Evidence map›Paper›PMID 35907935›Full record

Trial reportScientific reports2022

Virtual reality and its use in post-operative pain following laparoscopy: a feasibility study.

Olivia Payne, Vinayak Smith, Daniel L Rolnik, Miranda Davies-Tuck, Ritesh Warty, Densearn Seo, Lima Wetherell, Hamsaveni Kalina Murday, Amrish Nair, Rashvinder Kaur and 1 more

Open access · goldAbstract readRandomized Controlled Trial
In one paragraph

Trial report in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
6.1field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed, 1 synthesis or guideline pooled it, 28 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Article
  4. Immersive Virtual Reality for Postoperative Pain Among Older Adults: A Scoping Review.Annals of surgery open : perspectives of surgical history, education, and clinical approaches · 2025
    Review
  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Extended reality for biomedicine.Nature reviews. Methods primers · 2023
    Article
  13. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 3 institutions in 2 countries.

Olivia Payne *Department of Obstetrics and Gynaecology, Monash University, 246 Clayton Road, Clayton, VIC, 3168, Australia.
Vinayak Smith *Department of Obstetrics and Gynaecology, Monash University, 246 Clayton Road, Clayton, VIC, 3168, Australia. Vinayak.Smith@monash.edu.
Daniel L RolnikDepartment of Obstetrics and Gynaecology, Monash University, 246 Clayton Road, Clayton, VIC, 3168, Australia.
Miranda Davies-TuckDepartment of Obstetrics and Gynaecology, Monash University, 246 Clayton Road, Clayton, VIC, 3168, Australia.
Ritesh WartyDepartment of Obstetrics and Gynaecology, Monash University, 246 Clayton Road, Clayton, VIC, 3168, Australia.
Densearn SeoCentral Clinical School, Faculty of Medicine, Nursing, and Health Science, Monash University, 99 Commercial Rd, Melbourne, VIC, 3004, Australia.
Lima WetherellDepartment of Obstetrics and Gynaecology, Monash University, 246 Clayton Road, Clayton, VIC, 3168, Australia.
Hamsaveni Kalina MurdayDepartment of Obstetrics and Gynaecology, Monash University, 246 Clayton Road, Clayton, VIC, 3168, Australia.
Amrish NairBiorithm Pte Ltd, 81 Ayer Rajah Crescent 03-53, Singapore, 139967, Singapore.
Rashvinder KaurBiorithm Pte Ltd, 81 Ayer Rajah Crescent 03-53, Singapore, 139967, Singapore.
Beverley VollenhovenDepartment of Obstetrics and Gynaecology, Monash University, 246 Clayton Road, Clayton, VIC, 3168, Australia.
Monash University · AUBiotronik (Singapore) · SGHudson Institute of Medical Research · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pain following laparoscopic surgery remains a neglected healthcare issue. Virtual reality-mediated therapy's (VRT) analgesic potential could address this. However, its effect in this setting remains unexplored. We aimed to establish the feasibility and safety of VRT as an adjunct analgesic following gynaecological laparoscopy and explore differences between active distraction and passive meditation content. 35 women were enrolled into an open crossover pilot and randomised to either intervention group 1 (active then passive content) or intervention group 2 (passive then active content) following surgery. VRT was administered in two 10-min segments with a 10-min washout period in between. Pain scores, opioid requirements and side effects were recorded before and after each segment whilst questionnaires evaluated acceptability. We observed a significant reduction in pain over time for the entire study population (F = 8.63, p < 0.0005) but no differences between intervention groups, in contrast to many studies demonstrating an increase in pain during this time. During segment one, intervention group 1 (n = 18) were administered significantly less opioid than intervention group 2 (n = 17) [0.0 (0.0-7.5) vs. 3.0(0.0-10.0), p = 0.04]. Intervention group 1 rated the VRT experience significantly higher than intervention group 2 (7.97 vs. 6.62. p = 0.017). 97.1% (n = 34) would recommend VRT to a friend and use it as the standard-of-care in future procedures. These results demonstrate that post-operative VRT is feasible and safe. However, adequately powered studies are needed to appropriately determine its efficacy.

Indexed as

LaparoscopyVirtual RealityAnalgesicsAnalgesics, OpioidFeasibility StudiesFemaleHumansPostoperative PainAnalgesicsAnalgesics, Opioid

Identifiers

PMID35907935
PMCPMC9338945
OpenAlexW4288802075

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.