Virtual reality simulation for reducing pain in children

  • Protocol
  • Intervention



This is the protocol for a review and there is no abstract. The objectives are as follows:

To assess the effects of immersive and non-immersive virtual reality simulation for reducing pain in children in any healthcare setting


Description of the condition

Healthcare examinations, treatments, procedures and interventions are typical extreme stressors that can lead to pain for children (Melnyk 2000; Horstman 2002; Rassin 2004; Wollin 2004; Clift 2007). For the context of this review we draw on the International Association for Study of Pain 2011 (originally cited 1979) definition of pain as "an unpleasant sensory and emotional experience associated with actual or potential tissue damage, or described in terms of such damage". This definition highlights that pain has both sensory (i.e. pain intensity) and emotional (i.e. any negative affect secondary to pain such as distress; including anxiety, fear and/or stress) facets; which can sometimes be difficult to distinguish between (Goodenough 1999; McGrath 2008; Brown 2012; Curtis 2012). This may be especially the case for younger child (< 8 years of age) populations who by virtue of their developmental abilities may be unable meaningfully to differentiate pain from other unpleasant emotions such as fear and anxiety (Goodenough 1999; Blount 2006). These two dimensions of pain (i.e. pain intensity and pain-related distress) are important to consider - ensuring pain management strategies reduce not only pain intensity but also the distress, anxiety and/or fear associated with medical treatment-related pain (Goodenough 1999). 

Children can feel "threatened by the monster of medical care" where they fear being hurt, forced and violated by the adults delivering that care (Forsner 2009 p. 522). Pain results in anxiety and stress, which, in turn, negatively impacts not only on a child’s ability to cope with the treatment/intervention but also on his/her recovery (Li 2009). Inadequate relief of pain during childhood treatments may have long-term negative effects on future pain tolerance and pain responses (Young 2005).

Non-pharmacological techniques (e.g. imagery, hypnosis, story-telling, play, music) have long been promoted as useful adjuncts to pharmacological analgesics (Butler 2005; Klassen 2008; Landier 2010). Yet, aside from distraction and hypnosis, there is limited evidence to support the efficacy of many of these conventional psychological interventions (e.g. breathing, relaxation, guided imagery, music) for reducing procedure-related pain in children (Stinson 2008; Uman 2008). In addition, it has been recently documented that children may benefit more from interactive (e.g. playing a video game) as opposed to passive (e.g. watching a video game) distraction strategies (Wohlheiter 2013). One such recent ‘active’ adjunctive analgesic technique gaining momentum is virtual reality (Hoffman 2011).

Description of the intervention

Virtual reality, also referred to as virtuality, is defined as a computer technology which creates a simulated environment/world that users perceive as comparable to real world objects/events (Aguinis 2001; Weiss 2003; Hoffman 2004; Chan 2007). The user’s attention is drawn into the virtual world away from real world visual, auditory and tactile stimuli by the multi-sensory (i.e. sight, sound, touch) nature of the virtual environment (Gold 2006). Virtual reality simulated interventions can vary considerably in terms of three core aspects: types of equipment used; content and nature of the virtual world; and levels of engagement users might have. Virtual reality simulation draws the user’s attention to a virtual world/environment using real-time computer graphics and various input (e.g. position trackers, mouse and data glove) and output (e.g. shutter glasses, head-mounted displays, haptic and audiovisual) devices that make the person an active participant within a computer-generated three dimensional world. Interaction, navigation and immersion are key characteristics of virtual reality systems (Aguinis 2001).

The content of some virtual reality simulated interventions has been developed specifically for certain types of procedures (e.g. Snow World and Ice Cream Factory devised for burn wound dressings) (Hoffman 2004; Chan 2007), whereas other virtual reality simulated interventions are selected for convenience to engage children at the time of invasive medical procedures (e.g. Virtual Gorilla) (Gershon 2003, Wolitzky 2005). All virtual reality systems are categorised according to how immersive or non-immersive they are. With non-immersive systems, the user is connected to the virtual world (by an external monitor) but can still communicate with the real world (e.g. the healthcare environment) (Nilsson 2009). With full immersion, the user’s visual perception of stimuli in the outside world is blocked as they become fully enveloped in the computer-generated virtual environment through the use of a head-mounted display and a tracker position sensor (e.g. a helmet and headphones which exclude visual and auditory inputs from the healthcare environment) (Weiss 2003; Gold 2006). It is this sense of presence and immersive attention (i.e. the ability to give users the sense they are somewhere else) that sets virtual reality apart from other technological interventions such as watching television or video movies, or playing simulated or interactive video games (Weiss 2003; Steele 2003; Hoffman 2004; Chan 2007; Nilsson 2009; Gorini 2011).

How the intervention might work

While virtual reality simulation has been used in many contexts (e.g. treating phobias and post-traumatic stress disorders; training military and medical personnel), for the purposes of this review the focus is on the use of virtual reality simulation in the reduction of pain intensity and pain-related distress associated with medical treatments/interventions. The theory of how virtual reality simulation works in such instances is as a form of distraction; where distraction is defined as “the purposeful focusing of attention away from undesirable sensations” (Mobily 1993). Distraction is a common coping mechanism used by school aged children and adolescents for enduring unpleasant situations (Schneider 2000). Distraction interventions function by diverting the child’s attention away from the stimulus producing the pain and refocusing the child’s attention towards a more pleasant and positive stimulus (i.e. the virtual environment) (McCaul 1984; Schneider 2000). Virtual reality interventions are thought to manifest analgesic effects by altering pain perception through distracting user attention away from the painful procedure, in addition to changing the way a person interprets incoming pain signals, consequently reducing the amount of pain-related brain activity (as seen on MRI imagery) (Morris 2009). Virtual reality exposure can target cognitive and affective pain pathways, thereby decreasing pain intensity, distress, and anxiety by altering how pain signals are processed in the central nervous system. This is achieved by a number of mechanisms including attentional distraction, conditioning of virtual reality imagery and reduced pain.

Virtual reality distraction has been used, for example, to minimise children’s anxiety associated with chemotherapy (Schneider 1999; Ahmadi 2001), to reduce children’s pain during burn wound care (Hoffman 2000; Hoffman 2001; Hoffman 2004; Das 2005), to access intravenous ports in paediatric oncology patients (Wolitzky 2005), to alleviate pain/anxiety for invasive medical procedures such as venipuncture, lumbar puncture, and bone marrow aspirates (Gershon 2003; Wint 2002; Gold 2006; Nilsson 2009), to help adolescents with cerebral palsy as they endure physiotherapy (Steele 2003), and to reduce children’s preoperative anxiety using handheld video games or films (Patel 2006; Low 2008). Together with pharmacological interventions, distraction is thought be to an effective pain management strategy by cognitively redirecting attention away from pain to a more pleasant stimulus, thereby assisting children to cope with the distress of medical treatments. Long-term benefits include advantages for later adult life, as pain experienced during medical treatments in childhood is predictive of pain during subsequent medical procedures and avoidance of medical care during young adulthood (Blount 2006). 

Why it is important to do this review

Pain impacts on child and parent satisfaction with healthcare delivery and services. In an investigation of the views and experiences of children in Council of Europe member states, Kilkelly 2011 found that 60.1% of child participants rated ‘not being in pain’ as an important element of health care. Yet evidence still suggests that acute pain management in children is not always optimal (Cummings 1996; Taylor 2008; Groenewald 2012). Recent figures estimate that 27% of children experience moderate to severe pain in hospital, with teenagers and infants experiencing higher prevalence rates of 38% and 32% respectively (Groenewald 2012). This can impact on children’s physiological, psychological and emotional well being, in both the short and long term.

It is inevitable that children admitted to healthcare settings will likely be exposed to potentially painful procedures on a daily basis. For instance, Stevens 2011 reported that more than three quarters (78.2%) of child participants (n = 3822) in their study had undergone at least one painful procedure in a 24-hour period preceding data collection. While each child was exposed to an average of 6.3 (range 1 to 50) procedures, only a small portion (28.3%) of children had interventions specifically linked to the painful procedure. While acknowledging that certain procedures are essential for routine medical and surgical care, these procedures/treatments can cause pain for the child. With the use of technology becoming increasingly prevalent in children’s daily lives, alongside the drive towards e-health and the empowered patient, it seems reasonable to propose that interactive technologies, if proven effective, should be considered as vital intervention vehicles for enhancing health outcomes for children. One such intervention is virtual reality simulation. The use of virtual reality during healthcare procedures/treatments can create a child-friendly and developmentally sensitive environment, thereby contributing to the European campaign for a child-friendly approach to health care (Council of Europe 2011).

Virtual reality simulation is a recent technological advancement with the potential to be a powerful distractor for modulating children’s pain when they are undergoing healthcare treatments (e.g. intravenous cannulation, lumbar puncture, wound dressings, chemotherapy, bone marrow aspirates). For instance, Gold 2006 reported that children who underwent intravenous cannulae placement without distraction reported a fourfold increase in affective pain when compared to children immersed in a virtual reality intervention. Additionally, children who received a virtual reality intervention were twice as satisfied with their pain management as compared to children not exposed to a virtual reality intervention. Schneider 2000 found 82% of children indicated that their chemotherapy treatment was better with virtual reality as compared to previous chemotherapy treatment without virtual reality. Parents were also satisfied with the use of virtual reality interventions and believed such interventions did reduce children’s pain and enhance children’s cooperation during medical treatments (Das 2005; Gold 2006). In a recent review, Hoffman 2011 reported a 35% to 50% reduction in procedural pain in burn patients when in a distracting immersive virtual reality.

Despite these positive evaluations and reports of pain reduction, there remains uncertainty over the effectiveness of virtual reality interventions (Uman 2006; Morris 2009; Nilsson 2009; Dahlquist 2010). In addition, in comparison to other simpler forms of non-pharmacological distraction interventions (e.g. imaginary, breathing, positive thinking), there have been some common criticisms levelled at virtual reality such as high costs, bulky equipment, the need for specialist technological skills and the potential for cyber-sickness, all of which may threaten the widespread implementation of virtual reality for therapeutic healthcare interventions (Bohil 2011). It is important to conduct this systematic review to evaluate the efficacy of virtual reality simulations as pain distractors during healthcare treatments. As few psychological interventions incorporate, or evaluate the effectiveness of, modern and novel interactive technologies such as virtual reality, this review compliments other Cochrane systematic reviews evaluating the effectiveness of non-pharmacological distraction-based interventions for minimising pain in children when undergoing medical treatments including Uman 2006's review 'Psychological interventions for needle-related procedural pain and distress in children and adolescents'.


To assess the effects of immersive and non-immersive virtual reality simulation for reducing pain in children in any healthcare setting


Criteria for considering studies for this review

Types of studies

Randomised controlled trials (RCTs), including cross-over and cluster RCTs.

Types of participants

Children aged from birth up to and including 18 years, with acute or chronic pain in any healthcare setting.

Types of interventions


Any technology aimed at creating a simulated virtual environment/world, which may include immersive and/or non-immersive virtual reality of any intensity or duration, with the purpose of reducing pain. These interventions may be used with or without pharmacological support.

We will include interventions that use any combination of input and output devices (e.g. mouse and shutter glasses; position tracker and head-mounted display). We will exclude interventions where the user is a passive observer, such as watching a virtually-simulated movie as opposed to actively engaging in a virtual environment through physical movement.


The intervention will be compared against standard treatment, no intervention, any other active intervention and/or any other immersive and/or non-immersive virtual reality.

Types of outcome measures

Primary outcomes
  • Child pain

Secondary outcomes
  • Adverse effects related to engagement with virtual reality simulation. These may include motion sickness, ocular problems (e.g. eye strain, blurred vision), balance disturbances, headaches, fatigue and repetitive strain injuries.

  • Child satisfaction with virtual reality simulation

  • Child pain-related distress (including anxiety, fear and/or stress)

  • Parent anxiety

  • Administration of rescue analgesia (i.e. administration of additional analgesic medications to treat acute pain not controlled by child’s scheduled analgesic regimen)

  • Cost, which may include cost of the virtual reality intervention, duration of child’s treatment, and length of child’s recovery time

Search methods for identification of studies

Electronic searches

We will search the following electronic databases:

  • The Cochrane Central Register of Controlled Trials (CENTRAL, The Cochrane Library, latest issue)

  • MEDLINE (OvidSP) (1989 to present)

  • EMBASE (OvidSP) (1989 to present)

  • CINAHL (EbscoHOST) (1989 to present)

  • PsycINFO (OvidSP) (1989 to present)

The strategy for MEDLINE (OvidSP), compiled by John Kis-Rigo, Trials Search Co-ordinator, Cochrane Consumers and Communication Group, is presented at Appendix 1, and will be tailored to the above databases. A combination of controlled vocabulary under the existing databases' organisational systems (e.g. MeSH and EMTREE) and free text terms will be used. We will not apply language restrictions.

Searching other resources

For grey literature we will search:

  • Proceedings from conferences e.g. VR, Games for Health Europe, Med-e-Tel, Interaction Design and Children

  • ProQuest Digital Dissertations and Theses

  • Index to Theses (Ireland and UK)

  • TrialsCentralTM (

  • Clinical trials register (

  • WHO Clinical Trial Search Portal (

  • Current Controlled Trials (

We will search reference lists from retrieved eligible studies for other studies potentially eligible for inclusion. We will handsearch relevant journals (e.g. Virtual Reality (start date 1995 to latest edition), The International Journal of Virtual Reality (start date 1998 to latest edition), Open Virtual Reality Journal (start date 2009 to latest edition). We will contact experts in the field and authors of included studies about other potentially-relevant studies.

Data collection and analysis

Selection of studies

Two review authors (VL, AM) will search for trials using the databases and resources described above. Two review authors (VL, AM) will independently assess each title and abstract retrieved from the electronic searches for relevance. Any discrepancies will be resolved through discussion with a third author (DD) acting as arbiter as required. If no abstract is available, we will source and assess the full paper. For studies deemed potentially to meet the inclusion criteria, we will obtain full texts of the studies. Two review authors (VL, AM) will independently assess these full texts against the inclusion criteria before a final decision regarding inclusion/exclusion is confirmed. Any discrepancies will be resolved by consensus or discussion with a third review author (DD) acting as arbiter where necessary.

We will list all potentially relevant papers excluded from the review at full-text stage in the 'Characteristics of Excluded Studies' table, noting reasons for exclusion. Citation details and any available information about ongoing studies will be provided. We will collate and report multiple details of the same study/duplicate publications, to ensure that each study (rather than each report) is the unit of interest in the review. We will use an adapted PRISMA flow chart to report the screening and selection process.

Data extraction and management

We will design, pilot and amend as necessary a data extraction form based on the Cochrane Consumers and Communication Review Group template. At least two review authors(VL, AM) will independently extract and manage data from each included RCT using the tailored data extraction form. Data to be extracted from included studies will include the following items: 

  • Methods: aim of study, study design, method of participant recruitment, funding source, declaration of interests for primary investigators, statistical methods and consumer involvement.

  • Risk of bias: as specified under Assessment of risk of bias in included studies.

  • Participants: description, participant inclusion and exclusion criteria, geographical location, setting, number, age, gender, ethnicity, principal and stage of diagnosis, type of procedure/treatment receiving. 

  • Intervention: details of intervention (including aim, content, format, source, setting) and control/usual care, delivery of intervention (including timing, frequency, duration), providers of the intervention and intervention fidelity/integrity.

  • Outcomes: primary and secondary outcome measures (as detailed under Types of outcome measures), timing of assessment and methods of assessing outcome measures, follow up for non-respondents and adverse events.

Any discrepancies in data extraction between the two review authors will be resolved through and discussion or if required, consultation with a third review author (DD). The first review author (VL) will enter the data into Review Manager software (RevMan 2012), with the second review author (AM) checking the accuracy of data entry. For studies where data appear to be missing or unclear, we will attempt to obtain these data or further clarification through correspondence with the original authors of the studies.

Assessment of risk of bias in included studies

In accordance with guidance from the Cochrane Handbook of Systematic Reviews of Interventions (Higgins 2011) and the Cochrane Consumers and Communication Review Group (Ryan 2011) we will use the 'Risk of bias' tool and the tables in RevMan 2012 to assess and report the risk of bias for each outcome in the domains: blinding (participants, personnel, outcome assessment) and completeness of outcome data, and for each trial in the following domains: sequence generation; allocation concealment; selective outcome reporting; and any other possible sources of bias (e.g. baseline comparability of groups and source of funding) (Ryan 2011). We will also report on the validity and reliability of outcome measures.

We will describe the study and judge each item as low risk, high risk or unclear risk of bias, as set out in Higgins 2011.

If cross-over designs and cluster RCTs are included in the review, we will systematically assess their risk of bias by extending the above tool to include specific questions for cross-over designs (e.g. random ordering of receiving intervention; evaluation of carry-over effect) and cluster trials (e.g. selective recruitment of cluster participants; baseline reporting of comparability of clusters) (Higgins 2011; Ryan 2011). We will assess the quality of these studies systematically in accordance with the Cochrane Consumers and Communication Review Group guidelines to ascertain the risk of bias (Ryan 2011).

Two review authors (VL, AM) will independently assess the methodological risk of bias of included studies. Any disagreements will be resolved by discussion and consensus, with a third author (DD) acting as arbiter as required. If information is not clear, we will seek additional information about included studies from the principal investigator of the trial. We will incorporate the results of the 'Risk of bias' assessment into the review through systematic narrative description and commentary about each quality element for each included trial. We will assess the overall risk of bias across included trials and make a judgement about the internal validity of the review’s results. We will explore the impact of the level of bias through sensitivity analyses.

Measures of treatment effect

Data will be analysed using the Cochrane Collaboration's Review Manager (RevMan) 5.2 software (RevMan 2012). For dichotomous outcomes, we will report risk ratios (RR) and 95% confidence intervals (CI). For continuous outcomes, we will report mean differences (MD) (if outcomes are measured in the same way between trials) and 95% CI. For trials that use different methods to measure the same outcome we will use standardised mean differences (SMD) and 95% CI. We will undertake a meta-analysis if studies are sufficiently similar in design, interventions and outcomes (see Data synthesis).

Unit of analysis issues

Issues may arise from the inclusion of cross-over designs and cluster RCTs. If applicable the data will be analysed according to recommendations in theCochrane Handbook of Systematic Reviews of Interventions (Higgins 2011).  In cluster trials, where reported we will use effect size estimates and standard errors that have been adjusted in the analysis for clustering, and combine the studies using the generic inverse-variance method (Higgins 2011, section 16.3). We will adjust sample sizes using the methods described in the Cochrane Handbook using an estimate of the intra-cluster correlation co-efficient (ICC) derived from the trial (if possible), from a similar trial or from a study of a similar population. If we use ICCs from other sources, we will report this and conduct sensitivity analyses to investigate the effect of variation in the ICC. In cross-over trials, where reported we will use the effect estimate and standard deviation based on a paired t-test and combine the studies using the generic inverse-variance method (Higgins 2011, section 16.4). We will seek statistical advice for this part of the analysis.

Dealing with missing data

We will contact study authors for missing data. Where complete data are available, analysis of outcomes will be conducted on an intention-to-treat basis (i.e. all randomised participants will be included in the analysis and participants will be kept in the group to which they were randomised regardless of whether or not they received the allocated intervention). Where this is not possible (i.e. data remain missing), we will conduct an analysis based on the number of participants for whom outcome data are known. As part of our 'Risk of bias' assessment, we will report the number of participants lost to follow-up and the levels of, and reasons for, attrition in each trial. We will investigate the impact of including studies with high levels of missing data in the overall assessment of treatment effect by using sensitivity analysis.

Assessment of heterogeneity

Where studies are considered similar enough (based on consideration of populations, interventions, or methodological features) to allow pooling of data using meta-analysis, we will assess the degree of heterogeneity by visual inspection of forest plots and by examining the statistical heterogeneity in each meta-analysis using the Tau² (tau-squared), I², and Chi² statistics. We will regard heterogeneity as substantial if:

(a) the I² value is high (exceeding 30%); and


(b) there is inconsistency between trials in direction or magnitude of effects (judged visually), or a low (< 0.10) P value in the Chi² test for heterogeneity;


(c) the estimate of between-study heterogeneity (Tau²) is above zero.

If we identify substantial heterogeneity, we will investigate it using subgroup and sensitivity analyses. We will consider whether an overall summary is meaningful, and if it is, use random-effects analysis to produce it.

Where we detect substantial clinical, methodological or statistical heterogeneity across included studies we will not report pooled results from meta-analysis but will instead use a narrative approach to data synthesis. In this event we will attempt to explore possible clinical or methodological reasons for this variation by grouping studies that are similar in terms of populations, intervention features, or methodological features to explore differences in intervention effects.

Assessment of reporting biases

If sufficient studies are available (i.e. 10 trials), we will evaluate reporting biases graphically using funnel plots. We will conduct formal tests for funnel plot asymmetry; for continuous outcomes we will use the test proposed by Egger 1997, and for dichotomous outcomes we will use the test proposed by Harbord 2006. If asymmetry is detected in any of these tests or is suggested by a visual assessment, we will perform exploratory analyses to investigate it. Where we suspect reporting bias, we will attempt to contact study authors asking them to provide missing outcome data. Where this is not possible, and the missing data are thought to introduce serious bias, we will explore the impact of including such studies in the overall assessment of results by a sensitivity analysis. We will assess reporting bias qualitatively based on the characteristics of the included studies (e.g. if only small studies that indicate positive findings are identified for inclusion), and if information that we obtain from contacting experts and authors or studies suggests that there are relevant unpublished studies.

Data synthesis

We will use the Review Manager software (RevMan 2012) to carry out statistical analysis. If we identify enough studies suitable to be combined and undergo quantitative analysis we will conduct meta-analysis. An assessment of whether the included trials are similar enough in terms of participants, settings, intervention, comparison and outcome measures will determine our decision to meta-analyse data, or not, to ensure meaningful conclusions from a statistically-pooled result. A random-effects model will be employed for meta-analysis based on the anticipated variability in the populations and interventions of included studies.

Where studies are not suitable for meta-analysis (i.e. we are unable to pool data statistically), we will group the data based on the category that best explores the heterogeneity of studies and makes most sense to the reader (i.e. by interventions, populations or outcomes). Within each category we will present the data in tables and summarise the results narratively.

'Summary of findings' table

Based on the methods described in Chapter 11 of the Cochrane Handbook for Systematic Reviews of Interventions (Schünemann 2011), we will prepare a ‘Summary of findings’ table to present the meta-analysis results. Results of the meta-analysis will be presented for the main comparisons of the review, the primary outcome child pain and the following secondary outcomes: child satisfaction with virtual reality simulation, child pain-related distress and parent anxiety, as outlined in the section on Types of outcome measures. For each assumed risk cited in the table(s), we will provide a source and rationale, and the GRADE system will be used to rank the quality of the evidence using GRADEprofiler (GRADEpro) software (Schünemann 2011). If meta-analysis is not possible, we will present results in a narrative ‘Summary of findings’ table format (drawing on Chan 2011 as an example).

Subgroup analysis and investigation of heterogeneity

Where there are sufficient data, and where it is appropriate within the context of the review, we will conduct subgroup analysis according to: 

  • participant age groups: examining the effect on younger (0 to 9 years) versus older (10 to 18 years) aged children, and

  • intervention immersiveness: examining the effect of immersive versus non-immersive virtual reality simulated interventions.

Subgroup analyses will be limited to primary outcomes.

Sensitivity analysis

Sensitivity analysis will be performed by separating high quality from low quality trials. We will define ‘high quality’ as a trial having low risk of bias for sequence generation and adequate allocation concealment and low risk of bias for loss to follow up, classified as less than 20% for primary outcome data. After examination of individual study characteristics, low quality trials will be removed from the analysis to examine the effect on the pooled effects of the intervention. A sensitivity analysis for plausible variations in estimated intra-cluster correlation coefficients (ICCs) will be performed when unit-of-analysis errors arise in cluster randomised trials and the ICCs have been estimated for these studies.

Sensitivity analyses will be limited to primary outcomes. We will conduct a sensitivity analysis to determine the influence of validated versus non-validated scales on the effects of intervention on outcomes.

Consumer participation

The standard editorial process of the Cochrane Consumers and Communication Review Group includes feedback on the protocol and review from one to two consumer referees in addition to health professionals. The first author of the review engages in research in the field of children’s health care and services with particular emphasis on the voice and visibility of child patients themselves. These child perspectives will be drawn upon in the review, alongside children’s perspectives of virtual reality simulation use in health care. We also aim to obtain feedback from relevant consumer representative organisations (e.g. Children in Hospital Ireland, Association of Paediatric Anaesthetists of Great Britain and Ireland).


We thank the staff and editors of the Cochrane Consumers and Communication Review Group for their support, assistance and comments on this protocol; especially Megan Prictor (Managing Editor), Rebecca Ryan (Research Fellow) and John Kis-Rigo (Trials Search Coordinator). 


Appendix 1. MEDLINE Search Strategy

1. exp child/

2. exp infant/

3. adolescent/

4. minors/

5. pediatrics/

6. (child* or infant* or newborn or neonat* or baby or babies or adolescen* or pediatric* or youth* or teen*).tw,hw.

7. or/1-6

8. virtual reality exposure therapy/

9. (virtual or virtuality or vr).tw.

10. user computer interface/

11. computer simulation/

12. computer

13. ((simulated or augmented or mediated) adj3 (reality or world* or environment*)).tw.

14. video games/

15. (videogam* or ((video or computer or electronic or online or on-line or simulation or role playing) adj gam*)).tw.


17. ((head or helmet) adj mounted).tw.

18. (immersi* or spatial presence or lifelike or life-like).tw.

19. (interactive adj3 distraction*).tw.

20. or/8-19

21. 7 and 20

22. exp pain/

23. (pain* or ache* or anesthe* or analges* or suffering or anguish*).tw,hw.

24. anxiety/

25. exp fear/

26. (anxious* or anxiet* or fear* or panic* or dread* or worry* or agitation or agitated or apprehensi* or nervous* or distress* or catastrophiz* or discomfort*).tw,hw.

27. or/22-26

28. 21 and 27

29. randomized controlled

30. controlled clinical

31. randomized.ab.

32. placebo.ab.

33. drug therapy.fs.

34. randomly.ab.

35. trial.ab.

36. groups.ab.

37. or/29-36

38. 28 and 37

Contributions of authors

Veronica Lambert conceived the idea for the protocol and wrote the first draft of the protocol. All review authors (Anne Matthews, Paula Hicks, Lorraine Boran and Declan Devane) were involved in all aspects of the protocol development providing general and methodological advice.

Declarations of interest

Lorraine Boran is a co-applicant on a US patent application for the Placebo Responder software, which has been financed by the National Digital Research Centre, Ireland. She is also a shareholder director of Neurosynergy Games Ltd., a startup neurotech company, which aims to develop cognitive (brain) training, fitness and assessment software.  

Lorraine will not be involved in assessing any studies which relate in any way to these programmes. Her role in the protocol and review is to provide input on issues related to her area of expertise on the cognitive neuroscience of executive function and attention.

Paula Hicks has been involved in the research and development of virtual communities for children in hospital and ICT interventions preparing children for surgery. She will not assess for inclusion or extract data from any studies relating to projects in which she was involved.

Other authors: None known