Abstract
Background
Virtual reality (VR) could possibly alleviate complaints related to chronic musculoskeletal pain (CMP); however, little is known about how it affects pain-related variables on an individual level and how patients experience this intervention.
Objective
This study aimed to gain detailed insight into the influence of an at-home VR intervention for pain education and management on pain-related variables, and to explore its feasibility and general experience.
Methods
The study applied a single-case experimental design in which an at-home VR intervention was used for 4 weeks by patients with CMP who were on a waiting list for regular pain treatment. Outcome measures included pain-related variables, functioning, and objectively measured outcomes (ie, stress, sleep, and steps). Outcomes were analyzed using data visualization (based on line plots) and statistical methods (ie, Tau-U and reliable change index) on an individual and group level. In addition, a focus group was conducted to assess feasibility and general experience to substantiate findings from the single-case experimental design study. This focus group was analyzed using inductive thematic analysis.
Results
A total of 7 participants (female: n=6, 86%) with a median age of 45 (range 31‐61) years participated in this study. A dataset with 42 measurement moments was collected with a median of 280 (range 241‐315) data points per participant. No statistically significant or clinically relevant differences between the intervention and no-intervention phases were found. Results of the visual analysis of the diary data showed that patients responded differently to the intervention. Results of the focus group with 3 participants showed that the VR intervention was perceived as a feasible and valued additional intervention.
Conclusions
Although patients expressed a positive perspective on this VR intervention, it did not seem to influence pain-related outcomes. Individual patients responded differently to the intervention, which implies that this intervention might not be suitable for all patients. Future studies should examine which CMP patients VR is effective for and explore its working mechanisms. In addition, future larger trials should be conducted to complement this study’s findings on the effectiveness of this intervention for patients with CMP and whether VR prevents deterioration on the waiting list compared with a control group.
Introduction
Chronic musculoskeletal pain (CMP), defined as pain lasting longer than 3 months, is a major problem and prevalent in approximately 20% of adults [1,2]. CMP is associated with a decrease in quality of life and mental health problems [3,4], next to the significant financial and societal burden [1]. Unfortunately, the effectiveness of biomedical treatment options for CMP does not seem to be very promising [5], since CMP usually is a complex problem with an interplay of biological, psychological, and social factors [6].
Given the complexity of CMP, treatment should use a holistic approach in accordance with the biopsychosocial model [5] and neuromatrix theory [7]. Unfortunately, most more complex, holistic interventions for CMP have a waiting list period, which could have a deteriorating effect on patients with CMP [8]. Therefore, it might be sensible to already start treatment during this waiting list period. Virtual reality (VR) is a novel, therapeutic technology that is suitable for stand-alone, at-home treatment [9]. VR is defined as “a collection of technologies that allow people to interact efficiently with 3D computerized databases in real time using their natural senses and skills” [10].
Even though VR for CMP seems promising, much is still unknown about its underlying mechanisms (eg, distraction or skills-building) [11] and influences on an individual level, as previous studies applied a nomothetic approach [9]. Since the principles underlying VR for CMP remain a black box [12], an idiographic approach is warranted for a complex condition like CMP to gain insight into the influence of VR on individual outcomes [13]. A single-case experimental design (SCED) study could increase understanding of the individual experience [14]. SCED studies apply detailed assessment at numerous timepoints [15] and have benefits over other designs, including patients serving as their own control and being especially suitable for heterogeneous samples, like CMP patients with a variety of conditions [16]. A recent SCED study on VR for chronic low back pain (CLBP) found that VR has the potential to reduce CMP-related complaints, possibly through a combination of distraction and modification of attitudes and beliefs [17]. We expect that this VR intervention is suitable not only for patients with CLBP but also for patients with other CMP conditions. In addition, we hypothesize that VR might influence other outcome measures like pain acceptance and interference, functioning, and objectively measured outcomes.
Therefore, the aim of our study was to (1) explore whether and how a VR intervention has an influence on pain-related variables on an individual level and (2) explore the feasibility and general experience of the VR intervention. To do so, patients with CMP received a pain education and management VR intervention at home while they were on a waiting list to receive pain treatment.
Methods
Design
This mixed methods study consisted of 2 parts. The first part of the study applied a nonconcurrent single-case experimental ABA-design on at-home, VR intervention for patients with primary or secondary CMP who were on a waiting list to receive regular pain treatment. Phases A1 and A2 (no intervention) were 1 week before and 1 week after the VR intervention, fulfilling the criterion for a sufficient baseline in single-case designs [18]. Phase B (VR intervention) lasted a total of 4 weeks. To report and conduct the study, the Single-Case Reporting Guideline in Behavioural Interventions (SCRIBE) was used [19], more details in Multimedia Appendix 1. The second part of this study consisted of 1 focus group with patients with CMP who received the intervention. The aim of this focus group was to gain more insight into the general experience and feasibility (including acceptability and practicality, which includes participants’ satisfaction and ability to use a new intervention [20]) of the VR intervention and substantiate findings from the SCED study. This part of the study was reported and conducted according to the Consolidated Criteria for Reporting Qualitative Research (COREQ) reporting guidelines [21], more details in Multimedia Appendix 2. Recruitment and completion of the study procedures was from February 2023 to April 2023.
Ethical Considerations
The medical ethics committee of Radboudumc provided a non-WMO (medical research involving human subjects act) waiver (2022‐15829) to conduct this study. The ethics committee of the University of Twente approved this study (RP 2022‐174), as well as local ethics committees of the participating health care organizations. Participants gave written informed consent before any study procedures and received €50 (US $52) for participation in this study after finishing all procedures. All participant data was pseudonymized.
Participants
Participants were recruited from 4 secondary care organizations in the Netherlands (ie, Roessingh Centrum voor Revalidatie, Roessingh Pijnrevalidatie, ZGT Nocepta, and Deventer hospital). Patients were deemed eligible for participation if they (1) were aged 18 years or older, (2) had primary or secondary CMP, (3) finished first-line treatment, (4) were open to treatment with biopsychosocial elements, and (5) were willing and able to comply with the study protocol. Patients were excluded if they (1) were not capable of finishing the intervention due to physical (eg, face wounds, severe visual impairment), mental (eg, severe sensitivity to stimuli), or practical problems (eg, insufficient tech literacy); and (2) had no comprehension of the Dutch language.
Intervention
In this study, the Conformité Européenne (CE)–certified VR intervention Reducept was used as a daily at-home intervention for 10 to 30 minutes per day for 4 weeks, thereby following the intervention protocol dosage from the intervention provider. Besides pain neuroscience education (PNE), the VR intervention incorporates elements of several psychological therapies into 1 application: hypnotherapy, mindfulness, acceptance and commitment therapy (ACT), and cognitive behavioral therapy (CBT). The intervention was described in more detail in previous studies [9,22,23]. The Pico G2 4K (Bytedance) head-mounted display (HMD) was used in this study to provide the immersive VR intervention.
Procedure
Patients visited one of the participating centers of this study for their pain treatment. After their intake, but before starting their secondary care treatment (either [non]invasive pain treatment or interdisciplinary pain rehabilitation), patients were screened by their health care professional for possible participation in the study. Patients were given the opportunity to participate in our study or wait for their treatment on the waiting list without receiving any other treatment. In addition, participants were made clear that participating in this study would not have any influence on the pain treatment they were on a waiting list for. If a patient was deemed eligible, he or she was contacted by their health care professional, who gave a brief explanation about the study and asked for permission to forward the patient’s contact details to the researcher (through a fully secured app: Siilo). Next, the researcher contacted the patient by phone and gave more detailed information about the study and asked the patient to contemplate participating in the study. The patient enrolled in the study by signing the informed consent and received the first questionnaires (T0), the Garmin Forerunner 255 wearable, and the VR headset. The wearable and VR headset were provided by the researcher and used by participants for the duration of the study procedures. In the first week, a detailed baseline was obtained by asking patients to use the wearable and fill in the diary and weekly questionnaires, without receiving the intervention (phase A1). After this phase, participants carried out the intervention at home for four weeks (phase B). Next, patients waited a week (phase A2) before receiving the pain treatment he or she was on the waiting list for. After phase A2 and during the period patients received the pain treatment they were on a waiting list for, patients returned the used equipment (ie, VR headset and wearable) and were invited to the online focus group, using Microsoft Teams, about the feasibility and general experience of the intervention. The focus group was conducted by 2 researchers (SS and LH), assisted by a research student assistant. Both SS and LH attended various courses on and have previous experience with qualitative research. Given this experience, there may have been preconceived notions regarding VR for CMP. We aimed to reduce potential biases by fostering open discussions and critical reflections throughout data collection and analysis. None of the participants had previous relationships with any of the researchers conducting and analyzing the focus group. The topic list used for this focus group is added in Multimedia Appendix 3.
Outcomes
The outcome measures are shown in Table 1. The TIIM app (University of Twente, Enschede, the Netherlands) was used to collect demographic information, diary measures, and weekly questionnaires.
Table 1. Overview of outcome measurements.
| Pre | Week 1 | Week 2 | Week 3 | Week 4 | Week 5 | Week 6 | Post | |
|---|---|---|---|---|---|---|---|---|
| Patient characteristics | ✓ | |||||||
| Diary measures | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ||
| Weekly questionnaires | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ||
| Wearable data | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ||
| VRa parameters | ✓ | ✓ | ✓ | ✓ | ||||
| Feasibility | ✓ |
VR: virtual reality.
Diary Measures
The daily diary questions consisted of 4 questions, based on the IMMPACT (Initiative on Methods, Measurement, and Pain Assessment in Clinical Trials) recommendations for chronic pain clinical trials [24]: pain intensity (ie, what score would you give your pain today?), pain interference (ie, how burdensome was your pain today?), physical functioning (ie, to what extent did your pain restrict you in doing daily activities today?), and emotional functioning (ie, how was your mood today?). All questions were scored on a 0 (lowest) to 10 (highest) scale. A recent study showed that daily measures of pain and pain-related variables are both valid and reliable [25].
Weekly Questionnaires
Every week, participants were asked to answer 3 questionnaires to measure pain self-efficacy (Pain Self-Efficacy Questionnaire [PSEQ]) [26], pain acceptance (Chronic Pain Acceptance Questionnaire [CPAQ]) [27], and pain coping (Pain Coping Inventory [PCI]) [28]. These questionnaires were the Dutch translation of the original questionnaires, and all were shown to have adequate reliability and validity [29-31].
Wearable Outcomes
The following outcomes were measured using the wearable: physical activity (ie, daily steps), sleep quality, and stress. Daily sleep quality was scored from 0 (worst sleep quality) to 100 (best sleep quality) based on multiple factors, including sleep duration, stress score during sleep, and restlessness. Daily stress was measured using Garmin’s stress level from 0 (lowest stress level) to 100 (highest stress level), which is based on the participant’s heart rate variability (HRV). More information about the construction of sleep quality and stress as outcome measures in this study can be found in the Garmin manual [32].
Other Outcomes
The following patient characteristics were asked at baseline: age, gender, duration of CMP, comorbidities, pain location, pain medication use, expectation of intervention, occupational situation, education level (based on [33]), and experience with VR for treatment and entertainment.
VR-related parameters that were monitored included usage and module of the VR intervention.
The feasibility of the intervention was explored using usability data (ie, number of minutes used per day) and a semistructured postintervention focus group with patients who received the intervention.
Statistical Analysis
The results of the SCED study were examined using a combination of statistical and visual analyses [34,35]. Phase A1 of each individual participant was observed to determine a stable personal control to note any revealing alterations for the outcome variables measured in phase B. Both within-phase and between-phase analyses were performed and checked for patterns within participants. To determine changes in outcome variables in SCED studies, it is recommended to use the following factors to interpret the data: (1) raw data, (2) central tendency, (3) trend, (4) variability, (5) point of change, and (6) overlap region [15]. All visual plots were constructed using the Shiny SCDA web application [36,37]. Besides this visual analysis, outcomes of the diary questions and wearable data were statistically analyzed using the Tau-U nonoverlap method [38], using a web-based calculator [39]. Effect sizes for Tau-U were interpreted as small (0-.65), medium (.66-.92), or large (>.92) [38]. To gain insight into the relationship between pain-related variables during the intervention, outcomes of the weekly questionnaires were compared on an individual level using the Reliable Change Index (RCI). The RCI was calculated using the pretreatment and posttreatment scores and was considered reliable at 1.96 or more [40]. Clinically important differences in pain intensity were examined between pre- and postintervention, in which a reduction of ≥30% or 2 points was considered clinically important [41]. The recording of the focus group, which had a duration of 50 minutes, was transcribed using Amberscript. This transcript was analyzed using inductive thematic analysis with Atlas.ti (version 24), based on the 6 steps proposed by Braun and Clarke [42]: (1) (re-)read transcript to familiarize with the data, (2) generate initial codes, (3) combine codes into themes, (4) review themes, (5) define themes, and (6) report findings. These steps were completed by 2 researchers (SS and LH) and discussed until consensus was reached. Finally, all authors agreed on the final themes and results identified during this process.
Results
Patient Characteristics
A total of 9 participants enrolled in this study, of which 7 completed the study (Table 2). In addition, 1 participant stopped due to being too busy and 1 participant completed <50% of the questionnaires and was therefore excluded from the analysis. The 7 participants who were included in the analysis provided a median of 280 (range 241‐315) data points per participant. None of the participants had previous experience with VR. No adverse events were reported by any of the participants from using the VR intervention.
Table 2. Demographics of participants (n=7).
| Participant | Age (years) | Gender | Highest level of education | Occupational situation | Pain duration (years) | Pain location | Medication use | Expectancya |
|---|---|---|---|---|---|---|---|---|
| 1 | 31 | Woman | Higher | Part-time | 1 | Foot, ankle | Yes | 6 |
| 2 | 55 | Man | Lower | Full-time | 17 | Legs, hands | Yes | 5 |
| 3 | 45 | Woman | Middle | Part-time | 5 | Wrist, shoulder, back | Yes | 4 |
| 4 | 31 | Woman | Middle | Unemployed | 7 | Generalized | No | 6 |
| 5 | 61 | Woman | Lower | Part-time | 30 | Back, hip | Yes | 6 |
| 6 | 52 | Woman | Higher | Full-time | 3 | Back, shoulders, neck | Yes | 5 |
| 7 | 37 | Woman | Higher | Part-time | 4.5 | Back, pelvic | Yes | 6 |
Scored from 0 (lowest expectancy) to 10 (highest expectancy).
Visual Analysis
Results of the visual analysis of the diary data showed that patients responded differently to the intervention, as discussed below per outcome variable. The results of the 4 diary outcome measures are presented in Figures1 2 and Multimedia Appendix 4, in which the phases A1 (day 1‐7, no intervention), B (day 8‐35, intervention), and A2 (day 36‐42, no intervention) are presented on the x-axis and scores from 0 (lowest) to 10 (highest) are presented on the y-axis.
Figure 1. Visual analysis of diary data on pain intensity (see clearer version in Multimedia Appendix 5).

Figure 2. Visual analysis of diary data on pain interference (see clearer version in Multimedia Appendix 6).

Pain intensity scores (Figure 1) remained relatively consistent through phase A1, B, and A2. However, some participants seem to report somewhat lower scores during phase B compared with phase A1 (eg, participant 6 from mean phase A1 6.4, SD 0.8, to mean phase B 5.1, SD 1.7), while others report higher scores (eg, participant 3 from mean phase A1 1.9, SD 0.9 to mean phase B 3.3, SD 1.4). Furthermore, it is notable that most participants reported substantial variability within proximate measurement moments.
Analysis of the pain interference outcome (Figure 2) showed that patients reported fairly stable scores on central tendency. Some participants showed minor improvement between phases (eg, participant 2 from mean phase A1 6.7, SD 0.8, to mean phase B 7.5, SD 0.7), while others showed some deterioration (eg, participant 5 from mean phase B 6.4, SD 0.9, to mean phase A2 5.7, SD 0.8). In addition, it should be noted that pain interference scores show much likeness to pain intensity scores.
Results on physical functioning (Multimedia Appendix 4) showed that central tendency does not seem to alter too much between phases, similar to the results on pain intensity and pain interference scores. Variability within patients seems to be similar to previously reported outcome measures as well, except for participant 3 who shows large variability within proximate measurement times (eg, day 23: 2; day 24: 10; day 25: 2).
Finally, emotional functioning scores (Multimedia Appendix 4) were relatively high in most participants (mean 7.1, SD 1.5, compared with mean pain intensity 5.9, SD 1.8, pain interference 5.9, SD 1.8, and physical functioning 5.4, SD 1.7). Trend between phases seemed to be improving for some participants (eg, phase A1 of participant 7), while the opposite occurred in other participants (eg, phase A2 of participant 4). Variability seemed to be lower compared with previously discussed outcome measures in most participants.
Statistical Analysis
Analysis of the daily diary and wearable data using Tau-U, as shown in Table 3, showed no statistically significant difference in any of the outcome measures. In addition, no clinically important reductions in pain intensity (ie, reduction of pain intensity score of ≥30% or ≥2 points) were found. Results of the statistical analysis of the weekly questionnaires using the RCI (Table 4) showed no reliable change on any of the questionnaires for any of the participants. More detailed information about the results of the wearable data and weekly questionnaires can be found in respectively Multimedia Appendix 7 (individual scores on steps, stress, and sleep) and Multimedia Appendix 8 (Group scores on weekly questionnaires). Median VR use was 37.5 minutes per week (range 7.8‐78.4).
Table 3. Statistical analysis of diary and wearable data.
| Tau-U | 95% CI | P value | |
|---|---|---|---|
| Pain intensity | −0.011 | −0.16 to 0.14 | .88 |
| Pain interference | −0.013 | −0.16 to 0.13 | .87 |
| Physical functioning | −0.091 | −0.24 to 0.06 | .23 |
| Emotional functioning | −0.021 | −0.17 to 0.13 | .78 |
| Steps | 0.013 | −0.14 to 0.17 | .87 |
| Stress | −0.075 | −0.23 to 0.09 | .36 |
| Sleep | 0.082 | −0.08 to 0.24 | .32 |
Table 4. Statistical analysis of weekly questionnaires.
| Participant | |||||||
|---|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | |
| PSEQa | |||||||
| Pretreatment, mean (SD) | 43 (0.7) | 31 (3.5) | 42 (4.2) | 21 (8.5) | 37 (4.9) | 23 (2.8) | 27 (0) |
| Posttreatment, mean (SD) | 38 (2.8) | 36 (0) | 47 (2.1) | 23 (2.1) | 45 (1.4) | 18 (2.1) | 29 (3.5) |
| RCIb | −1.05 | 1.05 | 1.05 | 0.42 | 1.68 | −1.05 | 0.42 |
| CPAQc | |||||||
| Pretreatment, mean (SD) | 23 (0) | 32 (0.7) | 31 (0.7) | 20 (0.7) | 29 (1.4) | 15 (1.4) | 18 (5.7) |
| Posttreatment, mean (SD) | 28 (1.4) | 31 (3.5) | 31 (2.8) | 23 (0) | 29 (1.4) | 15 (2.1) | 20 (2.1) |
| RCI | 0.74 | −0.15 | 0 | 0.45 | 0 | 0 | 0.30 |
| PCId active | |||||||
| Pretreatment, mean (SD) | 31 (0.7) | 31 (1.4) | 31 (1.4) | 29 (0.7) | 26 (0.7) | 28 (0.7) | 30 (1.4) |
| Posttreatment, mean (SD) | 28 (1.4) | 28 (0) | 34 (0) | 26 (0) | 27 (2.8) | 23 (1.4) | 30 (0.7) |
| RCI | −0.84 | −0.84 | 0.84 | −0.84 | 0.28 | −1.40 | 0 |
| PCI passive | |||||||
| Pretreatment, mean (SD) | 40 (1.4) | 44 (5.7) | 42 (0) | 64 (2.8) | 46 (3.5) | 49 (0.7) | 51 (4.2) |
| Posttreatment, mean (SD) | 43 (4.2) | 44 (0.7) | 36 (.7) | 59 (1.4) | 44 (0.7) | 45 (0) | 55 (1.4) |
| RCI | −0.38 | 0 | 0.77 | 0.64 | 0.26 | 0.51 | −0.51 |
PSEQ: Pain Self-Efficacy Questionnaire.
RCI: Reliable Change Index.
CPAQ: Chronic Pain Acceptance Questionnaire.
PCI: Pain Coping Inventory.
Focus Group Analysis
Participants 4, 6, and 7, as described in Table 2, participated in the postintervention focus group. The other participants were not able to participate because they were too busy (with their pain rehabilitation program) (n=3), and did not feel well on the day of the focus group (n=1). Based on the analysis of the focus group, the following three themes were identified: (1) experiences of CMP patients with VR, (2) feasibility of VR, and (3) VR in CMP rehabilitation.
Theme 1: Experiences of CMP Patients With VR
Participants found the VR program attractive to use and valued the intuitive nature of the intervention. Furthermore, they reported several positive effects of the VR intervention, including feelings of self-efficacy, more knowledge about (chronic) pain and focus shifting. Although, these effects were not substantial and patients had to get used to using VR, as it demanded both their time and effort.
And it provided me with insights about how chronic pain works.
[Participant 7]
My focus shifted away from the pain and went more towards the game or killing those monsters, which was a lot of fun. And then you notice that it does something with the pain.
[Participant 6]
And then you still [use VR] while you are actually already tired and in need of a bit of a rest.
[Participant 4]
Theme 2: Feasibility of VR
Participants perceived the VR intervention as feasible. They found it easy and comfortable to use at home, the instructions were clear, and it was attainable to use daily.
And we received clear instructions beforehand, so then it’s just plug and play, you know.
[Participant 4]
Yes, I think I actually liked using it at home first, instead of somewhere else.
[Participant 6]
Theme 3: VR in CMP Rehabilitation
VR helped participants bridge the waiting time, but participants valued it more as an addition to their treatment rather than a substitution.
It’s more of an addition, a good addition, a meaningful addition.
[Participant 6]
Some participants mentioned it might be valuable to provide the VR intervention not only during the waiting list period but also during the pain treatment they were on the waiting list for. Furthermore, it is important to consider the individual process and whether a patient is open to working on the topics addressed in the VR intervention.
…that it would be even more effective during pain treatment, it would be even stronger, because you are already more involved in it and you can also ask for feedback immediately, for example from one of your therapists, if you have any questions.
[Participant 7]
It [the VR intervention] raised some internal conflict, but I can really understand that it could be very helpful for patients who are further in their process.
[Participant 4]
In the future, patients would recommend to receive VR not on a daily basis, but maybe 2 or 3 times a week, in between the days of the pain rehabilitation program.
Discussion
Principal Findings
The aim of this study was to gain insight into the influence of VR on pain-related variables and evaluate the feasibility and general experience of this intervention. Analyses of the reported measures showed no clinical and statistically significant differences. Our results imply that the provided intervention did not influence the outcome measures used in this study. This was supported by the visual analyses, which showed that some participants somewhat improved after the intervention on several outcome measures, but worsened on different outcome measures. However, results of the focus group showed that patients qualitatively reported a positive perspective and experienced the intervention as feasible.
Comparison to Previous Work
The results of this study are comparable to other studies that provided the VR intervention, Reducept. A previous study that examined the effect of Reducept for patients with CLBP who were on a waiting list to receive pain treatment [9], showed no significant between-group results on the primary and most other outcome measures, except for opioid use, daily worst, and least experienced pain intensity. It should be noted that the patient sample in both their and our study were patients with severe and complex symptoms. They were referred to secondary pain care, with for example a median pain duration of 5 years in our sample. Previous studies showed that a longer duration of pain complaints was associated with a worse prognosis [43,44] and diminished responsivity to treatment [45]. As suggested before, this specific stand-alone VR intervention might therefore be more suitable for CMP patients with less complex complaints [17].
This study by de Vries et al [17] found somewhat more promising results when they conducted a SCED study among patients with CLBP where they received 9 to 12 45-minute sessions of the VR intervention [17]. Results of their study showed that Reducept might be able to induce clinically relevant reductions in pain intensity and other pain-related outcomes in some patients [17]. These patients were not on a waiting list to receive other pain treatment and received the intervention supervised in the hospital, which might have increased effectiveness [46]. Other interventions that used a stand-alone at-home VR intervention reported clinically meaningful results [47-49], but patients were (1) not on a waiting list to receive other pain treatment and (2) received a more extensive intervention (both in duration and content). A waiting list period is known to possibly deteriorate pain complaints [8]. A meta-analysis among psychotherapies even showed that waiting lists might be regarded as a nocebo condition since patients might, for example, feel the need to remain their complaints to be able to start the pain treatment they are on the waiting list for [50]. In addition, it might be possible that the waiting list period is not the best time to provide VR. This was mentioned in our focus group, and previous research showed that it is also possible to extend secondary care for CMP patients with VR as an additional treatment option [51,52]. In regard to the content of the VR module, it might be possibile to supplement this with, for example, personalized exercise therapy as was done in previous VR interventions for CMP [51,53,54]. Finally, the dosage of the VR intervention might be a point of interest, as the study by de Vries et al [17] found different results from this study while using another dosage of the same intervention. The intervention duration in this trial was 4 weeks, while for behavioral CMP interventions, a duration of 6 to 10 weeks is advised [55], which implies that the intervention did not last long enough. Future studies on VR for CMP should, therefore, study the optimal timing, (personalized) content, and dosage of VR interventions for the most fitting patients.
Results of our study showed a discrepancy between the analyses of quantitative outcome measures and qualitative measures. This is congruent with the qualitative evaluation [22] of the trial that was discussed before [9]. They reported that the VR intervention positively affected how patients’ health was experienced, provided patients with more control over their pain, and helped patients accept and understand pain. This is supported by other studies in which patients did not report significant differences in, for example, quality of life or pain intensity measured using questionnaires but mentioned positive benefits during an oral evaluation after their VR intervention [17,56]. This discrepancy could partially be explained by social-desirability bias, as patients might want to portray a more positive impression of the intervention for the researcher who is interviewing them [57]. In addition, it might be possible that nonoptimal quantitative outcome measures were used for this VR intervention, and softer outcomes like values (eg, autonomy) or more proximate outcomes (eg, knowledge about CMP) should be examined as well, as was suggested previously [14].
Strengths and Limitations
One of the strengths of this study was the use of a heterogeneous sample of patients with ranging ages (31-61 years), pain duration (1-30 years), and type of pain complaints. In addition, a rich dataset with multiple subjective (ie, daily diary, validated questionnaires, and focus group) and objective (ie, wearable) outcome measures was used, which was analyzed both visually and statistically. In line with SCED study recommendations, at least 5 data points per phase were collected [58].
This study had several limitations. First, the nature of the study design is characterized by a smaller sample size, which came with risks of selection-bias of specific patients and hindered generalizability of study results. Second, treatment fidelity varied between participants, and not all participants used the VR intervention as much as prescribed, which could have diminished the intervention effect. This problem was mentioned in other VR interventions for CMP as well [48,53], while it is known that repetition is key in, for example, PNE [59]. However, it should be noted that treatment fidelity varies outside a study design, and therefore, this study reflects a real-world situation. Third, we conducted only 1 focus group with 3 participants who provided an insight into the intervention feasibility. Given the limited sample size, these results should be interpreted with caution. However, a more in-depth analysis of qualitative data, possibly with one-on-one interviews instead of focus groups, of participants’ experience with VR in a larger study sample would be interesting, to learn more about possible working mechanisms and administration best practices of VR for CMP, which could further improve this intervention.
Future Directions
The results of this study suggest implications for clinical and theoretical practice. It seems that this stand-alone VR intervention for patients with CMP on a waiting list for secondary care does not influence pain-related complaints. However, in the right dose, setting, and timing it might be more effective, as previous research, for example, suggested that VR interventions for CMP might be more effective for younger patients [60]. To further inform trial and intervention design, other relevant pain-related outcomes (eg, catastrophizing) and medication use could be investigated, as these were found relevant in previous VR for CMP studies [9]. In addition, future studies could explore prognostic patient characteristics to identify patients who would respond better or worse to therapeutic VR for CMP. To further study the effectiveness of the (improved) intervention and complement the findings of this study, a randomized controlled trial (RCT) is warranted, in which a control group that receives usual care should be included. This RCT should both focus on the short-term results and include an analysis of the complete pain treatment trajectory. Furthermore, subgroup analyses are needed to examine for which patients VR is effective.
The results of this study showed that this stand-alone immersive VR intervention for patients with CMP on a waiting list did not seem to alter pain-related outcomes. Patients reported good feasibility and general positive experience of the intervention and these outcomes can inform further intervention and trial design.
Supplementary material
Acknowledgments
The authors would like to thank all patients who participated in this study and Martijn Eenhoorn and Job Brinkman for their help in data collection. This study was funded by the 2021 Pioneers in Healthcare innovation fund. The funder had no role in the design, organization, and execution of the study.
Abbreviations
- ACT
acceptance and commitment therapy
- CBT
cognitive behavioral therapy
- CE
Conformité Européenne
- CLBP
chronic low back pain
- CMP
chronic musculoskeletal pain
- COREQ
Consolidated Criteria for Reporting Qualitative Research
- COREQ
Consolidated Criteria for Reporting Qualitative Research
- CPAQ
Chronic Pain Acceptance Questionnaire
- HMD
head-mounted display
- HRV
heart rate variability
- IMMPACT
Initiative on Methods, Measurement, and Pain Assessment in Clinical Trials
- PCI
Pain Coping Inventory
- PNE
pain neuroscience education
- PSEQ
Pain Self-Efficacy Questionnaire
- RCI
Reliable Change Index
- RCT
randomized controlled trial
- SCED
single-case experimental design
- SCRIBE
Single-Case Reporting Guideline in Behavioural Interventions
- VR
virtual reality
Footnotes
Data Availability: The datasets generated during this study will not be publicly available but will be available upon reasonable request to the corresponding author.
Authors’ Contributions: SS was the principal investigator of this study and drafted the first version of the manuscript. LH conceptualized and designed the study, reviewed and revised the manuscript, and performed supervision. SS, RA, JB, NMDO, RTR, and MS supported recruitment of patients and reviewed and revised the manuscript. MT conceptualized and designed the study, reviewed and revised the manuscript, and supervised SS. All authors contributed to the manuscript and approved the final manuscript.
Conflicts of Interest: None declared.
References
- 1.Bekkering GE, Bala MM, Reid K, et al. Epidemiology of chronic pain and its treatment in The Netherlands. Neth J Med. 2011 Mar;69(3):141–153. Medline. [PubMed] [Google Scholar]
- 2.Breivik H, Collett B, Ventafridda V, Cohen R, Gallacher D. Survey of chronic pain in Europe: prevalence, impact on daily life, and treatment. Eur J Pain. 2006 May;10(4):287–333. doi: 10.1016/j.ejpain.2005.06.009. doi. Medline. [DOI] [PubMed] [Google Scholar]
- 3.Hadi MA, McHugh GA, Closs SJ. Impact of chronic pain on patients’ quality of life: a comparative mixed-methods study. J Patient Exp. 2019 Jun;6(2):133–141. doi: 10.1177/2374373518786013. doi. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Hooten WM. Chronic pain and mental health disorders: shared neural mechanisms, epidemiology, and treatment. Mayo Clin Proc. 2016 Jul;91(7):955–970. doi: 10.1016/j.mayocp.2016.04.029. doi. Medline. [DOI] [PubMed] [Google Scholar]
- 5.Hylands-White N, Duarte RV, Raphael JH. An overview of treatment approaches for chronic pain management. Rheumatol Int. 2017 Jan;37(1):29–42. doi: 10.1007/s00296-016-3481-8. doi. Medline. [DOI] [PubMed] [Google Scholar]
- 6.Cohen SP, Vase L, Hooten WM. Chronic pain: an update on burden, best practices, and new advances. Lancet. 2021 May 29;397(10289):2082–2097. doi: 10.1016/S0140-6736(21)00393-7. doi. Medline. [DOI] [PubMed] [Google Scholar]
- 7.Melzack R. From the gate to the neuromatrix. PAIN. 1999 Aug;Suppl 6:S121–S126. doi: 10.1016/S0304-3959(99)00145-1. doi. Medline. [DOI] [PubMed] [Google Scholar]
- 8.Lynch ME, Campbell F, Clark AJ, et al. A systematic review of the effect of waiting for treatment for chronic pain. Pain. 2008 May;136(1-2):97–116. doi: 10.1016/j.pain.2007.06.018. doi. Medline. [DOI] [PubMed] [Google Scholar]
- 9.Groenveld TD, Smits MLM, Knoop J, et al. Effect of a behavioral therapy-based virtual reality application on quality of life in chronic low back pain. Clin J Pain. 2023 Jun 1;39(6):278–285. doi: 10.1097/AJP.0000000000001110. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.McCloy R, Stone R. Science, medicine, and the future. Virtual reality in surgery. BMJ. 2001 Oct 20;323(7318):912–915. doi: 10.1136/bmj.323.7318.912. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Trost Z, France C, Anam M, Shum C. Virtual reality approaches to pain: toward a state of the science. PAIN. 2021;162(2):325–331. doi: 10.1097/j.pain.0000000000002060. doi. [DOI] [PubMed] [Google Scholar]
- 12.Liu Z, Wangluo S, Dong H. In: Virtual Augment Mix. Lackey S, Shumaker R, editors. Springer International Publishing; 2016. Advances and tendencies: A review of recent studies on virtual reality for pain management; pp. 512–520. doi. [DOI] [Google Scholar]
- 13.Hamaker EL. The curious case of the cross-sectional correlation. Multivariate Behav Res. 2024;59(6):1111–1122. doi: 10.1080/00273171.2022.2155930. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Smits M, Ludden GDS, Verbeek PP, van Goor H. How digital therapeutics are urging the need for a paradigm shift: from evidence-based health care to evidence-based well-being. Interact J Med Res. 2022 Oct 20;11(2):e39323. doi: 10.2196/39323. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Morley S. Single Case Methods in Clinical Psychology: A Practical Guide. Routledge; 2017. ISBN.978-1-315-41292-4 [Google Scholar]
- 16.Smith JD. Single-case experimental designs: a systematic review of published research and current standards. Psychol Methods. 2012 Dec;17(4):510–550. doi: 10.1037/a0029312. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.de Vries FS, van Dongen RTM, Bertens D. Pain education and pain management skills in virtual reality in the treatment of chronic low back pain: A multiple baseline single-case experimental design. Behav Res Ther. 2023 Mar;162:104257. doi: 10.1016/j.brat.2023.104257. doi. Medline. [DOI] [PubMed] [Google Scholar]
- 18.Kratochwill TR, Hitchcock JH, Horner RH, et al. Single-case intervention research design standards. Remedial Spec Educ. 2013 Jan;34(1):26–38. doi: 10.1177/0741932512452794. doi. [DOI] [Google Scholar]
- 19.Tate RL, Perdices M, Rosenkoetter U, et al. The Single-Case Reporting Guideline In BEhavioural Interventions (SCRIBE) 2016 statement. Phys Ther. 2016 Jul;96(7):e1–e10. doi: 10.2522/ptj.2016.96.7.e1. doi. Medline. [DOI] [PubMed] [Google Scholar]
- 20.Bowen DJ, Kreuter M, Spring B, et al. How we design feasibility studies. Am J Prev Med. 2009 May;36(5):452–457. doi: 10.1016/j.amepre.2009.02.002. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Tong A, Sainsbury P, Craig J. Consolidated criteria for reporting qualitative research (COREQ): a 32-item checklist for interviews and focus groups. Int J Qual Health Care. 2007 Dec;19(6):349–357. doi: 10.1093/intqhc/mzm042. doi. [DOI] [PubMed] [Google Scholar]
- 22.Smits M, van Goor H, Kallewaard JW, Verbeek PP, Ludden GDS. Evaluating value mediation in patients with chronic low-back pain using virtual reality: contributions for empirical research in Value Sensitive Design. Health Technol (Berl) 2022;12(4):765–778. doi: 10.1007/s12553-022-00671-w. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Slatman S, Ostelo R, van Goor H, Staal JB, Knoop J. Physiotherapy with integrated virtual reality for patients with complex chronic low back pain: protocol for a pragmatic cluster randomized controlled trial (VARIETY study) BMC Musculoskelet Disord. 2023 Feb 20;24(1):132. doi: 10.1186/s12891-023-06232-0. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Turk DC, Dworkin RH, Allen RR, et al. Core outcome domains for chronic pain clinical trials: IMMPACT recommendations. Pain. 2003;106(3):337–345. doi: 10.1016/j.pain.2003.08.001. doi. [DOI] [PubMed] [Google Scholar]
- 25.Overton M, Ward S, Swain N, et al. Are ecological momentary assessments of pain valid and reliable? a systematic review and meta-analysis. Clin J Pain. 2023 Jan;39(1):29–40. doi: 10.1097/AJP.0000000000001084. doi. [DOI] [PubMed] [Google Scholar]
- 26.Nicholas MK. The pain self-efficacy questionnaire: Taking pain into account. Eur J Pain. 2007 Feb;11(2):153–163. doi: 10.1016/j.ejpain.2005.12.008. doi. Medline. [DOI] [PubMed] [Google Scholar]
- 27.Fish RA, McGuire B, Hogan M, Morrison TG, Stewart I. Validation of the chronic pain acceptance questionnaire (CPAQ) in an Internet sample and development and preliminary validation of the CPAQ-8. Pain. 2010 Jun;149(3):435–443. doi: 10.1016/j.pain.2009.12.016. doi. Medline. [DOI] [PubMed] [Google Scholar]
- 28.Kraaimaat FW, Bakker ABH, Evers AWM. Pijncoping-strategieën bij chronische pijnpatiënten: de ontwikkeling van de pijn-coping-inventarisatielijst (PCI) [article in dutch] Radboud University. 1997. [05-10-2023]. https://repository.ubn.ru.nl/handle/2066/24661 URL. Accessed.
- 29.Kraaimaat FW, Evers AWM. Pain-coping strategies in chronic pain patients: psychometric characteristics of the pain-coping inventory (PCI) Int J Behav Med. 2003;10(4):343–363. doi: 10.1207/s15327558ijbm1004_5. doi. Medline. [DOI] [PubMed] [Google Scholar]
- 30.Maas L, Vet H, Köke A, Bosscher RJ, Peters ML. Psychometric properties of the Pain Self-Efficacy Questionnaire (PSEQ): Validation, prediction, and discrimination quality of the Dutch version. Eur J Psychol Assess. 2012;28(1):68–75. doi: 10.1027/1015-5759/a000092. doi. [DOI] [Google Scholar]
- 31.Reneman MF, Dijkstra A, Geertzen JHB, Dijkstra PU. Psychometric properties of Chronic Pain Acceptance Questionnaires: A systematic review. Eur J Pain. 2010 May;14(5):457–465. doi: 10.1016/j.ejpain.2009.08.003. doi. [DOI] [PubMed] [Google Scholar]
- 32.Forerunner® 255 series owner’s manual. Garmin. 2022. [26-01-2023]. https://www8.garmin.com/manuals/webhelp/GUID-676967A0-1B23-4384-9BC9-76F3D643F1C8/EN-US/Forerunner_255_OM_EN-US.pdf URL. Accessed.
- 33.Verhage F. Koninklijke Van Gorcum; 1964. Intelligentie en leeftijd: Onderzoek bij Nederlanders van twaalf tot zevenenzeventig jaar [report in Dutch] [Google Scholar]
- 34.Manolov R, Gast DL, Perdices M, Evans JJ. Single-case experimental designs: Reflections on conduct and analysis. Neuropsychol Rehabil. 2014 Jul 4;24(3-4):634–660. doi: 10.1080/09602011.2014.903199. doi. [DOI] [PubMed] [Google Scholar]
- 35.Tate R, Perdices M. Single-Case Experimental Designs for Clinical Research and Neurorehabilitation Settings: Planning, Conduct, Analysis and Reporting. Routledge; 2018. doi. ISBN.978-0-429-48818-4 [DOI] [Google Scholar]
- 36.Bulté I, Onghena P. When the truth hits you between the eyes. Methodology (Gott) 2012 Aug;8(3):104–114. doi: 10.1027/1614-2241/a000042. doi. [DOI] [Google Scholar]
- 37.Bulté I, Onghena P. The single-case data analysis package: analysing single-case experiments with R software. J Mod App Stat Meth. 2013;12(2):450–478. doi: 10.22237/jmasm/1383280020. doi. [DOI] [Google Scholar]
- 38.Parker RI, Vannest KJ, Davis JL. Effect size in single-case research: a review of nine nonoverlap techniques. Behav Modif. 2011 Jul;35(4):303–322. doi: 10.1177/0145445511399147. doi. [DOI] [PubMed] [Google Scholar]
- 39.Vannest KJ, Parker RI, Gonen O, Adiguzel T. Single Case Research: web based calculators for SCR analysis. Single Case Research. 2011. [24-01-2025]. https://singlecaseresearch.org/calculators/ URL. Accessed.
- 40.Jacobson NS, Truax P. Clinical Significance: A Statistical Approach to Defining Meaningful Change in Psychotherapy Research. American Psychological Association; 1992. Methodological issues & strategies in clinical research; pp. 631–648. doi. ISBN.978-1-55798-154-7 [DOI] [PubMed] [Google Scholar]
- 41.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;94(2):149–158. doi: 10.1016/S0304-3959(01)00349-9. doi. [DOI] [PubMed] [Google Scholar]
- 42.Braun V, Clarke V. Using thematic analysis in psychology. Qual Res Psychol. 2006 Jan;3(2):77–101. doi: 10.1191/1478088706qp063oa. doi. [DOI] [Google Scholar]
- 43.Henschke N, Maher CG, Refshauge KM, et al. Prognosis in patients with recent onset low back pain in Australian primary care: inception cohort study. BMJ. 2008 Jul 7;337:a171. doi: 10.1136/bmj.a171. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44.Von Korff M, Miglioretti DL. A prognostic approach to defining chronic pain. Pain. 2005;117(3):304–313. doi: 10.1016/j.pain.2005.06.017. doi. [DOI] [PubMed] [Google Scholar]
- 45.Wang CK, Myunghae Hah J, Carroll I. Factors contributing to pain chronicity. Curr Pain Headache Rep. 2009 Feb;13(1):7–11. doi: 10.1007/s11916-009-0003-3. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46.Matthias MS, Bair MJ. The patient–provider relationship in chronic pain management: where do we go from here? Pain Med. 2010 Dec;11(12):1747–1749. doi: 10.1111/j.1526-4637.2010.00998.x. doi. [DOI] [PubMed] [Google Scholar]
- 47.Garcia LM, Birckhead BJ, Krishnamurthy P, et al. An 8-Week self-administered at-home behavioral skills-based virtual reality program for chronic low back pain: double-blind, randomized, placebo-controlled trial conducted during COVID-19. J Med Internet Res. 2021 Feb 22;23(2):e26292. doi: 10.2196/26292. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 48.Maddox T, Oldstone L, Sparks CY, et al. In-home virtual reality program for chronic lower back pain: a randomized sham-controlled effectiveness trial in a clinically severe and diverse sample. Mayo Clinic Proceedings: Digital Health. 2023 Dec;1(4):563–573. doi: 10.1016/j.mcpdig.2023.09.003. doi. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 49.Darnall BD, Krishnamurthy P, Tsuei J, Minor JD. Self-administered skills-based virtual reality intervention for chronic pain: randomized controlled pilot study. JMIR Form Res. 2020 Jul 7;4(7):e17293. doi: 10.2196/17293. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 50.Furukawa TA, Noma H, Caldwell DM, et al. Waiting list may be a nocebo condition in psychotherapy trials: a contribution from network meta‐analysis. Acta Psychiatr Scand. 2014 Sep;130(3):181–192. doi: 10.1111/acps.12275. doi. [DOI] [PubMed] [Google Scholar]
- 51.Ummels D, Cnockaert E, Timmers I, den Hollander M, Smeets R. Use of virtual reality in interdisciplinary multimodal pain treatment with insights from health care professionals and patients: action research study. JMIR Rehabil Assist Technol. 2023 Nov 10;10:e47541. doi: 10.2196/47541. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 52.Goudman L, Jansen J, Billot M, et al. Virtual reality applications in chronic pain management: systematic review and meta-analysis. JMIR Serious Games. 2022 May 10;10(2):e34402. doi: 10.2196/34402. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 53.Tuck N, Pollard C, Good C, et al. Active virtual reality for chronic primary pain: Mixed methods randomized pilot study. JMIR Form Res. 2022 Jul 13;6(7):e38366. doi: 10.2196/38366. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 54.Griffin A, Wilson L, Feinstein AB, et al. Virtual reality in pain rehabilitation for youth with chronic pain: Pilot feasibility study. JMIR Rehabil Assist Technol. 2020;7(2):e22620. doi: 10.2196/22620. doi. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 55.Knoerl R, Lavoie Smith EM, Weisberg J. Chronic pain and cognitive behavioral therapy: An integrative review. West J Nurs Res. 2016 May;38(5):596–628. doi: 10.1177/0193945915615869. doi. Medline. [DOI] [PubMed] [Google Scholar]
- 56.Garrett B, Taverner T, McDade P. Virtual reality as an adjunct home therapy in chronic pain management: An exploratory study. JMIR Med Inform. 2017 May 11;5(2):e11. doi: 10.2196/medinform.7271. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 57.Bergen N, Labonté R. “Everything Is Perfect, and We Have No Problems”: Detecting and limiting social desirability bias in qualitative research. Qual Health Res. 2020 Apr;30(5):783–792. doi: 10.1177/1049732319889354. doi. [DOI] [PubMed] [Google Scholar]
- 58.Ganz JB, Ayres KM. Methodological standards in single-case experimental design: Raising the bar. Res Dev Disabil. 2018 Aug;79:3–9. doi: 10.1016/j.ridd.2018.03.003. doi. Medline. [DOI] [PubMed] [Google Scholar]
- 59.Watson JA, Ryan CG, Cooper L, et al. Pain neuroscience education for adults with chronic musculoskeletal pain: a mixed-methods systematic review and meta-analysis. J Pain. 2019 Oct;20(10):1140. doi: 10.1016/j.jpain.2019.02.011. doi. Medline. [DOI] [PubMed] [Google Scholar]
- 60.Lier EJ, de Vries M, Steggink EM, Ten Broek RPG, van Goor H. Effect modifiers of virtual reality in pain management: a systematic review and meta-regression analysis. PAIN. 2023 Aug 1;164(8):1658–1665. doi: 10.1097/j.pain.0000000000002883. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
