A review of participant recruitment transparency for sound validation of hip surgery simulators: a novel umbrella approach

Abstract

Malposition of implants is associated with complications, higher wear and increased revision rates in total hip replacement (THR) along with surgeon inexperience. Training THR residents to reach expert proficiency is affected by the high cost and resource limitations of traditional training techniques. Research in extended reality (XR) technologies can overcome such barriers. These offer a platform for learning, objective skill-monitoring and, potentially, for automated certification. Prior to their incorporation into curricula however, thorough validation must be undertaken. As validity is heavily dependent on the participants recruited, there is a need to review, scrutinise and define recruitment criteria in the absence of pre-defined standards, for sound simulator validation. A systematic review on PubMed and IEEE databases was conducted. Training simulator validation research in fracture, arthroscopy and arthroplasty relating to the hip was included. 46 validation studies were reviewed. It was observed that there was no uniformity in reporting or recruitment criteria, rendering cross-comparison challenging. This work developed Umbrella categories to help prioritise recruitment, and has formulated a detailed template of fields and guidelines for reporting criteria so that, in future, research may come to a consensus as to recruitment criteria for a hip “expert” or “novice”.

Keywords:

• Hip
• simulation
• training
• VR
• validation

Correction Statement

This article has been republished with minor changes. These changes do not impact the academic content of the article.

Acknowledgements

Many thanks to Louise Burgess and Tikki Immins from the Orthopaedic Research Institute at BU for helping with the PRISMA process.

Notes

1 Also referred to as total hip arthroplasty (THA).

2 In this context this includes wearable head-mounted displays (HMDs) in Augmented Reality (AR), Virtual Reality (VR), Mixed Reality (MR), as well as static PC-based platforms, and excludes traditional simulation such as stand-alone cadaveric, animal or synthetic bone/manikin platforms.

3 www.prismastatement.org/PRISMAStatement

4 Though one literature review of orthopaedic simulators has done so by stating rigid definitions for both [28].

5 This category should not be confused with Predictive criterion validity, which often requires data from transfer validity studies to be able to estimate levels of skills transfer.

6 Plotly Technologies Inc. Collaborative data science. Montréal, QC, 2015. https://plot.ly

7 https://trends.google.com/trends/explore?date=all&q=%2Fm%2F07_ny

8 https://www.fundamentalvr.com/

9 https://ossovr.com/

10 https://oramavr.com/

11 https://www.virtamed.com/en/

12 Amount of experience is unknown as the study does not report the number of prior cases participants have performed/assisted/observed

13 https://www.rcseng.ac.uk/careers-in-surgery/trainees/foundation-and-core-trainees/surgery-career-paths/

14 https://www.vive.com/uk/product/vive-pro-eye/overview/

15 https://www.microsoft.com/en-us/hololens

16 Depending on the simulator’s place in the training curricula.

Additional information

Funding

This research was undertaken as part of project THRiLS, which is match-funded by Bournemouth University and Dorset Creative.