pain intensity and pain-related outcomes;and (3) to isolate the immersive effects of VR by comparing it
https://formative.jmir.org/2020/7/e17293

XSL• FO
RenderX

with an audio-only treatment group. We hypothesized good
feasibility and satisfaction for VR as well as the superiority of
VR over audio treatment for pre-post improvement across thepain indicator variables.

Methods
Design and SettingThis was a parallel-group, randomized controlled clinical trial
involving 2 home-based behavioral interventions applied in acommunity-based, web-based convenience sample of people
with chronic pain conducted between March and May 2019.

JMIR Form Res 2020 | vol. 4 | iss. 7 | e17293 | p. 3
(page number not for citation purposes)

JMIR FORMATIVE RESEARCH

Procedures
Participants were recruited remotely through web-based
advertisements on Facebook and The Mighty, a digital healthcommunity. Internet and computer literacy were implicit defacto eligibility criteria. Eligibility screening involved a brief
telephone assessment for enrollment criteria outlined in the
Inclusion and Exclusion Criteria section.

Inclusion and Exclusion Criteria
Following electronic informed consent (see Multimedia
Appendix 1 for the study consent form), study participants wererandomized one-to-one using a Research Electronic Data
Capture Cloud random number generator and allocated to thetreatment group. All study procedures were completed remotely,and no in-person visits were required. Study participants were
not blinded to the treatment group assignment because of theobvious nature of the mode of delivery of their assigned
treatment. Participants assigned to the VR group were called
by a study staff to ensure receipt of the mailed VR kit and fora brief orientation to materials. A study staff member wasavailable by phone at the request of study participants in bothgroups. Participant compensation was prorated based on thenumber of surveys completed; they received up to US $30 in
the form of an Amazon electronic gift card following completionof their final study survey. The study was approved by theWestern institutional review board (Puyallup, WA).

Darnall et alvariety of sessions to support participants in learning
self-management skills based on evidence-based CBT principles
as well as biofeedback and mindfulness strategies used in pain
management. The program was designed to improveself-regulation of cognitive, emotional, and physiologicalresponses to stress and pain and comprised 3 main content
categories:••

Treatment Groups
Both treatment groups received the same didactic content
delivered in distinct formats (VR versus audio; see Multimedia
Appendix 2 for program content). Treatment consisted of a•

Skills rooted in pain CBT: brief didactics describe how
thoughts and emotions can impact pain and techniques on
thought restructuring and adaptive regulation of pain-related
cognition and emotion (eg, addressing pain catastrophizing
tendencies).
Relaxation training: participants engage in diaphragmatic
breathing exercises to enhance parasympathetic nervous
system function and decrease physiological hyperarousal.
Importantly, relaxation training was optimized in the VR
group with visual biofeedback that displayed theenvironment responding to the users’ physiologic behavior
during the exercises (Figure 3). The software uses apatent-pending algorithm to detect the user’s exhalations
with the VR headset’s built-in microphone, along with ahardware breath amplifier that directs the user’s breath
toward the microphone. The user’s breath is then visualized
in the VR environment as either breath particles or waves
expanding outward from the user, with the synchronizationof physical exhalation and the visual effects deepening theimmersion of the experience and helping the user slow anddeepen their respiration.
Mindfulness: mindfulness content encouraged awarenessof the mind and body (somatic cues) as well as thoughtrelease (nonattachment).

Figure 3. Image of Pain Care virtual reality content that visualizes the user’s breath.

https://formative.jmir.org/2020/7/e17293

XSL• FO
RenderX

JMIR Form Res 2020 | vol. 4 | iss. 7 | e17293 | p. 4
(page number not for citation purposes)

JMIR FORMATIVE RESEARCH

Darnall et al

The 21-day program consisted of 4-8 treatment sessions fromeach content category with the duration of session length ranging
from 1 to 15 min. Each treatment session was indexed ascomplete if the participants initiated the experience. Participants
could replay the completed sessions.

Measures

Virtual Reality Group

Average Pain Intensity

VR group participants were mailed an Oculus Go VR headset
preloaded with VR software developed by AppliedVR. The
Oculus Go is an easy-to-use, stand-alone VR headset with anaccompanying orientation-tracked controller, a head-mounted
display with a high-resolution screen, built-in spatial audio
speakers, and an integrated microphone. A VR user manual sent
via email included an instructional video on the proper use of
the VR headset. Participants were instructed to telephone VR
support staff if they had any questions or difficulty in using theheadset. Participants were instructed to complete 1 VR treatment
session daily for 21 days (Multimedia Appendix 2).

The average pain intensity was rated for the previous 24 hours
using an 11-point numeric rating scale (0=no pain and 10=as
bad as it could be; nothing else matters). The average pain
intensity was assessed pretreatment (baseline), during treatment,
and at the end of treatment on day 21.

Audio GroupThe audio program consisted of the majority of the samenarrative content contained in the VR program, with changes
made to the descriptive titles for each session. Owing to VR
having a visual media form and audio that specifically references
the changing images in the VR environment, approximately
one-third of the VR program could not be included verbatim in
the audio. Rather, the audio session topical content was closely
matched to the corresponding VR session for that day andadapted to eliminate any references to visual content that would
be confusing to the listener. Participants received an electronic
link to the audio recordings on SoundCloud (a music streaming
platform) where they could choose to stream or download theaudio recordings on their smartphones, laptops, or desktop
computers. Participants were instructed to complete 1 audio
treatment session daily for 21 days (Multimedia Appendix 2).

Data Collection and Variable Measurement
Data collection consisted of electronically collectedpatient-reported measures and objective use data collected fromthe VR devices and audio access logs.
In accordance with the Initiative on Methods, Measurement,
and Pain Assessment in Clinical Trials (IMMPACT)
recommendations, we included multiple methods to evaluate
the importance of change in outcome measures across 4
recommended domains: pain intensity, health-related qualityof life as defined by physical functioning, emotional functioning,
and ratings of overall improvement [41,42].

Data Collection Time Points
Data were collected across 4 phases of the study: screening,
pretreatment baseline, treatment, and posttreatment (day 22).
The pretreatment baseline assessment period involved 3 survey
time points: days −9, −6, and −3 (averaged to create a single
pretreatment baseline value). Surveys were distributed 7 times
during the active treatment period (days 1, 3, 6, 9, 12, 15, and18) and posttreatment on days 21 and 22.

https://formative.jmir.org/2020/7/e17293

XSL• FO
RenderX

The Defense and Veterans Pain Rating Scale (DVPRS) [43]was used to measure average pain intensity, and the DVPRS
interference scale was used to measure pain interference on
activity, sleep, mood, and stress over the past 24 hours [44].

Pain Interference on Activity, Mood, Sleep, and StressParticipants were asked to rate the extent to which their paininterfered with their activity, mood, sleep, and stress over the
past 24 hours (0=does not interfere and 10=completelyinterferes). Pain interference was assessed pretreatment(baseline), during treatment, and at the end of treatment on day
21.

Pain Catastrophizing
The 13-item Pain Catastrophizing Scale (PCS) [45] is a validated
instrument widely used clinically and in pain research to assess
patterns of negative cognition and emotion in the context ofactual or anticipated pain. Despite having discrete subscales forrumination, magnification, and feelings of helplessness related
to pain, prior work has shown that the PCS operates
unidimensionally [46]. For this study and the purpose of brevity,
the following 4 items were used: “It’s terrible and I think it’s
never going to get any better,” “I become afraid that the pain
will get worse,” “I can’t seem to keep it out of my mind,” and“I keep thinking about how badly I want the pain to stop.”
Respondents rate the frequency in which they experience suchthoughts on a scale ranging from 0 (not at all) to 4 (all the time).
The items are summed to create a total score and index for pain
catastrophizing. The four-item PCS was administered on day 0(baseline) and on day 22.

Pain Self-Efficacy
The two-item Pain Self-Efficacy Questionnaire (PSEQ-2) is avalidated instrument used to assess patients’ confidence in theirability to carry out their daily activities [47]. The scale includes
the following 2 items: “I can still accomplish most of my goals
in life, despite the pain” and “I can live a normal lifestyle,despite the pain.” Respondents rate their responses to the items
using a 7-point scale, ranging from 0 (not at all confident) to 4(completely confident). The two-item scores are summed tocreate a total score. PSEQ-2 was administered on day 0(baseline) and on day 22.

Patient Global Impression of Change
Aligning with IMMPACT recommendations for pain research[48], Patient Global Impression of Change was assessed on day
22 (posttreatment survey) using the question, “Since thebeginning of the study, how has your pain changed?” on a
7-point scale, ranging from much worse to much better.

JMIR Form Res 2020 | vol. 4 | iss. 7 | e17293 | p. 5
(page number not for citation purposes)

JMIR FORMATIVE RESEARCH

Satisfaction With Treatment
Satisfaction with treatment was assessed on day 22(posttreatment survey) using the question, “How satisfied ordissatisfied are you with the ability of this VR (audio) program
to relieve your symptoms?” on a 5-point scale (1=extremely
dissatisfied to 5=extremely satisfied).

Motion Sickness and Nausea
Adverse experiences with using VR were assessed on day 22(posttreatment survey) using the question, “Did you experienceany motion sickness or nausea while using VR?” on a 4-point
scale, with 0=never, 1=sometimes, 2=often, and 3=always. This
single-item evaluation of cybersickness was adapted from related
work on visual images and motion sickness.

Study Sample and Analytic Data Set
A convenience sample of 97 participants who met all study
criteria was enrolled, randomized, and allocated to the VR oraudio treatment groups (VR=47 and audio=50). Of 97
participants, 88 (VR=42 and audio=46) provided pretreatmentbaseline values for the 5 pain indicators and moved to theintervention phase of the study. Of the 88 participants, 74(VR=35 and audio=39) completed at least one survey over the
21-day treatment phase. The analytic sample comprised 74
participants who completed the baseline measures and at least
one survey during the intervention phase.

Statistical Analysis
The feasibility of the VR treatment was indexed using 3 aspectsof the participants’ experience: engagement, satisfaction, andadverse effects nausea/discomfort. For engagement,
individual-level session data exist only for the VR group; assuch, we presented a descriptive statistic of the total number ofsessions launched by the VR and audio groups. Groupdifferences in posttreatment satisfaction (day 22) were assessedusing a t test. For nausea and discomfort, we provided the
proportion of participants who did not experience any
nausea/discomfort.
With regard to the secondary outcome of the efficacy of the VR
treatment on the 5 pain-related indicators (average pain intensityand pain interference with activity, mood, sleep, and stress), we
specified a repeated measures model with time of measurement(henceforth time) as the sole predictor. The effect of interest
was whether there was a significant improvement in the 5 pain
indicators from baseline through the end of treatment, assessed
through the significance of the main effect for time. To test theimmersive effects of VR relative to audio treatment, we analyzed

https://formative.jmir.org/2020/7/e17293

XSL• FO
RenderX

Darnall et aleach of the 5 pain indicators in a linear mixed model frameworkin which treatment (VR versus audio) was specified as a
between-participants factor and time was specified as awithin-participants factor with participant-specific intercept andtime specified as random effects. The effect of interest waswhether the improvement in the pain indicators was different
for the VR versus the audio group over time, which was assessed
through the significance of the group×time interaction.
Posttreatment effect sizes (baseline to treatment completion at
day 21) were computed by treatment group using an adaptationof Cohen d to suit the repeated measures design [49].
The four-item PCS and two-item PSEQ scales were analyzed
in a mixed modeling framework, except that there were only 2time points (baseline day 0 and day 22). We aimed to test 3
questions: (1) whether pain catastrophizing reduced over timeand pain self-efficacy increased over time, both assessed throughthe significance of the time main effect; (2) whether the VR
versus audio group had a differential effect, assessed throughthe group main effect; and (3) whether the immersive aspect of
VR produced a differential impact compared with audio overtime, assessed through a time×group interaction.
Group equivalence was assessed through univariate tests ofassociation between treatment groups (VR/audio) on
demographics (age, gender, race, household income, numberof children ≥17 in the home, employment status, and relationshipstatus), anhedonia, depression, and baseline levels of pain
intensity and pain-related interference to sleep, activity, stress,and mood.

Results
Sample Characteristics
No significant differences were found between the VR and audiogroups for baseline demographic, anhedonia, and depression
variables (Table 1). Treatment groups differed in duration ofpain since onset, with the VR group having greater pain duration
as indexed by the following. Pain duration of 1 year to <5 years
represented 40% (14/35) of the VR group and 21% (8/39) of
the audio group, whereas pain duration of <1 year represented
3% (1/35) of the VR group and 21% (8/39) of the audio group(P=.03).
Furthermore, the baseline values for average pain intensity andpain-related interference with activity, mood, sleep, and stresswere found to be equivalent between the study groups (all P
values>.29; Multimedia Appendix 3).

JMIR Form Res 2020 | vol. 4 | iss. 7 | e17293 | p. 6
(page number not for citation purposes)

JMIR FORMATIVE RESEARCH

Darnall et al

Table 1. Participant characteristics by treatment group (N=74).
Variable

Audio (n=39)

Virtual reality (n=35)

Gender, n (%)

.47

Male

26 (67)26 (74)

Female13 (33)9 (26)

Age group (years), n (%)

.63

25-34

3 (8)

3 (9)

35-44

8 (21)

5 (14)

45-54

12 (31)

11 (31)55-64

7 (18)

11 (31)65-74

9 (23)

5 (14)

Race, n (%).63

Missing

2 (5)

6 (17)

African American

3 (8)4 (14)

Asian

2 (5)

0 (0)

White

28 (76)21 (72)

Hispanic/Latino

2 (5)

3 (10)

Multiracial/other

1 (3)

0 (0)

Native American/Pacific Islander

1 (3)

1 (3)

Education, n (%).17

Missing

2 (5)

6 (17)

Some high school

3 (8)

0 (0)

High school graduate

11 (30)14 (48)

Some college

2 (5)4 (14)

Bachelor degree

13 (35)6 (21)

Postgraduate

8 (22)

5 (17)

Employment, n (%).75

Missing

2 (5)

6 (17)

Full time

16 (43)

11 (38)

Part time

7 (19)

9 (31)

Not working

3 (8)3 (10)

Retired

1 (3)

1 (3)

Unable to work

10 (27)5 (17)

Marital status, n (%).16

Missing

2 (5)

6 (17)

Married/civil union

16 (43)15 (52)

Widowed

1 (3)

1 (3)

Divorced/separated

5 (14)

5 (17)

Single/cohabitating

1 (3)4 (14)

Single14 (38)4 (14)

Pain onset, n (%)

XSL• FO
RenderX.03

6 months to <1 year

8 (21)1 (3)

1 year to <5 years

8 (21)

14 (40)5 years to <10 years

10 (26)

13 (37)https://formative.jmir.org/2020/7/e17293

P valuea

JMIR Form Res 2020 | vol. 4 | iss. 7 | e17293 | p. 7
(page number not for citation purposes)

JMIR FORMATIVE RESEARCH
Variable>10 years

Darnall et al
Audio (n=39)

Virtual reality (n=35)

13 (33)7 (20)

Anhedonia.20

Mean (SD)

1.4 (0.8)

1.1 (0.8)

Minimum to maximum

0.0-3.0

0.0-3.0

Median (IQR)

1.0 (1.0-2)

1.0 (1.0-2)

Depressiona

P valuea.15

Mean (SD)

1.2 (0.7)

0.9 (0.7)

Minimum to maximum

0.0-3.0

0.0-3.0

Median (IQR)

1.0 (1.0-2)

1.0 (0.0-1)

The P values represent the parametric test of significant differences between the virtual reality and audio conditions [50].

Feasibility of At-Home Virtual Reality Interventions
for Chronic Pain
This study was designed to provide indicators for feasibility(indexed by participant engagement, satisfaction, and adverse
effects) for an at-home self-administered 3-week VR chronic
pain treatment program. In the following section, we reported
the results for these 3 feasibility indicators.

Participant Engagement (Number of Treatment Sessions
Completed)
Participants were encouraged to follow the 21-day treatment
schedule and told they could repeat any completed experiencesat any time. In contrast to the VR group, individual-level session
launch data do not exist for the audio group, and engagement
data exist only at the group level. As such, we limited thedescription to the total number of sessions launched by thetreatment group for the study period. We observed a total of1048 and 1067 sessions launched in the audio group and the
VR group, respectively (these group-level data do not accountfor discrepancy in group size). VR participants completed anaverage of 34.4 sessions (SD 20.30), which exceeded theminimum number (21 sessions) they were asked to complete.
Overall, 54 participants responded to the day 22 survey(audio=29 and VR=25), which included items on satisfaction
with treatment and motion sickness and nausea (for the VR
group).

Treatment Satisfaction
Among participants who completed the postintervention survey(n=54), 84% (n=21/25) of participants in the VR group and 72%(n=21/29) of participants in the audio group were either
extremely satisfied or very satisfied.

Motion Sickness and Nausea
Of the 25 VR respondents who completed the day 22 survey,
76% (n=19/25) reported never experiencing nausea or motion
sickness. Of the 6 participants who reported nausea or motion
sickness, 5 reported experiencing the lowest possible symptom
frequency (sometimes) and 1 participant reported experiencing
it often. We tested whether motion sickness and nausea impacted
the engagement with the VR treatment by examining the numberof VR sessions launched for those with sometimes (n=5) andoften (n=1) nausea/motion sickness and the remainder of thehttps://formative.jmir.org/2020/7/e17293

XSL• FO
RenderX

VR group (n=29). We found that experiencing nausea/motion
sickness at the lowest level did not negatively impact the useof VR, as indexed by the number of sessions launched (36sessions versus 33 sessions for the remainder of the VR group).
However, the single individual who reported nausea/motion
sickness often launched only one-third of the number of sessions
compared with the remainder of the VR group (11 sessions
versus 33 sessions).

Survey Completion
There was no group difference for completion of the 8 treatment
surveys administered during and immediately following the
21-day treatment period (VR=5.5 and audio=5.6; P=.89).

Preliminary Efficacy on Patient-Reported Outcomes(Virtual Reality Group Only)
For the VR group, we found significant effects on each of the
5 pain indicators using the repeated measures model in whichtime was the sole predictor (all P<.001). For brevity and clarity,
we included only the baseline and 21-day mean values in the
text but provided the mean values for all time points in the
figures. The average reductions from baseline through day 21
were as follows: pain intensity was reduced by 30% (meanreduced from 4.6 to 3.2; Cohen d effect size of 0.71),
pain-related activity interference reduced by 37% (mean reduced
from 4.9 to 3.1; Cohen d effect size of 0.83), pain-related moodinterference reduced by 50.0% (mean reduced from 5.4 to 2.7;
Cohen d effect size of 0.94), pain-related sleep interference
reduced by 40.4% (mean reduced from 5.2 to 3.1; Cohen d effectsize of 0.87), and pain-related stress interference reduced by
49.1% (mean reduced from 5.3 to 2.7; Cohen d effect size of0.89). All the aforementioned effect sizes met or exceeded the>30% threshold for clinically important changes, andimprovement in pain-related mood interference met thesubstantial clinical importance threshold of >50% [48,51].

Comparison Between the Virtual Reality and Audio
Treatment Groups
The 5 figures below (Figures 4-8) compared group effects overtime for the 5 pain indicators. For all figures, the trend of thepain-related variable was displayed over time for participantsin the VR and audio groups. Values in the x-axis refer to thenumber of days in the study, where 0 represents the baseline
JMIR Form Res 2020 | vol. 4 | iss. 7 | e17293 | p. 8
(page number not for citation purposes)

JMIR FORMATIVE RESEARCH
computed as the average of the 3 preexposure measures on −9,−6, and −3 days before the start of the treatment.

Average Pain Intensity
Pain intensity decreased over time in both groups, and thedecline was steeper for the VR and audio groups (P=.04), withdifferences becoming more pronounced from day 15 onward.

Darnall et al
It should be noted that none of the simple effects (ie, effect ofgroup within time slice) are significant (Figure 4). As seen in
Multimedia Appendix 4, from baseline to day 21, consistent
with the time×group interaction, the Cohen d was smaller in
the audio group than in the VR group (0.42 and 0.71,
respectively).

Figure 4. Effect of virtual reality vs audio on pain intensity over time.

Pain-Related Activity Interference
Activity interference decreased more steeply in the VR groupthan in the audio group (P=.005), with differences becoming
more pronounced from day 15 onward (Figure 5). The simple

https://formative.jmir.org/2020/7/e17293

XSL• FO
RenderX

effect (ie, effect of group within time slice) was significant at
day 18 (VR<audio; P=.02). As seen in Multimedia Appendix
4, Cohen d was smaller in the audio group than in the VR group(0.26 and 0.83, respectively).

JMIR Form Res 2020 | vol. 4 | iss. 7 | e17293 | p. 9
(page number not for citation purposes)

JMIR FORMATIVE RESEARCH

Darnall et al

Figure 5. Effect of virtual reality vs audio on pain-related activity interference over time.

Pain-Related Mood Interference
As shown in Figure 6, mood interference appeared to decrease
more steeply in the VR group than in the audio group. The
difference between the VR and audio groups became morehttps://formative.jmir.org/2020/7/e17293

XSL• FO
RenderX

pronounced from day 15 onward. The simple effect (ie, effectof group within time slice) was significant at day 18 (VR<audio;
P<.001). As seen in Multimedia Appendix 4, Cohen d wassmaller in the audio group than in the VR group (0.76 and 0.94,
respectively).

JMIR Form Res 2020 | vol. 4 | iss. 7 | e17293 | p. 10(page number not for citation purposes)

JMIR FORMATIVE RESEARCH

Darnall et al

Figure 6. Effect of virtual reality vs audio on pain-related mood interference over time.

Pain-Related Sleep Interference

reaching significance at day 1 (audio<VR; P=.02) and on day
18 (VR<audio, Figure 7; P=.002).

Reductions in sleep interference were greater in the VR group,with the simple effects (ie, effect of group within time slice)https://formative.jmir.org/2020/7/e17293

XSL• FO
RenderX

JMIR Form Res 2020 | vol. 4 | iss. 7 | e17293 | p. 11(page number not for citation purposes)

JMIR FORMATIVE RESEARCH

Darnall et al

Figure 7. Effect of virtual reality vs audio on pain-related sleep interference over time.

As seen in Multimedia Appendix 4, Cohen d was smaller in theaudio group than in the VR group (0.64 and 0.87, respectively).

Pain-Related Stress Interference
As shown in Figure 8, stress interference appeared to decrease
more steeply in the VR group compared with the audio group,https://formative.jmir.org/2020/7/e17293

XSL• FO
RenderX

and this difference was more pronounced from day 15 onward.
The simple effect (ie, effect of group within time slice) was
significant on day 18 (P=.01). As seen in Multimedia Appendix
4, Cohen d was smaller in the audio group than in the VR group(0.87 and 0.89, respectively).

JMIR Form Res 2020 | vol. 4 | iss. 7 | e17293 | p. 12(page number not for citation purposes)

JMIR FORMATIVE RESEARCH

Darnall et al

Figure 8. Effect of virtual reality vs audio on pain-related stress interference over time.

Pain Catastrophizing

were preserved with one exception; the time×treatment
interaction was no longer significant.

We observed a significant main effect of time, with pain
catastrophizing decreasing for both groups over time (P<.001).
The main effect for group was not significant (P=.61). Finally,
we did not perform a time×group interaction (P=.52).

Discussion

Pain Self-Efficacy
We observed a significant main effect of time, with pain
self-efficacy increasing in both groups over time (P<.047). The
main effect for group was not significant (P=.68). Finally, we
did not perform a time×group interaction (P=.46).

Global Impression of Change
At day 22, among survey responders (n=54), 84% (n=21/25) ofparticipants in the VR group reported that their pain was
improved, 16% (n=4/25) reported no change, and 0% (n=0/25)
reported worsening pain. In the audio group, 62% (n=18/29) ofparticipants reported improvement, 34% (n=10/29) reported nochange, and 3% (n=1/29) reported worsening pain.
Finally, because of the observed group difference in the durationof chronic pain (indexed as pain onset in Table 1), we conducted
additional analyses with pain onset specified as a covariate in
the model with time, group, and time×group as predictors of
the 5 pain variables. The significance of the time main effectand time×group interaction effects was fully preserved. Whenintention-to-treat (ITT) analyses were applied all of the results
https://formative.jmir.org/2020/7/e17293

XSL• FO
RenderX

Principal Findings
We conducted an unblinded randomized controlled study in a
web-based convenience sample of community-based participants
with nonmalignant chronic low back pain and/or fibromyalgia
by comparing at-home self-administered VR treatment with anaudio-only treatment group (same audio content as VR withminor modifications made for one-third of the modules). The
primary goal of the study was to evaluate the feasibility of aself-administered home-based VR program for chronic painthat included skills-based content informed by evidence-based
CBT for chronic pain. The secondary goal was to conduct an
RCT of the VR treatment to an audio-only treatment. We aimed
to determine the preliminary efficacy of VR for reducing averagepain intensity and pain-related interference with activity, mood,sleep, and stress over the 21-day treatment program. Our tertiary
goal was to isolate the immersive effects of the skills-based VR
program by comparing the effects between treatment groups.
VR demonstrated good feasibility as indexed by excellent
participant engagement (average of 34 sessions completed overthe 21-day treatment program), high ratings for satisfaction withthe treatment (84%), and relatively low reporting for motion
sickness and nausea (n=6/25, 24% of VR participants who
JMIR Form Res 2020 | vol. 4 | iss. 7 | e17293 | p. 13(page number not for citation purposes)

JMIR FORMATIVE RESEARCH
completed the day 22 survey). Of these 6 participants, 5 reported
the lowest level of symptom frequency possible (sometimes).
We found that this symptom level did not interfere with VR
treatment engagement, as indexed by the number of sessions
launched compared with participants in the remainder of the
VR group. The single individual who experienced nausea andmotion sickness often showed markedly decreased use of VR(11 sessions launched versus 34 for people with low nausea andthe remainder of the VR group).
With respect to preliminary efficacy, VR demonstrated thesignificant reduction in average pain intensity and pain-related
interference in activity, mood, sleep, and stress over the courseof the 21-day treatment program. Treatment effect sizes
suggested that a home-based stand-alone, digital, skills-based
treatment program may affect clinically meaningful changes inpatient-reported pain and pain correlates. The durability of thetreatment effects reported here remains a topic for future
research.
Although a significant body of research exists on the use of VR
for acute pain management [26,28,30,52-54] and for physicalrehabilitation [24,40], the use of VR as a platform to deliver
behavioral medicine for chronic pain remains novel andunderstudied. Research on VR for acute pain is based on thepremise that distraction is a primary mechanism of VR analgesia[33,55]. Therefore, the effects of distraction on pain are typicallymeasured within a rapid time frame using study designs thatalign with drug trials. Investigations of VR for chronic pain
require a different approach to align with the goal of sustained
pain management. Although VR for physical rehabilitationshows sustained results, content is typically constrained torehabilitative movement, exercise, and kinematic training[24,40] and is devoid of didactics and skills training containedin evidence-based behavioral medicine treatments [7].
Unlike distraction alone, behavioral health therapies rarely
produce instantaneous results. Rather, skills acquisition andmastery require time, in part because of the multisession deliveryof content, and become effective over the course of weeks, as
the content is delivered more comprehensively, and patientspractice skills during and between sessions and is correlatedwith patient engagement [56]. Our prior work suggests that an
ultrabrief skill-based intervention for chronic pain evidenced
clinically meaningful improvements in pain-related symptoms
at 2 weeks, with even greater improvements evidenced at 4
weeks [12]. The results presented here dovetail with thisliterature and our fundamental understanding of how didactic
and skills-based behavioral medicine treatment results accrue
over time as participants receiving increasing amounts ofknowledge and skills practice during active treatment [6,56,57].
In this study, the emergence of a more pronounced improvementin pain outcomes at day 15 supports the hypothesis that thedidactic and skills-based elements of immersive behavioral
medicine VR are operating as expected, although confirmatory
studies are needed.
In evaluating the method of delivery of a skills-based treatment
program, this study demonstrated superior reduction of mostpain indicators in the VR group relative to the audio group after
2 weeks. Treatment group differences remained minimal until
https://formative.jmir.org/2020/7/e17293

XSL• FO
RenderX

Darnall et alday 12, with VR superiority strengthening from day 15 onward
and peaking on day 18. For the pain interference outcomes, theVR group showed greater improvement compared with theaudio group. The exceptions were pain catastrophizing and pain
self-efficacy, which improved for both treatment groups. We
have no evidence that VR’s superior treatment effects wereexplained by user engagement, as we observed similar rates ofengagement for both groups. Our study design allowed us toisolate the immersive effect of VR relative to active treatment
delivered via audio format only. On balance, our findings
suggest that the treatment effect sizes for VR are both
statistically significant and clinically meaningful for pain
intensity and across the pain interference variables and aresuperior to the same treatment delivered by audio alone. A key
aspect of the immersive VR experience involves dynamic
interaction between the user’s breath and the environment,
wherein voice-over coaching directs the user to slow the breath
to engage a parasympathetic response. The environment
responds to the breath, provides visual feedback to the user, andpossibly affords users enhanced acquisition of this skill relative
to the audio-only content.

Strengths and Limitations
The strengths and limitations of our study bear careful attention.
The interpretation of study findings is limited by the 2 pain
conditions studied and the selection bias inherent in the
web-based convenience sample. In addition, the analytic data
set included only those participants who completed at least one
study survey; accordingly, larger studies are needed to confirm
the findings reported here and to determine generalizability.
Medication use was not assessed and may have been a
confounding variable. Chronic pain type and duration wereself-reported, and there was no review of medical records toconfirm diagnoses. Our ability to assess VR satisfaction andnausea/motion sickness was limited by only 25 of 35 participants
completing the day 22 posttreatment survey. Although only
17% of the full VR sample reported experiencing cybersickness
to any degree, we cannot rule out the possibility that early
attrition may be partially attributable to these adverse effects,
although notably, we did not find disparate attrition rates
between the VR and audio groups. Commercially available VRprograms typically offer a money-back guarantee trial period
to allow customers to return their VR device for refund in casesof cybersickness. Although assignment to treatment group was
random, differences in duration of pain since onset between the
2 treatment groups may have influenced pain outcomes during
the course of the study, and we note that this difference favored
the audio group. In addition, the analysis did not focus on thecorrelation between individual-level variations in the use of theintervention (VR or audio) and the pain indicators, and thisremains a topic for future study.
Our study design merits consideration within the context of ourfindings. The audio treatment group was an active comparator
with two-thirds of the audio content identical to the audio of
the VR group, and one-third of the audio content closely
matched the VR content for topical content, skills, andexperience (minus the visual and interactive elements). This
study was rigorously designed to isolate the immersive effectsof VR rather than simply comparing VR with placebo or withJMIR Form Res 2020 | vol. 4 | iss. 7 | e17293 | p. 14(page number not for citation purposes)

JMIR FORMATIVE RESEARCH
a weaker control group such as usual care. In studying atreatment delivered 2 ways, our results suggest that theimmersive (3D visual elements, dynamic scenery, and360-degree vision capability) and user interactivity with theenvironment are pleasing, engaging, and generally effective forthose who do not experience cybersickness (many commercial
VR companies offer consumers a trial period or money-backguarantee for cases of cybersickness).
Finally, the cost-effectiveness of VR for chronic pain relative
to in-person behavioral medicine visits or other digital treatment
options merits investigation. In-person behavioral medicine
treatments require multiple clinic visits, travel costs, time fromwork and other obligations, and treatment copayment costs that
may total several hundreds of dollars over a standard 8-session
treatment package. Future research should compare home-based
VR to in-person multisession CBT for chronic pain in terms ofefficacy and cost-effectiveness. Although some 2D digitaltreatment options, such as web-based pain CBT or
self-management programs, and may be sourced at no cost,engagement rates remain relatively low. Future research may

Darnall et al
explore participants’ perceived comparative value of VR toaudio-only treatment. VR provides patients and clinicians witha new home-based treatment option that may be preferred bysome patients and also provide more effective pain management
to a subset of individuals. Additional studies of longer duration
may investigate the durability of treatment effects reported here.

Conclusions
This study is one of the first to explore how a self-administeredhome-based VR program rooted in behavioral medicine skills
and techniques impacts chronic pain. The findings broadly
suggest that VR holds promise as effective, stand-alone,home-based digital behavioral medicine for chronic pain.
Additional studies are needed, including larger sample sizes,
diverse chronic pain conditions, longer duration of study to best
characterize the efficacy of VR in chronic pain management,
and the impact of VR on other factors such as pain medication
use and medical care utilization. Future studies may further
elucidate the VR mechanisms of action and VR’s role inexpanding access to multimodal behavioral medicine for chronicpain.

Acknowledgments
This study was financially supported by AppliedVR.

Conflicts of Interest
BD is employed as a chief scientific adviser to AppliedVR. PK serves as a consultant for AppliedVR.

Multimedia Appendix 1
Participant consent form.
[DOC File , 84 KB-Multimedia Appendix 1]

Multimedia Appendix 2
Schedule of 21-day virtual reality and audio programs.
[DOCX File , 14 KB-Multimedia Appendix 2]

Multimedia Appendix 3
Baseline pain-related variables by treatment group.
[DOCX File , 17 KB-Multimedia Appendix 3]

Multimedia Appendix 4
Effect sizes for change from baseline to day 21.
[DOCX File , 18 KB-Multimedia Appendix 4]

References
1.
2.
3.

4.

Interagency Pain Research Coordinating Committee - NIH. 2016. National Pain Strategy Overview URL: https://www.
iprcc.nih.gov/National-Pain-Strategy/Overview [accessed 2019-12-10]
The US Department of Health and Human Services. 2019. Pain Management Best Practices: Inter-Agency Task Force
Report URL: https://www.hhs.gov/sites/default/files/pmtf-final-report-2019-05-23.pdf [accessed 2019-11-10]
Board on Health Sciences Policy, Committee on Advancing Pain Research Care and Education, Institute of Medicine.
Relieving Pain in America: A Blueprint for Transforming Prevention, Care, Education, and Research. New York, USA:
National Academies Press; 2011.
International Association for the Study of Pain, Subcommittee on Taxonomy. Classification of chronic pain. Descriptionsof chronic pain syndromes and definitions of pain terms. Pain Suppl 1986;3:S1-226. [Medline: 3461421]

https://formative.jmir.org/2020/7/e17293

XSL• FO
RenderX

JMIR Form Res 2020 | vol. 4 | iss. 7 | e17293 | p. 15(page number not for citation purposes)

JMIR FORMATIVE RESEARCH
5.

6.

7.

8.

9.
10.

11.

12.

13.

14.

15.

16.

17.

18.
19.
20.

21.

22.
23.
24.

Turner JA, Anderson ML, Balderson BH, Cook AJ, Sherman KJ, Cherkin DC. Mindfulness-based stress reduction andcognitive behavioral therapy for chronic low back pain: similar effects on mindfulness, catastrophizing, self-efficacy, andacceptance in a randomized controlled trial. Pain 2016 Nov;157(11):2434-2444 [FREE Full text] [doi:10.1097/j.pain.0000000000000635] [Medline: 27257859]
Cherkin DC, Sherman KJ, Balderson BH, Cook AJ, Anderson ML, Hawkes RJ, et al. Effect of mindfulness-based stress
reduction vs cognitive behavioral therapy or usual care on back pain and functional limitations in adults with chronic low
back pain: a randomized clinical trial. J Am Med Assoc 2016;315(12):1240-1249 [FREE Full text] [doi:10.1001/jama.2016.2323] [Medline: 27002445]
Williams AC, Eccleston C, Morley S. Psychological therapies for the management of chronic pain (excluding headache)in adults. Cochrane Database Syst Rev 2012 Nov 14;11:CD007407 [FREE Full text] [doi: 10.1002/14651858.CD007407.pub3][Medline: 23152245]
Hughes LS, Clark J, Colclough JA, Dale E, McMillan D. Acceptance and commitment therapy (ACT) for chronic pain: asystematic review and meta-analyses. Clin J Pain 2017 Jun;33(6):552-568. [doi: 10.1097/AJP.0000000000000425] [Medline:
27479642]
Darnall B. Psychological Treatment for Patients With Chronic Pain. Washington, DC: American Psychological Association
Press; 2018.
Darnall BD, Scheman J, Davin S, Burns JW, Murphy JL, Wilson AC, et al. Pain psychology: a global needs assessmentand national call to action. Pain Med 2016 Feb;17(2):250-263 [FREE Full text] [doi: 10.1093/pm/pnv095] [Medline:
26803844]
Thorn BE, Pence LB, Ward LC, Kilgo G, Clements KL, Cross TH, et al. A randomized clinical trial of targeted cognitive
behavioral treatment to reduce catastrophizing in chronic headache sufferers. J Pain 2007 Dec;8(12):938-949. [doi:10.1016/j.jpain.2007.06.010] [Medline: 17690017]
Darnall BD, Sturgeon JA, Kao M, Hah JM, Mackey SC. From catastrophizing to recovery: a pilot study of a single-session
treatment for pain catastrophizing. J Pain Res 2014;7:219-226 [FREE Full text] [doi: 10.2147/JPR.S62329] [Medline:
24851056]
Kelleher SA, Winger JG, Dorfman CS, Ingle KK, Moskovich AA, Abernethy AP, et al. A behavioral cancer pain intervention:a randomized noninferiority trial comparing in-person with videoconference delivery. Psychooncology 2019
Aug;28(8):1671-1678. [doi: 10.1002/pon.5141] [Medline: 31162756]
Darnall B, Ziadni MS, Krishnamurthy P, Flood P, Heathcote LC, Mackey IG, et al. 'My surgical success': effect of a digital
behavioral pain medicine intervention on time to opioid cessation after breast cancer surgery-a pilot randomized controlled
clinical trial. Pain Med 2019 Nov 1;20(11):2228-2237 [FREE Full text] [doi: 10.1093/pm/pnz094] [Medline: 31087093]
Palermo TM, Murray C, Aalfs H, Abu-El-Haija M, Barth B, Bellin MD, Consortium for the Study of Chronic Pancreatitis‚
Diabetes and Pancreatic Cancer. Web-based cognitive-behavioral intervention for pain in pediatric acute recurrent andchronic pancreatitis: Protocol of a multicenter randomized controlled trial from the study of chronic pancreatitis, diabetes
and pancreatic cancer (CPDPC). Contemp Clin Trials 2020 Jan;88:105898. [doi: 10.1016/j.cct.2019.105898] [Medline:
31756383]
Fisher E, Law E, Palermo TM, Eccleston C. Psychological therapies (remotely delivered) for the management of chronic
and recurrent pain in children and adolescents. Cochrane Database Syst Rev 2014 May 14;2014:1 [FREE Full text] [doi:10.1002/14651858.CD011118] [Medline: 25221436]
Palermo TM, Wilson AC, Peters M, Lewandowski A, Somhegyi H. Randomized controlled trial of an Internet-deliveredfamily cognitive–behavioral therapy intervention for children and adolescents with chronic pain. Pain 2009
Nov;146(1):205-213 [FREE Full text] [doi: 10.1016/j.pain.2009.07.034] [Medline: 19695776]
Hoffman HG, Richards T, Coda B, Richards A, Sharar SR. The illusion of presence in immersive virtual reality during an
fMRI brain scan. Cyberpsychol Behav 2003 Apr;6(2):127-131. [doi: 10.1089/109493103321640310] [Medline: 12804024]
Gold JI, Belmont KA, Thomas DA. The neurobiology of virtual reality pain attenuation. Cyberpsychol Behav 2007
Aug;10(4):536-544. [doi: 10.1089/cpb.2007.9993] [Medline: 17711362]
Geenen R, Bijlsma JW. Deviations in the endocrine system and brain of patients with fibromyalgia: cause or consequenceof pain and associated features? Ann N Y Acad Sci 2010 Apr;1193:98-110. [doi: 10.1111/j.1749-6632.2009.05290.x][Medline: 20398014]
Nararro-Haro MV, Hoffman HG, Garcia-Palacios A, Sampaio M, Alhalabi W, Hall K, et al. The use of virtual reality tofacilitate mindfulness skills training in dialectical behavioral therapy for borderline personality disorder: a case study. Front
Psychol 2016;7:1573 [FREE Full text] [doi: 10.3389/fpsyg.2016.01573] [Medline: 27853437]
Parsons TD, Rizzo AA. Affective outcomes of virtual reality exposure therapy for anxiety and specific phobias: ameta-analysis. J Behav Ther Exp Psychiatry 2008 Sep;39(3):250-261. [doi: 10.1016/j.jbtep.2007.07.007] [Medline: 17720136]
Parsons TD, Rizzo AA, Rogers S, York P. Virtual reality in paediatric rehabilitation: a review. Dev Neurorehabil 2009
Aug;12(4):224-238. [doi: 10.1080/17518420902991719] [Medline: 19842822]
Ahern MM, Dean LV, Stoddard CC, Agrawal A, Kim K, Cook CE, et al. The effectiveness of virtual reality in patientswith spinal pain: a systematic review and meta-analysis. Pain Pract 2020 Mar 20:- epub ahead of print. [doi:10.1111/papr.12885] [Medline: 32196892]

https://formative.jmir.org/2020/7/e17293

XSL• FO
RenderX

Darnall et al

JMIR Form Res 2020 | vol. 4 | iss. 7 | e17293 | p. 16(page number not for citation purposes)

JMIR FORMATIVE RESEARCH
25.
26.
27.

28.

29.
30.

31.

32.

33.
34.

35.

36.

37.

38.

39.
40.
41.

42.

43.

44.

45.
46.

Gold JI, Kim SH, Kant AJ, Joseph MH, Rizzo AS. Effectiveness of virtual reality for pediatric pain distraction during iv
placement. Cyberpsychol Behav 2006 Apr;9(2):207-212. [doi: 10.1089/cpb.2006.9.207] [Medline: 16640481]
Atzori B, Grotto RL, Giugni A, Calabrò M, Alhalabi W, Hoffman HG. Virtual reality analgesia for pediatric dental patients.
Front Psychol 2018;9:2265 [FREE Full text] [doi: 10.3389/fpsyg.2018.02265] [Medline: 30532720]
Gold JI, Mahrer NE. Is virtual reality ready for prime time in the medical space? A randomized control trial of pediatricvirtual reality for acute procedural pain management. J Pediatr Psychol 2018 Apr 1;43(3):266-275. [doi:10.1093/jpepsy/jsx129] [Medline: 29053848]
Haisley KR, Straw OJ, Müller DT, Antiporda MA, Zihni AM, Reavis KM, et al. Feasibility of implementing a virtual reality
program as an adjuvant tool for peri-operative pain control; results of a randomized controlled trial in minimally invasive
foregut surgery. Complement Ther Med 2020 Mar;49:102356. [doi: 10.1016/j.ctim.2020.102356] [Medline: 32147069]
Özkan TK, Polat F. The effect of virtual reality and kaleidoscope on pain and anxiety levels during venipuncture in children.
J Perianesth Nurs 2020 Apr;35(2):206-211. [doi: 10.1016/j.jopan.2019.08.010] [Medline: 31759833]
Hoffman HG, Chambers GT, Meyer WJ, Arceneaux LL, Russell WJ, Seibel EJ, et al. Virtual reality as an adjunctive
non-pharmacologic analgesic for acute burn pain during medical procedures. Ann Behav Med 2011 Apr;41(2):183-191[FREE Full text] [doi: 10.1007/s12160-010-9248-7] [Medline: 21264690]
Khadra C, Ballard A, Déry J, Paquin D, Fortin J, Perreault I, et al. Projector-based virtual reality dome environment forprocedural pain and anxiety in young children with burn injuries: a pilot study. J Pain Res 2018;11:343-353 [FREE Fulltext] [doi: 10.2147/JPR.S151084] [Medline: 29491717]
Birckhead B, Khalil C, Liu X, Conovitz S, Rizzo A, Danovitch I, et al. Recommendations for methodology of virtual reality
clinical trials in health care by an international working group: iterative study. JMIR Ment Health 2019 Jan 31;6(1):e11973[FREE Full text] [doi: 10.2196/11973] [Medline: 30702436]
Dascal J, Reid M, IsHak WW, Spiegel B, Recacho J, Rosen B, et al. Virtual reality and medical inpatients: a systematic
review of randomized, controlled trials. Innov Clin Neurosci 2017;14(1-2):14-21 [FREE Full text] [Medline: 28386517]
Sato K, Fukumori S, Matsusaki T, Maruo T, Ishikawa S, Nishie H, et al. Nonimmersive virtual reality mirror visual feedback
therapy and its application for the treatment of complex regional pain syndrome: an open-label pilot study. Pain Med 2010
Apr;11(4):622-629. [doi: 10.1111/j.1526-4637.2010.00819.x] [Medline: 20202141]
Shiri S, Feintuch U, Weiss N, Pustilnik A, Geffen T, Kay B, et al. A virtual reality system combined with biofeedback fortreating pediatric chronic headache--a pilot study. Pain Med 2013 May;14(5):621-627. [doi: 10.1111/pme.12083] [Medline:
23659372]
Garcia-Palacios S, Herrero R, Vizcaíno Y, Belmonte MA, Castilla D, Molinari G, et al. Integrating virtual reality withactivity management for the treatment of fibromyalgia: acceptability and preliminary efficacy. Clin J Pain 2015
Jun;31(6):564-572. [doi: 10.1097/AJP.0000000000000196] [Medline: 25551475]
Botella C, Garcia-Palacios A, Vizcaíno Y, Herrero R, Baños RM, Belmonte MA. Virtual reality in the treatment offibromyalgia: a pilot study. Cyberpsychol Behav Soc Netw 2013 Mar;16(3):215-223. [doi: 10.1089/cyber.2012.1572][Medline: 23496678]
Wiederhold BK, Gao K, Sulea C, Wiederhold MD. Virtual reality as a distraction technique in chronic pain patients.
Cyberpsychol Behav Soc Netw 2014 Jun;17(6):346-352 [FREE Full text] [doi: 10.1089/cyber.2014.0207] [Medline:
24892196]
Sulea C, Soomro A, Wiederhold BK, Wiederhold MD. Quantifying the effectiveness of virtual reality pain management:a pilot study. Stud Health Technol Inform 2014;199:94-97. [Medline: 24875698]
Gumaa M, Youssef AR. Is virtual reality effective in orthopedic rehabilitation? A systematic review and meta-analysis.
Phys Ther 2019 Oct 28;99(10):1304-1325. [doi: 10.1093/ptj/pzz093] [Medline: 31343702]
Deyo RA, Dworkin SF, Amtmann D, Andersson G, Borenstein D, Carragee E, et al. Report of the NIH task force on researchstandards for chronic low back pain. Phys Ther 2015 Feb;95(2):e1-18 [FREE Full text] [doi: 10.2522/ptj.2015.95.2.e1][Medline: 25639530]
Dworkin RH, Turk DC, Farrar JT, Haythornthwaite JA, Jensen MP, Katz NP, IMMPACT. Core outcome measures forchronic pain clinical trials: IMMPACT recommendations. Pain 2005 Jan;113(1-2):9-19. [doi: 10.1016/j.pain.2004.09.012][Medline: 15621359]
Turk DC, Dworkin RH, Burke LB, Gershon R, Rothman M, Scott J, Initiative on Methods‚ Measurement and Pain Assessment
in Clinical Trials. Developing patient-reported outcome measures for pain clinical trials: IMMPACT recommendations.
Pain 2006 Dec 5;125(3):208-215. [doi: 10.1016/j.pain.2006.09.028] [Medline: 17069973]
Buckenmaier CC, Galloway KT, Polomano RC, McDuffie M, Kwon N, Gallagher RM. Preliminary validation of the defense
and veterans pain rating scale (DVPRS) in a military population. Pain Med 2013 Jan;14(1):110-123. [doi:10.1111/j.1526-4637.2012.01516.x] [Medline: 23137169]
Nassif TH, Hull A, Holliday SB, Sullivan P, Sandbrink F. Concurrent validity of the defense and veterans pain rating scale
in VA outpatients. Pain Med 2015 Nov 1;16(11):2152-2161. [doi: 10.1111/pme.12866] [Medline: 26257151]
Sullivan MJ, Bishop SR, Pivik J. The pain catastrophizing scale: development and validation. Psychol Assess
1995;7(4):524-532 [FREE Full text] [doi: 10.1037/1040-3590.7.4.524]

https://formative.jmir.org/2020/7/e17293

XSL• FO
RenderX

Darnall et al

JMIR Form Res 2020 | vol. 4 | iss. 7 | e17293 | p. 17(page number not for citation purposes)

JMIR FORMATIVE RESEARCH
47.

48.
49.

50.
51.

52.

53.

54.

55.

56.
57.

Darnall et al

Sun EC, Dixit A, Humphreys K, Darnall BD, Baker LC, Mackey S. Association between concurrent use of prescription
opioids and benzodiazepines and overdose: retrospective analysis. Br Med J 2017 Mar 14;356:j760 [FREE Full text] [doi:10.1136/bmj.j760] [Medline: 28292769]
Nicholas MK, McGuire BE, Asghari A. A 2-item short form of the pain self-efficacy questionnaire: development andpsychometric evaluation of PSEQ-2. J Pain 2015 Feb;16(2):153-163. [doi: 10.1016/j.jpain.2014.11.002] [Medline: 25463701]
Dworkin RH, Turk DC, McDermott MP, Peirce-Sandner S, Burke LB, Cowan P, et al. Interpreting the clinical importanceof group differences in chronic pain clinical trials: IMMPACT recommendations. Pain 2009 Dec;146(3):238-244. [doi:10.1016/j.pain.2009.08.019] [Medline: 19836888]
Lakens D. Calculating and reporting effect sizes to facilitate cumulative science: a practical primer for t-tests and ANOVAs.
Front Psychol 2013 Nov 26;4:863 [FREE Full text] [doi: 10.3389/fpsyg.2013.00863] [Medline: 24324449]
Gu H, Li D, Liu C, Rao Z. %ggBaseline: a SAS macro for analyzing and reporting baseline characteristics automaticallyin medical research. Ann Transl Med 2018 Aug;6(16):326 [FREE Full text] [doi: 10.21037/atm.2018.08.13] [Medline:
30364007]
Farrar JT, Young JP, LaMoreaux L, Werth JL, Poole MR. Clinical importance of changes in chronic pain intensity measured
on an 11-point numerical pain rating scale. Pain 2001 Nov;94(2):149-158. [doi: 10.1016/s0304-3959(01)00349-9] [Medline:
11690728]
Spiegel B, Fuller G, Lopez M, Dupuy T, Noah B, Howard A, et al. Virtual reality for management of pain in hospitalized
patients: a randomized comparative effectiveness trial. PLoS One 2019;14(8):e0219115 [FREE Full text] [doi:10.1371/journal.pone.0219115] [Medline: 31412029]
Hoffman HG, Rodriguez RA, Gonzalez M, Bernardy M, Peña R, Beck W, et al. Immersive virtual reality as an adjunctive
non-opioid analgesic for pre-dominantly Latin American children with large severe burn wounds during burn woundcleaning in the intensive care unit: a pilot study. Front Hum Neurosci 2019;13:262 [FREE Full text] [doi:10.3389/fnhum.2019.00262] [Medline: 31440148]
Tashjian VC, Mosadeghi S, Howard AR, Lopez M, Dupuy T, Reid M, et al. Virtual reality for management of pain in
hospitalized patients: results of a controlled trial. JMIR Ment Health 2017 Mar 29;4(1):e9 [FREE Full text] [doi:10.2196/mental.7387] [Medline: 28356241]
Spiegel BM. Virtual medicine: how virtual reality is easing pain, calming nerves and improving health. Med J Aust 2018
Sep 17;209(6):245-247. [Medline: 29764343]
Winger JG, Nunez C, Kelleher SA, Ingle KK, Gandhi V, Keefe FJ, et al. Predictors of intervention session completion ina randomized clinical trial of a behavioral cancer pain intervention. J Pain Symptom Manage 2020 Jun;59(6):1268-1277.
[doi: 10.1016/j.jpainsymman.2020.01.020] [Medline: 32045676]

Abbreviations
CBT: cognitive behavioral therapy
DVPRS: Defense and Veterans Pain Rating Scale
IMMPACT: Initiative on Methods, Measurement, and Pain Assessment in Clinical Trials
PCS: Pain Catastrophizing Scale
PSEQ-2: two-item Pain Self-Efficacy Questionnaire
RCT: randomized controlled trial
VR: virtual reality

Edited by P Santana-Mancilla; submitted 03.12.19; peer-reviewed by M Linnett, A Parks, D Ahern PhD; comments to author 15.01.20;
revised version received 12.04.20; accepted 05.05.20; published 07.07.20
Please cite as:
Darnall BD, Krishnamurthy P, Tsuei J, Minor JD
Self-Administered Skills-Based Virtual Reality Intervention for Chronic Pain: Randomized Controlled Pilot StudyJMIR Form Res 2020;4(7):e17293
URL: https://formative.jmir.org/2020/7/e17293
doi: 10.2196/17293
PMID: 32374272©Beth D Darnall, Parthasarathy Krishnamurthy, Jeannette Tsuei, Jorge D Minor. Originally published in JMIR Formative Research(http://formative.jmir.org), 07.07.2020. This is an open-access article distributed under the terms of the Creative Commons
Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction
in any medium, provided the original work, first published in JMIR Formative Research, is properly cited. The complete
https://formative.jmir.org/2020/7/e17293

XSL• FO
RenderX

JMIR Form Res 2020 | vol. 4 | iss. 7 | e17293 | p. 18(page number not for citation purposes)

JMIR FORMATIVE RESEARCH

Darnall et albibliographic information, a link to the original publication on http://formative.jmir.org, as well as this copyright and license
information must be included.

https://formative.jmir.org/2020/7/e17293

XSL• FO
RenderX

JMIR Form Res 2020 | vol. 4 | iss. 7 | e17293 | p. 19(page number not for citation purposes)