119 The Potential of Low-fidelity Arthroscopic Simulation Training in Trauma and Orthopaedic Surgery: A Systematic Review of Experimental Studies

Abstract

AimIn an era of budget tightening and work-hour guideline reductions that have significantly reduced surgical exposure, low-fidelity arthroscopic simulators have an essential role to play in surgical training. The COVID-19 pandemic has only further amplified the need for alternative training models, as 91% of orthopaedic trainees have had elective procedures cancelled. The purpose of this systematic review is to synopsise the limited literature regarding the effectiveness of low-fidelity training models in the instruction of novices, and to formulate recommendations for future studies.MethodThe Embase, PubMed, Web of Science and Scopus databases were electronically searched. Studies from any year that described the use of orthopaedic, low-fidelity arthroscopic training models in novice populations were included. Questionnaires, case studies and review studies were excluded. Risk of bias assessments were also conducted for all studies.Results16 studies were identified. Using the PRISMA algorithm, 6 studies were deemed relevant. A cross-study comparison revealed low-fidelity arthroscopic simulators reduced time to completion outcomes (P < 0.05), increased ASSET scores (P < 0.01) and confirmed face validity and transfer of skills (cadaver, live patients).ConclusionsLow-fidelity simulator training significantly improves the arthroscopic performance of novices, without the high setup costs and practical constraints of high-fidelity equivalents. Low-fidelity arthroscopic simulators remain a promising training apparatus in an era of reduced surgical exposure (COVID-19). We have identified the need for consistent outcome measures with greater sample sizes across future studies. We recommend the use of standardised pre-intervention teaching (e.g., ABOS curriculum) and further transference, construct, and face validity evaluations to support future result interpretations.