Browse Subject Areas

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here.

  • Loading metrics

Clinical efficacy of virtual reality for acute procedural pain management: A systematic review and meta-analysis

  • Evelyn Chan,

    Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Supervision, Validation, Writing – review & editing

    Affiliations Department of Paediatrics, Monash Medical Centre, Clayton, Victoria, Australia, Southern Clinical School, Monash Medical Centre, Clayton, Victoria, Australia

  • Samantha Foster,

    Roles Data curation, Investigation, Validation

    Affiliation Southern Clinical School, Monash Medical Centre, Clayton, Victoria, Australia

  • Ryan Sambell,

    Roles Data curation, Investigation, Validation

    Affiliation Southern Clinical School, Monash Medical Centre, Clayton, Victoria, Australia

  • Paul Leong

    Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Software, Supervision, Validation, Writing – original draft, Writing – review & editing

    Affiliations Southern Clinical School, Monash Medical Centre, Clayton, Victoria, Australia, Monash Lung and Sleep, Monash Medical Centre, Clayton, Victoria, Australia

Clinical efficacy of virtual reality for acute procedural pain management: A systematic review and meta-analysis

  • Evelyn Chan, 
  • Samantha Foster, 
  • Ryan Sambell, 
  • Paul Leong



Acutely painful procedures are commonplace. Current approaches to pain most often involve pharmacotherapy, however, there is interest in virtual reality (VR) as a non-pharmacological alternative. A methodologically rigorous systematic review and meta-analysis is lacking.


Following PRISMA guidelines, we searched the Cochrane Library, Ovid MEDLINE, Embase, CINAHL, ERIC, NIHR Centre for Review and Dissemination, Proquest, the System for Information on Grey Literature in Europe and the WHO International Clinical Trials Registry Platform from inception to 5 November 2017. Included studies were randomised with an experimental trial design, included a non-VR control group and examined the efficacy of VR with regards to an acutely painful clinical intervention. Bias was assessed along Cochrane guidelines, with performance bias not assessed due to the non-blindable nature of VR. We extracted summary data for maximal pain score and used standard mean difference DerSimonian-Laird random-effects meta-analysis (RevMan 5.3). This review was prospectively registered (PROSPERO CRD42017058204).


Of the 12,450 studies identified, 20 studies were eligible for the systematic review. No trials reported in sufficient detail to judge their risk of bias, and 10 studies were at high risk of bias in at least one domain. 16 studies (9 randomised controlled trials, 7 crossover studies) examining 656 individuals were included in quantitative synthesis. Pain scales were heterogenous, but mostly employed 100-point scales. Across all trials, meta-analysis was suggestive of a -0.49 (95%CI -0.83 to -0.41, p = 0.006) standardised mean difference reduction in pain score with VR. However there was a high degree of statistical heterogeneity (χ2 p<0.001, I2 81%, 95%CI for I2 70–88%), driven by randomised studies, with substantial clinical heterogeneity.


These data suggest that VR may have a role in acutely painful procedures, however included studies were clinically and statistically heterogenous. Further research is required to validate findings, establish cost efficacy and optimal clinical settings for usage. Future trials should report in accordance with established guidelines.


The management of acute pain related to healthcare interventions remains a major global healthcare challenge[1], existing at the convergence of the consumer-driven desire for patient empowerment and physician-driven desire for better outcomes[2]. For most procedures, pharmacological approaches remain the mainstay although these have significant drawbacks including imprecise titration, narrow therapeutic windows, adverse side effects, the potential for drug misuse and cost[3]. Approaches that avoid pharmacotherapy and associated interventions such as monitoring could therefore be of benefit in a multimodal armentarium[1].

Virtual reality (VR) is a developing technology which has garnered significant lay and medical attention as its cost and accessibility and quality have favourably converged. Briefly, virtual reality is a computer-generated depiction of an immersive environment which can be viewed through a headset[4]. By providing distraction, this approach is hypothesized to reduce pain by pharmacological-sparing means[4].

However, there is no comprehensive, high-quality systematic review that specifically assesses the efficacy of virtual reality on acutely painful healthcare interventions, nor has there been any quantitative data synthesis on this topic. We therefore conducted a systematic review and meta analysis to appraise the quality of published literature and to synthesize data for acute pain scores.


Study selection, data sources and search strategy

We defined VR as an intervention with an immersive, 3D display that excluded the external (real-world) environment. Studies were included if they were published in a peer reviewed journal, examined the effect of VR on an acutely painful clinical intervention and included a pain score as an outcome measure. Studies were excluded if there was no acutely painful clinical intervention, no non-VR control group or non-VR sequence or lacked an experimental design. This review and protocol was prospectively registered on PROSPERO (CRD42017058204).

Following PRISMA guidelines[5], we identified studies through reviews of the Cochrane Library, Ovid MEDLINE (1975–5 November 2017), Embase, CINAHL, ERIC, NIHR Centre for Review and Dissemination and Proquest (PRISMA checklist: S1 Checklist). The search strategy included the terms “virtual reality”, “simulation”, and “pain”: the full strategy is in S1 Appendix. For completeness, we searched the System for Information on Grey Literature in Europe and WHO International Clinical Trials Registry Platform. No language restrictions were applied. Non-English articles were machine translated and screened for inclusion. Automatic de-duplication was performed in EndNote X8.1 (Clarivate Analytics, Philadelphia USA), and manually verified by an author (EC). Citation lists of included studies were hand checked to ensure completeness. Screening was performed by two authors (SF, RS) and disagreements resolved consensus discussion with a third author (EC).

Data analysis

Summary data was extracted by one author (PL) and confirmed by another author (EC). For parallel group randomised trials (RCTs), the Cochrane risk of bias assessment tool was used[6]. For crossover trials, a published modification of this tool was employed[7]. Two authors (PL, EC) independently assessed risk of bias, with verification by the other two authors (SF, RS). Disagreements were resolved by consensus.

The following information was extracted from each study: first author name, study location, source and number of participants, ethics approval, age, sex, study design, and virtual environment and nature of painful stimulus. The primary outcome was the mean difference in maximum self-rated pain during the healthcare intervention (with and without VR). If the study included interventions other than VR, only data relevant to pain scores with and without VR was extracted. If the study had multiple treatment periods, the first was extracted. If data were not reported in an analysable format, summary measures were reconstructed from published individual patient data, or authors approached. Where data were missing, first authors were contacted twice by e-mail at one-month intervals, and if data were still missing, senior authors were contacted similarly; if authors had moved, attempts were made to contact them at their new institutions.

It was anticipated that crossover trials would pose difficulties and thus employed Elbourne’s “ideal” method (within-individual data)[8]. In brief, correlation coefficient was sought and missing data imputed by Elbourne’s published method[8]. We used standard mean difference (SMD) DerSimonian-Laird random-effects meta-analysis (RevMan 5.3, Copenhagen) to estimate effect size on pain.

Variability within studies is reported in forest plots and incorporated into the meta-analysis (I2), and interpreted in accordance with standard guidelines[9]. To quantify uncertainty in the I2 statistic, we calculated heterogeneity in I2 as recommended[10] using heterogi[11] in Stata 14.2 (College Station, Texas). The calculation requires at least two degrees of freedom.

Risk of bias was assessed but other no methods to account for this were employed. A priori, due to the obvious nature of VR, performance bias was not assessed. Detection bias was assessed as high if an unblinded investigator assessed outcomes, low if a blinded observer assessed outcomes and unclear if self-administered instruments were used. Funnel plots were inspected for asymmetry to assess for sources of bias including publication bias[12].

Role of the funding source

There was no funding source for this study. All authors had full access to data and the corresponding author takes responsibility for the decision to submit to publication.


12,450 studies were screened with 11,150 excluded, leaving 48 full text articles (Fig 1). 28 studies were excluded (predominantly because they examined non-clinical procedures), leaving 20 for qualitative synthesis.

Study characteristics are detailed in Table 1. 11 were RCTs[1323] and 9 were crossover studies[2432], studying 776 subjects. 10 studies were performed in the setting of burns wound care[16,1820,2529,32], 3 studied physiotherapy in the setting of burns[24,30,31], 5 further studies concerned needle-related procedures (largely venous access)[1315,21,23], and 2 examined minor surgical procedures[17,22]. Studies were predominantly conducted in English speaking countries (USA (n = 12), Australia (n = 3), South Africa (n = 1)). 11 trials were performed in the inpatient setting, and the remainder were outpatient studies. Pain measurement instruments were heterogenous, but mostly employed 100-point scales.

10 studies demonstrated high risk of bias in at least 1 domain (Tables 2 and 3). No trials reported in sufficient detail that their risk of bias could be sufficiently assessed across all domains. No trials were prospectively registered and only four studies[17,19,20,31] mentioned CONSORT[38] reporting guidelines. Incomplete reporting or selective reporting was judged at unclear or high risk of bias in 9 studies.

All trials had short follow up periods and thus attrition bias was generally low. 9/20 studies did not adequately describe their randomisation sequence generation, and 9/11 randomised trials did not describe their allocation concealment in sufficient detail to be assessable.

Data were generally not reported in sufficient detail for detection bias to be assessable, and only one study was assessed at low detection bias risk.

One trial[26] used a crossover design where pain was assessed as being at high risk of being different between baseline and intervention, and was therefore excluded from analysis. No crossover trials specifically reported carry-over effects.

Three further studies were excluded from meta-analysis due to missing data (one group of authors did not respond, one group had destroyed data in accordance with legislation retention requirements, and one group could not provide data due to workload constraints (personal communications)). The meta-analysis therefore consisted of 16 studies for meta-analysis: 9 RCT and 7 crossover, involving 656 individuals (Fig 2).

Fig 2. Meta-analysis of the efficacy of virtual reality in acutely painful procedures.

Statistical heterogeneity[6] was high for RCTs (n = 9, χ2 p<0.001, I2 88%, 95%CI for I2 80–93%), low for crossover studies but with a wide confidence interval for I2 (n = 6, χ2 p = 0.79, I2 20%, 95%CI for I2 0–64%) and considerable overall (n = 16, χ2 p<0.001, I2 81%, 95%CI for I2 70–88%). The relatively low number of studies available limited the assessment of the funnel plot., However, no evidence of asymmetry was seen on visual inspection and in particular studies were not absent from the bottom right corner, which would have suggested publication bias (S1 Fig)[12,39].

Meta-analysis of all studies was suggestive of a beneficial effect for VR, with a standardised mean difference pain score reduction of -0.49 (95%CI -0.83 to -0.14, p = 0.006)(Fig 2).

In post-hoc per-procedure subgroup analysis, VR had no effect for minor surgical procedures (SMD -0.65, -1.48 to 0.18, p = 0.13) or burns wound care (SMD -0.46, -1.36 to 0.44, p = 0.31)(S2 Fig). There appeared to be a favourable effect for VR on pain in needles (SMD -0.66, 95%CI -0.56 to -0.04, p = 0.02), and in burns physical therapy (SMD -0.53 95%CI -0.81 to -0.26,p<0.001), although these subgroups enrolled limited numbers of patients (227 and 104 participants respectively).

Statistical heterogeneity assessment was often limited by the relatively few studies present, and reflected in wide I2 confidence intervals. For minor surgical procedures (n = 2 studies), some heterogeneity was present (χ2 p = 0.09, I2 66%, 95%CI for I2 not calculated as too few studies), and for burns wound care (n = 7 studies), there was considerable heterogeneity (χ2 p<0.001, I2 92%, 95%CI for I2 85–95%). Though the χ2 test indicated no evidence of heterogeneity for needles (n = 4 studies, χ2 p = 0.79, I2 = 0%, 95%CI for I2 0–85%) or for burns physical therapy (n = 3 studies, χ2 p = 0.94, I2 = 0%, 95%CI for I2 0–90%), the confidence intervals for I2 were broad.


This systematic review appraises the efficacy of virtual reality for acutely painful clinical procedures, finding that studies were generally at high risk of bias. In meta-analysis, VR appeared to reduce pain in comparison with control, and in post-hoc analysis, the benefit was limited to burns physical therapy and needles.

Applying published, well-accepted criteria, 10/20 studies were at high risk of bias in one or more domain, and no trial reported completely enough for their risk of bias to be completely evaluated. No studies were prospectively registered, and the risk of incomplete or selective outcome reporting was unclear or high in 9 studies. Only four studies reported according to CONSORT guidelines[38].

Meta-analysis indicated a positive effect of VR (SMD -0.49, 95%CI -0.83 to -0.41, p = 0.006) on pain, although the strength of this finding was limited by significant clinical and statistical heterogeneity. Statistical heterogeneity was generally high. This was likely due at least in part to differences in differences in study design and study populations, as well as small study numbers. We chose random-effects meta-analysis to synthesize data in this setting. Although the overall effect may be interpreted by convention as a ‘medium’ effect size[40], benefits appear to differ across different procedural subtypes, with no statistically significant evidence for burns wounds care or minor surgical procedures. Positive effects were driven by needles studies and burns physical therapy studies, raising the possibility that the effect of VR may vary according to study population and clinical scenario. Subgroup analyses were based on small numbers of studies. Importantly, the results of this systematic review and meta analysis are based on less than 1,000 patients in total, with post-hoc subgroup analyses, so findings require confirmation. Before widespread clinical usage of VR can be recommended, large methodologically rigorous studies validating and extending these findings are required.

This study has limitations. VR is a non-blindable intervention that creates methodological issues in bias assessment. Performance bias is un-assessable, and detection bias is difficult to assess, thus we a priori defined risk categories. Measures to reduce detection bias can include using independent assessors for study outcomes[6], however, this may be logistically difficult and in paediatric subjects particularly, the patient is at risk of un-blinding the assessor. No crossover studies assessed for carryover effects. However, it seems likely that VR would be reversible and short lived and thus unlikely that VR would have a persistent effect in this clinical context. In addition, study populations were heterogenous, and the precise nature of the hardware and software employed in the VR intervention varied.

We treated VR as a homogenous intervention, although the VR environments and hardware used differed. Even if individual patient data were available, it is unlikely that we would have sufficient statistical power to separate differences between different VR types given significant confounding would exist due to study design, population, and procedure type.

Strengths of our study include a clear clinical question, prospectively registered protocol, thorough search strategy, and the use of high-quality, standardised assessment criteria with more than one assessor at each stage of the review process. We deliberately restricted our selection criteria to clinical studies that were pertinent to our clinical question to maximise external validity. No prior reviews have specifically addressed the clinical question we sought to assess. Existing reviews have not employed a systematic methodology[4], located fewer studies[41], have not performed quantitative data synthesis[42,43], or have focused on special populations[44]. The conclusion of our risk of bias assessment is broadly similar to Garrett[4], inasmuch as we found few trials to be at low risk of bias. The conclusions of our meta-analysis are broadly similar but of a lesser magnitude to Kenney[41], who found a large effect size for VR for painful stimuli in a different group of studies.


In summary, there is early evidence to suggest that VR is effective for burns physical therapy and needles. However, the quality of the underlying evidence is limited and statistically heterogenous. Thus, prior to widespread adoption of VR, there is a need for further, high-quality studies to validate findings. Trials should be prospectively registered, and reporting should be along CONSORT guidelines to minimise bias. Further studies could include cost-efficacy outcomes, and investigate the role of VR in other acutely painful procedures.

Supporting information

S1 Appendix. Search strategy.

Search executed on 5 November 2017.


S2 Fig. Post-hoc procedural type meta-analysis.



  1. 1. Upp J, Kent M, Tighe PJ. The Evolution and Practice of Acute Pain Medicine. Pain Med. 2013;14: 124–144. pmid:23241132
  2. 2. Tighe P, Buckenmaier CC, Boezaart AP, Carr DB, Clark LL, Herring AA, et al. Acute Pain Medicine in the United States: A Status Report. Pain Med Malden Mass. 2015;16: 1806–1826.
  3. 3. Frieden TR, Houry D. Reducing the Risks of Relief—The CDC Opioid-Prescribing Guideline. N Engl J Med. 2016;374: 1501–1504. pmid:26977701
  4. 4. Garrett B, Taverner T, Masinde W, Gromala D, Shaw C, Negraeff M. A Rapid Evidence Assessment of Immersive Virtual Reality as an Adjunct Therapy in Acute Pain Management in Clinical Practice: Clin J Pain. 2014;30: 1089–1098. pmid:24535053
  5. 5. Moher D, Liberati A, Tetzlaff J, Altman DG, Group TP. Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement. PLOS Med. 2009;6: e1000097. pmid:19621072
  6. 6. Higgins JPT, Altman DG, Gøtzsche PC, Jüni P, Moher D, Oxman AD, et al. The Cochrane Collaboration’s tool for assessing risk of bias in randomised trials. BMJ. 2011;343: d5928. pmid:22008217
  7. 7. Ding H, Hu GL, Zheng XY, Chen Q, Threapleton DE, Zhou ZH. The Method Quality of Cross-Over Studies Involved in Cochrane Systematic Reviews. PLOS ONE. 2015;10: e0120519. pmid:25867772
  8. 8. Elbourne DR, Altman DG, Higgins JP, Curtin F, Worthington HV, Vail A. Meta-analyses involving cross-over trials: methodological issues. Int J Epidemiol. 2002;31: 140–149. pmid:11914310
  9. 9. Higgins JPT, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency in meta-analyses. BMJ. 2003;327: 557–560. pmid:12958120
  10. 10. Ioannidis JPA, Patsopoulos NA, Evangelou E. Uncertainty in heterogeneity estimates in meta-analyses. BMJ. 2007;335: 914–916. pmid:17974687
  11. 11. Orsini N, Bottai M, Higgins J, Buchan I. HETEROGI: Stata module to quantify heterogeneity in a meta-analysis [Internet]. 2006. Available:
  12. 12. Sterne JAC, Sutton AJ, Ioannidis JPA, Terrin N, Jones DR, Lau J, et al. Recommendations for examining and interpreting funnel plot asymmetry in meta-analyses of randomised controlled trials. BMJ. 2011;343: d4002–d4002. pmid:21784880
  13. 13. Gershon J, Zimand E, Pickering M, Rothbaum BO, Hodges L. A pilot and feasibility study of virtual reality as a distraction for children with cancer. J Am Acad Child Adolesc Psychiatry. 2004;43: 1243–1249. pmid:15381891
  14. 14. Gold JI, Kim SH, Kant AJ, Joseph MH, Rizzo AS. Effectiveness of virtual reality for pediatric pain distraction during i.v. placement. Cyberpsychology Behav Impact Internet Multimed Virtual Real Behav Soc. 2006;9: 207–212. pmid:16640481
  15. 15. Gold JI, Mahrer NE. Is Virtual Reality Ready for Prime Time in the Medical Space? A Randomized Control Trial of Pediatric Virtual Reality for Acute Procedural Pain Management. J Pediatr Psychol. 2017; pmid:29053848
  16. 16. Guo C, Deng H, Yang J. Effect of virtual reality distraction on pain among patients with hand injury undergoing dressing change. J Clin Nurs. 2015;24: 115–120. pmid:24899241
  17. 17. JahaniShoorab N, Ebrahimzadeh Zagami S, Nahvi A, Mazluom SR, Golmakani N, Talebi M, et al. The Effect of Virtual Reality on Pain in Primiparity Women during Episiotomy Repair: A Randomize Clinical Trial. Iran J Med Sci. 2015;40: 219–224. pmid:25999621
  18. 18. Jeffs D, Dorman D, Brown S, Files A, Graves T, Kirk E, et al. Effect of Virtual Reality on Adolescent Pain During Burn Wound Care: J Burn Care Res. 2014;35: 395–408. pmid:24823326
  19. 19. Kipping B, Rodger S, Miller K, Kimble RM. Virtual reality for acute pain reduction in adolescents undergoing burn wound care: A prospective randomized controlled trial. Burns. 2012;38: 650–657. pmid:22348801
  20. 20. Konstantatos AH, Angliss M, Costello V, Cleland H, Stafrace S. Predicting the effectiveness of virtual reality relaxation on pain and anxiety when added to PCA morphine in patients having burns dressings changes. Burns. 2009;35: 491–499. pmid:19111995
  21. 21. Sander Wint S, Eshelman D, Steele J, Guzzetta CE. Effects of distraction using virtual reality glasses during lumbar punctures in adolescents with cancer. Oncol Nurs Forum. 2002;29: E8–E15. pmid:11845217
  22. 22. Walker MR, Kallingal GJS, Musser JE, Folen R, Stetz MC, Clark JY. Treatment Efficacy of Virtual Reality Distraction in the Reduction of Pain and Anxiety During Cystoscopy. Mil Med. 2014;179: 891–896. pmid:25102532
  23. 23. Wolitzky K, Fivush R, Zimand E, Hodges L, Rothbaum BO. Effectiveness of virtual reality distraction during a painful medical procedure in pediatric oncology patients. Psychol Health. 2005;20: 817–824.
  24. 24. Carrougher GJ, Hoffman HG, Nakamura D, Lezotte D, Soltani M, Leahy L, et al. The Effect of Virtual Reality on Pain and Range of Motion in Adults With Burn Injuries: J Burn Care Res. 2009;30: 785–791. pmid:19692911
  25. 25. Chan EA, Chung JW, Wong TK, Lien AS, Yang JY. Application of a virtual reality prototype for pain relief of pediatric burn in Taiwan. J Clin Nurs. 2007;16: 786–793. pmid:17402961
  26. 26. Das DA, Grimmer KA, Sparnon AL, McRae SE, Thomas BH. The efficacy of playing a virtual reality game in modulating pain for children with acute burn injuries: A randomized controlled trial [ISRCTN87413556]. BMC Pediatr. 2005;5. pmid:15745448
  27. 27. Hoffman HG, Patterson DR, Seibel E, Soltani M, Jewett-Leahy L, Sharar SR. Virtual reality pain control during burn wound debridement in the hydrotank. Clin J Pain. 2008;24: 299–304. pmid:18427228
  28. 28. Maani CV, Hoffman HG, Morrow M, Maiers A, Gaylord K, McGhee LL, et al. Virtual Reality Pain Control During Burn Wound Debridement of Combat-Related Burn Injuries Using Robot-Like Arm Mounted VR Goggles: J Trauma Inj Infect Crit Care. 2011;71: S125–S130. pmid:21795888
  29. 29. McSherry T, Atterbury M, Gartner S, Helmold E, Searles DM, Schulman C. Randomized, Crossover Study of Immersive Virtual Reality to Decrease Opioid Use During Painful Wound Care Procedures in Adults: J Burn Care Res. 2017; 1.
  30. 30. Morris LD, Louw QA, Crous LC. Feasibility and potential effect of a low-cost virtual reality system on reducing pain and anxiety in adult burn injury patients during physiotherapy in a developing country. Burns J Int Soc Burn Inj. 2010;36: 659–664. pmid:20022431
  31. 31. Schmitt YS, Hoffman HG, Blough DK, Patterson DR, Jensen MP, Soltani M, et al. A randomized, controlled trial of immersive virtual reality analgesia, during physical therapy for pediatric burns. Burns. 2011;37: 61–68. pmid:20692769
  32. 32. van Twillert B, Bremer M, Faber AW. Computer-Generated Virtual Reality to Control Pain and Anxiety in Pediatric and Adult Burn Patients During Wound Dressing Changes: J Burn Care Res. 2007;28: 694–702. pmid:17667488
  33. 33. McGrath PJ, Johnson G, Goodman JT, Schillinger J, Dunn J, Chapman J. CHEOPS: A behavioral scale for rating postoperative pain in children. In: Fields H, editor. Advances in Pain Research and Therapy. New York: Raven Press; 1985. pp. 395–402.
  34. 34. Hicks CL, von Baeyer CL, Spafford PA, van Korlaar I, Goodenough B. The Faces Pain Scale-Revised: toward a common metric in pediatric pain measurement. Pain. 2001;93: 173–183. pmid:11427329
  35. 35. Wong DL, Baker CM. Pain in children: comparison of assessment scales. Pediatr Nurs. 1988;14: 9–17. pmid:3344163
  36. 36. Savedra MC, Holzemer WL, Tesler MD, Wilkie DJ. Assessment of postoperation pain in children and adolescents using the adolescent pediatric pain tool. Nurs Res. 1993;42: 5–9. pmid:8424069
  37. 37. Choiniere M, Auger FA, Latarjet J. Visual analogue thermometer: a valid and useful instrument for measuring pain in burned patients. Burns. 1994;20: 229–235. pmid:8054135
  38. 38. Schulz KF. CONSORT 2010 Statement: Updated Guidelines for Reporting Parallel Group Randomized Trials. Ann Intern Med. 2010;152: 726. pmid:20335313
  39. 39. Sterne JA., Gavaghan D, Egger M. Publication and related bias in meta-analysis. J Clin Epidemiol. 2000;53: 1119–1129. pmid:11106885
  40. 40. Cohen J. Statistical power analysis for the behavioral sciences. 2nd ed. Hillsdale, N.J: L. Erlbaum Associates; 1988.
  41. 41. Kenney MP, Milling LS. The effectiveness of virtual reality distraction for reducing pain: A meta-analysis. Psychol Conscious Theory Res Pract. 2016;3: 199–210.
  42. 42. Matsangidou M, Ang CS, Sakel M. Clinical utility of virtual reality in pain management: a comprehensive research review. Br J Neurosci Nurs. 2017;13: 133–143.
  43. 43. 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: 14–21. pmid:28386517
  44. 44. Won A, Bailey J, Bailenson J, Tataru C, Yoon I, Golianu B. Immersive Virtual Reality for Pediatric Pain. Children. 2017;4: 52. pmid:28644422