Use of virtual reality in managing paediatric procedural pain and anxiety: An integrative literature review
Bibliographic record
Abstract
AIMS: This integrative review aimed to identify, analyse and synthesise studies investigating the clinical efficacy of virtual reality (VR) distraction for children undergoing varying painful and anxiety-inducing medical procedures across different hospital settings and to identify implications for research and clinical practice. BACKGROUND: Virtual reality has been leveraged as a distraction tool in the healthcare setting to help patients manage procedural pain and anxiety. Initial studies in the burn wound care setting using VR as a non-pharmacological analgesia led to the use of VR during other medical procedures. DESIGN: An integrative review of the literature was conducted following the PRISMA guidelines across four electronic databases. Published studies between 2000 and 2020 investigating the clinical efficacy of VR in managing paediatric procedural pain or anxiety were included for review. RESULTS: Reviewed studies collectively included 2,174 patients aged 6 months-18 years used VR during burn wound care, post-burn physiotherapy, dental, needle-related and other procedures. Additionally, ten studies included samples with adults, for which paediatric data could not be isolated (n = 507). Overall, studies supported the efficacy of VR in managing procedural pain and anxiety in the paediatric setting. CONCLUSION: Virtual reality is redefining pain management by immersing children in a virtual world, reducing pain and anxiety at the hospital. A notable gap was the neglected use of VR in children with chronic conditions receiving orthopaedic procedures as part of their standard care. RELEVANCE TO CLINICAL PRACTICE: Ultimately, VR distraction will reduce the fear associated with medical interventions, preventing increased pain sensitivity, exacerbated anxiety and healthcare avoidance in adulthood. Nurses will play an important role in ensuring the smooth integration of VR in clinical practice by championing the technology and transferring evidence-based methods for VR use.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.012 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".