Arthroscopic knee simulation in Singapore: Will virtual reality simulation-based training become a mainstay of surgical education?

R. Radhakrishnan; A. Padki; D.M.E. Huang

doi:10.1016/j.jorep.2025.100657

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Research Article

2026

:5;

100657

doi:

10.1016/j.jorep.2025.100657

Arthroscopic knee simulation in Singapore: Will virtual reality simulation-based training become a mainstay of surgical education?

R. Radhakrishnan , A. Padki, D.M.E. Huang

Department of Orthopaedic Surgery, Singapore General Hospital, Singapore

⁎Corresponding author: R. Radhakrishnan. ramesh.radhakrishnan@mohh.com.sg

Received: 2025-3-15, Accepted: 2025-3-25, Published: 2025-3-26

The Authors

Disclaimer:
This article was originally published by Reed Elsevier India Pvt. Ltd. and was migrated to Scientific Scholar after the change of Publisher.

Abstract

Traditional orthopedic surgical training follows the Halstedian "see one, do one, teach one" model, which is increasingly challenged by concerns over patient safety, limited operative opportunities, and restricted working hours. Virtual reality (VR)-based arthroscopic knee simulation has emerged as a promising adjunct to conventional training, allowing trainees to practice skills in a risk-free environment. This study evaluates the effectiveness of VR-based arthroscopy training in Singapore and explores its potential integration into surgical education programs.

A prospective study was conducted at Singapore General Hospital, involving 30 participants, including Junior Residents, Senior Residents, and Consultants. The Virtamed ArthroS™ virtual arthroscopy simulator was used for training and assessment. Performance metrics such as overall scores, procedural time, safety measures, and camera path length were analyzed before and after training. Statistical analyses, including Wilcoxon Signed-Rank Test, Kruskal-Wallis Test, and correlation analyses, were performed to evaluate skill improvements and the impact of repeated simulation exposure.

Significant improvements were observed in overall scores (p < 0.001), overview scores (p < 0.001), and procedural time (p < 0.001), demonstrating enhanced arthroscopic proficiency across all participant groups. However, no significant differences were found between groups in terms of safety scores and camera path length. Consultants initially outperformed Junior and Senior Residents, but post-training assessments showed no significant intergroup differences, suggesting that VR simulation enables skill leveling across experience levels. Correlation analysis indicated weak, non-significant relationships between the number of completed simulations and performance improvements.

VR-based arthroscopic knee simulation is an effective training modality that enhances technical proficiency and reduces procedural errors. While the study highlights its potential role in orthopedic education, further research is needed to optimize integration into residency curricula, address technological limitations, and assess long-term skill retention. Widespread adoption in Singapore's orthopedic training programs may help bridge the gap in hands-on surgical exposure, ultimately improving patient outcomes.

IV, Cohort studies.

Keywords

Simulation based training

Surgical education

Arthroscopic knee simulation

Training cost

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1 Introduction

Surgical training has traditionally followed the Halstedian model of "see one, do one, teach one," which relies on progressive hands-on experience under expert supervision. However, increasing concerns over patient safety, ethical considerations, and restricted working hours have challenged the adequacy of this approach. In orthopedic surgery, particularly arthroscopic knee procedures, the steep learning curve presents an additional challenge. Trainees require extensive practice to develop the necessary skills in triangulation, depth perception, and instrument handling, which are critical for achieving proficiency in minimally invasive techniques. In response to these challenges, simulation-based training has gained traction as an adjunct to conventional surgical education.

Virtual reality (VR) simulation has emerged as a promising tool in orthopedic surgery training, offering a structured and risk-free environment where trainees can hone their skills before operating on actual patients. These platforms allow trainees to practice surgical procedures repeatedly, leading to better retention and understanding of complex techniques. Advanced arthroscopic simulators can provide real-time haptic feedback, objective performance metrics, and customizable training modules to cater to different skill levels. Multiple studies have demonstrated the effectiveness of VR-based arthroscopy training in improving technical skills, reducing procedural errors, and shortening the learning curve.¹^,² By practicing in a virtual environment, trainees can make mistakes and learn from them without causing harm. This approach has been shown to significantly reduce the percentage of risk in executing arthroscopic surgeries.³ Given these advantages, VR simulation is increasingly being integrated into surgical education programs worldwide.

With an increasing number of orthopedic trainees and a growing emphasis on value-based care, opportunities for hands-on surgical training are becoming more limited.⁴ The traditional apprenticeship model, which relies heavily on direct patient interaction, is becoming less viable in today's healthcare landscape. At the same time, rising costs associated with surgical training and growing concerns over physician burnout in Singapore further highlight the need for alternative learning methods.⁵^,⁶ In this context, VR-based simulation offers a valuable solution—allowing trainees to practice surgical techniques in a controlled, low-stress environment without the pressure of real-world patient care.

Singapore, with its strong emphasis on medical education and technological innovation, is well-positioned to adopt VR simulation for arthroscopic knee training. Various institutions have been investing in simulation-based medical training to enhance clinical competency. Despite these efforts, the widespread implementation of VR-based arthroscopy training remains limited, raising questions about its feasibility, cost-effectiveness, and acceptance among orthopedic trainees and educators. Furthermore, there is currently limited research assessing the practicality and effectiveness of simulation-based surgical training within Singapore's healthcare education system. Most available data originates from international studies, which may not accurately reflect Singapore's unique healthcare infrastructure, resource allocation, or financial constraints.

The primary aim of this study is to evaluate the current state of arthroscopic knee simulation training in Singapore and explore whether VR-based simulation can become a mainstay in surgical education. In this study, we examine the barriers to adoption, including financial constraints, technological limitations, and institutional support.

By analysing these factors, we hope to provide insights into the future of VR-based arthroscopy training in Singapore and offer recommendations for its successful implementation. As surgical education continues to evolve, embracing innovative training modalities may enhance competency, improve patient outcomes, and shape the next generation of orthopedic surgeons.

2 Methods

Our prospective study was approved by the hospital's ethics committee, SingHealth Centralised Institutional Review Board, and carried out in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki. Informed written consent was also obtained from all participants.

2.1

2.1 Participant selection

Between January 2020 and December 2021, a total of 30 participants were recruited from the Department of Orthopaedic Surgery at Singapore General Hospital, a tertiary-level teaching institution. Participation in the study was voluntary and participants were grouped in accordance to their stage of training. The three groups were namely, junior residents, senior residents, as well as consultants specializing in sports surgery. The six participating consultants were all fellowship-trained arthroscopic sports surgeons with extensive experience in the field. Prior to the study, all prospective participants completed a questionnaire to provide baseline demographic data and details regarding their level of experience in arthroscopic procedures.

The Virtamed ArthroS™ virtual arthroscopy system (Virtamed AG, Schlieren, Switzerland) was utilized in this study for knee arthroscopy training.⁷ This system features an anatomically realistic knee model with soft skin, enabling physical manipulation in multiple planes, including varus/valgus stress, flexion, extension, and hyperflexion. Trainees practice fundamental arthroscopic techniques, conduct diagnostic procedures, and perform minor surgical interventions across 40 patient cases with varying pathologies. The simulator enhances instrument handling, triangulation skills, and visualization of intra-articular structures while minimizing cartilage damage. Interactive guidance aids learning, and objective performance reports provide constructive feedback for skill refinement in managing meniscal lesions, arthrosis, and synovitis. The total expenditure incurred to acquire this unit amounted to $287,200.

2.2

2.2 Simulator assessment

None of the participants had prior formal training in arthroscopic simulation before engaging with the simulator. Each participant was required to complete a series of simulated exercises, during which several performance metrics—including time to completion (TTC), number of camera movements (CM), number of instrument movements (IM), and number of errors—were recorded. These individual metrics were then combined into a composite score.

Following the completion of the initial set of exercises, participants were instructed to revisit six specific exercises, with their performance reassessed and scores recalculated. Between the initial and final assessments, participants were permitted to engage with the simulator training at their own pace. The "Guided Diagnostic and Palpation" simulation module was designated as the primary benchmark for assessment, as it was the first exercise completed by all participants and had the highest overall completion rate. In cases where participants had not completed a final assessment, the next available simulation was used.

The study assessed the final aggregate scores by evaluating the initial and final overall scores, overview performance scores, procedure duration, safety measures, and camera movement length for “guided diagnostics and palpation”. These parameters were analyzed to determine improvements in arthroscopic proficiency throughout the training period. Key arthroscopic skills such as camera path length, instrument errors were tracked, recorded, and tabulated into an easy-to-understand scoring system that residents received at the end of the session.

2.3

2.3 Statistical analysis

Statistical analysis was performed to compare the initial and final scores between the two study groups. Both descriptive and inferential statistical methods were employed. Categorical variables were summarized as frequencies and percentages, while continuous variables were presented as means with standard deviations or medians with interquartile ranges, depending on data distribution. All results were systematically tabulated for clarity.

To assess differences in paired data, the Wilcoxon Signed-Rank Test was utilized, while the Kruskal-Wallis Test was applied for comparisons across three groups. Post-hoc analysis was subsequently conducted using the Mann-Whitney U Test. These non-parametric tests were selected based on the non-normal distribution of assessed variables, as determined by the Shapiro-Wilk Test (p < 0.05). For variables following a normal distribution, Analysis of Variance (ANOVA) was employed to evaluate intergroup differences.

Additionally, Pearson's and Spearman's correlation analyses were conducted to explore the relationship between score improvements and the number of completed simulations. Pearson's correlation was applied to normally distributed variables, whereas Spearman's correlation was used for non-normally distributed variables. A statistical significance threshold of p < 0.05 was established for all tests, corresponding to a 95 % confidence interval. Statistical analyses were carried out using IBM SPSS version 27.0.1.

3 Results

Amongst the 30 participants recruited, 6 were Consultants, comprising 20.0 % of the sample. The majority were Senior Residents (n = 17, 56.7 %), while Junior Residents accounted for 23.3 % (n = 7) (Table 1).

Table 1 Descriptive Statistics of the Participants (n = 30) and scores achieved.

Designation	N (%)
Consultant	6 (20.0 %)
Senior Resident	17 (56.7 %)
Junior Resident	7 (23.3 %)

Scores Achieved For "Guided Diagnostic And Palpation" Simulation Module
Parameter	Mean ± Std.
Initial Overall Score	45 ± 21
Final Overall Score	58 ± 17
Initial Overview Score	16 ± 2
Final Overview Score	19 ± 2
Initial Procedure Time (S)	243.2 ± 114.1
Final Procedure Time (S)	209.8 ± 408.7
Initial Safety Score	16 ± 5
Final Safety Score	17 ± 5
Initial Camera Path length (cm)	92.7 ± 49.5
Final Camera path length (cm)	83.3 ± 53.6

The study encompassed a comprehensive evaluation of various parameters pertinent to the arthroscopic knee simulation. The initial guided diagnostic and palpation overall score exhibited a mean of 45 ± 21, while the final score in this category demonstrated a mean of 58 ± 17. Additionally, the initial overview score yielded a mean of 16 ± 2, which improved to a mean of 19 ± 2 in the final assessment. Moreover, the initial procedure time was recorded at a mean of 243.23 s ± 114.08, which reduced to a mean of 209.75 s ± 408.68 in the final assessment. Safety scores, both initial and final, were reported with means of 16 ± 5 and 17 ± 5, respectively. Camera path length, a crucial metric, showed an initial mean of 92.69 cm ± 49.51, and a final reduced mean of 83.31 cm ± 53.63 (Table 1).

Table 2 presents a comprehensive comparison of the initial and final measurements for various parameters related to the “Guided Diagnostic and Palpation” simulation module. Overall, there was a significant improvement in the module's performance, with the median score increasing from 45 (IQR: 39–55) at baseline to 58 (IQR: 53–60) in the final assessment (p < 0.001). Similarly, the overview score saw a notable increase, rising from a median of 17 (IQR: 15–19) to 20 (IQR: 18–20) (p < 0.001). The procedure time showed a marked reduction, decreasing from a median of 247.57 s (IQR: 145.05–337.39) initially to 113.47 s (IQR: 97.36–151.39) in the final assessment (p < 0.001). However, no significant differences were found in the safety score or camera path length between the initial and final measurements.

Table 2 Comparison of initial and final parameters of "guided diagnostic and palpation" simulation module.

Parameter	Initial		Final		P value^W
Parameter	Median	IQR	Median	IQR	P value^W
Overall score	45	39–55	58	53–60	<0.001*
Overview score	17	15–19	20	18–20	<0.001*
Procedure time (s)	247.6	145.1–337.4	113.5	97.4–151.4	<0.001*
Safety Score	18	13–20	20	18–20	0.092
Camera Path length (cm)	96.7	46.9–128.1	85.27	49.8–97.8	0.318

Table 3 offers a detailed comparison of the initial and final measurements among three distinct groups based on designation: Consultants, Senior Residents, and Junior Residents. Baseline overall score for Consultants was a median of 55 (IQR: 53–58), Senior Residents achieved a median of 44 (IQR: 40–50), and Junior Residents had a median of 31 (IQR: 0–55). A significant difference was observed among these groups (p = 0.017), with post-hoc analysis revealing that Consultants scored significantly higher than Senior Residents. In the final assessment, the median scores for Consultants, Senior Residents and Junior Residents were 60 (IQR: 54–87), 59 (IQR: 54–60), and 51 (IQR: 44–57) respectively. Post-hoc analysis suggests that no statistically significant difference was present among the groups at the final assessment (p = 0.125) (Table 4).

Table 3 Comparison of Initial and Final Parameter for "Guided Diagnostic And Palpation" Simulation Module categorized into respective designations.

	Designation						P-Value^K
	Consultant		Senior Resident		Junior Resident
	Median	IQR	Median	IQR	Median	IQR
Initial Overall Score	55	53–58	44	40–50	31	0–55	0.017*
Final Overall Score	60	54–87	59	54–60	51	44–57	0.125
Initial Overview Score	19	18–19	16	15–18	16	8–20	0.154
Final Overview Score	20	20–20	20	19–20	17	15–20	0.127
Initial Procedure Time (s)	191.9	129.5–263.2	252.9	197.1–317.5	177.7	110.4–369.8	0.620
Final Procedure Time (s)	99.3	91.3–103.7	116.8	99.04–151.4	128.7	87.0–416.7	0.453
Initial Safety Score	20	19–20	17	13–19	18	8–20	0.165
Final Safety Score	20	19–20	20	18–20	20	9–20	0.768
Initial Camera Path Length (cm)	84.0	64.8–139.4	95.6	46.9–120.8	98.2	37.9–128.1	0.934
Final Camera Path Length (cm)	84.1	80.4–86.4	90.8	49.8–99.6	84.1	30.7–120.8	0.848
Total Number Of Completed Simulations	9	4–10	11	5–13	12	10–17	0.132

Table 4 Post hoc test for initial guided diagnostic and palpation overall score.

Comparison	P value^U
Junior Resident vs Senior Resident	0.264
Junior Resident vs Consultant	0.053
Senior Resident vs Consultant	0.006*

The initial overview score exhibited only marginal variation. Consultants had a median score of 19 (IQR: 18–19), Senior Residents had a median score of 16 (IQR: 15–18), and Junior Residents had a median score of 16 (IQR: 8–20) (p = 0.154). With regards to final overview scores, Consultants achieved a median score of 20 (IQR: 20–20), Senior Residents had a median score of 20 (IQR: 19–20), and Junior Residents had a median score of 17 (IQR: 15–20) (p = 0.127). There was no statistical difference noted between the 3 groups for both initial and final overview scores (Table 3).

An analysis of procedure time, safety scores and camera path length revealed no significant differences among the groups for both the initial and final measurements. Furthermore, there was no significant difference in number of completed simulations between the initial and final assessments across the three groups: Consultants, Senior Residents, and Junior Residents (p = 0.132) (Table 3).

Table 5 presents a comparison of the changes in initial and final scores across three groups. In terms of the overall score, Consultants showed a mean change of 5 ± 14, Senior Residents demonstrated a mean change of 14 ± 11, and Junior Residents exhibited a mean change of 17 ± 23 (p = 0.328). Regarding the overview score, Consultants had a median change of 1 (IQR: 0–1), Senior Residents showed a median change of 3 (IQR: 1–4), and Junior Residents had a median change of 0 (IQR: −2 to 12) (p = 0.063). In relation to procedure time, Consultants exhibited a median change of −53.27 s, Senior Residents showed a change of −111.50 s, and Junior Residents demonstrated no change (p = 0.269). No significant differences were observed in safety scores between the groups (p = 0.618). With regards to change in camera path length, Consultants demonstrated a median change of −17.99 cm, Senior Residents showed a median change of 11.71 cm, and Junior Residents exhibited a median change of −20.28 cm (p = 0.838). Overall, there were no significant differences in the degree of change across the groups for the overall score, overview score, safety score, procedure time, or camera path length.

Table 5 Comparison of Change in Initial and Final Parameters among three groups of Designation.

Change in Initial and Final measurement	Designation						P-Value^K
	Consultant		Senior Resident		Junior Resident
	Mean	SD	Mean	SD	Mean	SD
Overall score	5	14	14	11	17	23	0.328^A
	Median	IQR	Median	IQR	Median	IQR
Overview score	1	0–1	3	1–4	0	−2–12	0.063 ^K
Procedure time (s)	−53.3	−159.5 – (−2.17)	−111.5	−161.7 – (−71.9)	0	−209.9–46.9	0.269 ^K
Safety Score	0	0–0	1	0–3	0	−8–11	0.618 ^K
Camera Path length (cm)	−18.0	−67.8–19.5	11.7	−81.1–32.3	−20.3	−45.3–47.3	0.838 ^K

Table 6 presents the results of the correlation analysis between the change in parameters and number of simulations completed. For the overall score, the correlation coefficient is −0.091, indicating a very weak negative correlation (p = 0.631). Similarly, for the overview score, the correlation coefficient is −0.106, signifying a very weak negative correlation (p = 0.576). For the safety score, the correlation coefficient is −0.122, representing a very weak negative correlation (p = 0.519). In contrast, for procedure time, the correlation coefficient is 0.252, demonstrating a weak positive correlation (p = 0.180). In terms of camera path length, the correlation coefficient is 0.244, indicating a weak positive correlation (p = 0.193). All parameters did not show statistically significant correlation.

Table 6 Correlation between Change in scores and Number of Completed Simulations.

Change in Initial and Final measurement	Number of completed simulations between initial and final
Change in Initial and Final measurement	Correlation coefficient	p value
Guided diagnostic and palpation score	−0.091^r	0.631
Guided diagnostic and palpation overview score	−0.106 ^ρ	0.576
Guided diagnostic and palpation procedure time (s)	0.252 ^ρ	0.180
Guided diagnostic and palpation Safety Score	−0.122 ^ρ	0.519
Camera Path length (cm)	0.244	0.193

4 Discussion

This study aimed to evaluate the effectiveness of virtual reality (VR)-based simulation for arthroscopic knee training in Singapore, exploring its potential as a core component of surgical education. As the landscape of surgical training continues to evolve, particularly with the increasing limitations of the traditional Halstedian model, alternative training methods, such as VR simulation, offer promising solutions that provide safe, effective, and cost-efficient learning environments.⁸ Residency and fellowship programs are increasingly incorporating simulation modules to enhance learning while minimizing patient risk.^9–12 Our results highlight both the potential benefits and limitations of integrating VR simulation into orthopedic residency programs.

One of the key findings from this study was the overall improvement in performance across all participants between the initial and final assessments. Specifically, the significant increase in both the overall and overview scores, coupled with the reduction in procedure time, underscores the potential for VR-based simulation to enhance technical proficiency. The improvements in these metrics suggest that participants were able to acquire and refine their skills in a controlled, risk-free environment, leading to better outcomes in subsequent assessments. This aligns with previous studies that have demonstrated the efficacy of VR simulation in enhancing surgical skills and reducing the learning curve, particularly in minimally invasive procedures like arthroscopic surgery.^13–15 In a meta-analysis by Portelli et al. comparing traditional apprenticeship-based training with virtual reality based training, they found virtual reality not only improves efficiency, but also improved quality with reduced error rates which is similar results from this study.¹⁶ Studies have shown that VR training significantly enhances student engagement, comprehension, confidence and surgical proficiency compared to conventional methods.^17–21

The results also revealed that, while there was overall improvement, the differences in performance changes across the three groups—Consultants, Senior Residents, and Junior Residents—were not statistically significant. This lack of significant difference suggests that the benefits of VR simulation were observed across all levels of experience, although Consultants, with their greater experience, initially performed better than their Junior and Senior Resident counterparts. Interestingly, post-hoc analysis of the final scores revealed no significant differences between groups, suggesting that with repeated practice and assessment based simulations, participants at different training levels were able to achieve similar proficiency in the VR simulation. This highlights the potential of VR simulation to level the playing field in surgical training, providing an opportunity for trainees at various stages to practice and improve their skills at their own pace, regardless of their baseline level of expertise. Yari et al. found in their study that residents training on a virtual arthroscopic simulator made significant improvements in both knee and shoulder arthroscopic surgical skills with greater improvements made by more junior residents.²²

Despite the overall improvements in scores and reduction in procedure times, the study found no significant differences in safety scores or camera path length between the initial and final assessments. This could be due to the nature of the simulation, which may not fully replicate the complexity and variability of real-world surgeries. Despite the benefits, current simulation technologies face challenges in replicating the tactile and visual feedback of real surgeries. Enhancements in haptic systems are needed to improve the realism and accuracy of simulations, which is crucial for effective skill transfer.³^,²³^,²⁴ The static nature of the simulated environment might also not account for the dynamic challenges presented in live surgeries, such as unpredictable tissue behavior or patient-specific factors. As such, while VR simulation offers a structured and repeatable training environment, it is crucial to complement this training with real-world clinical exposure to ensure comprehensive skill development.²⁵

Furthermore, the correlation analysis conducted to examine the relationship between the number of completed simulations and improvements in performance metrics revealed weak correlations across all parameters. While there was a weak positive correlation in procedure time and camera path length, these relationships were not statistically significant. This suggests that simply increasing the number of simulations or lengthy workshops may not be sufficient to guarantee substantial improvements in all performance aspects. Other factors, such as the quality of training, the feedback provided, and individual learning styles, may also play crucial roles in determining how effectively trainees can transfer their skills from the simulation to real-world scenarios.

The study's findings also raise important considerations regarding the feasibility and scalability of VR-based arthroscopic training in Singapore's healthcare system. Despite the demonstrated improvements in technical performance, challenges remain in the widespread adoption of VR simulation. Financial constraints, technological limitations, and institutional support are all potential barriers to the integration of VR training into residency programs.²⁶ Atesok et al. emphasizes the importance of developing a nationwide standard curriculum for surgical specialties that includes benchmarks established by multi-institutional experts, which would help in integrating simulation training into residency programs and board certification.²⁷ A notable limitation of this study was that there was a long lag period where the simulator machine was undergoing maintenance, this was a recurrent issue and a very important one to consider in simulation training. Frequent use led to wearing down of the artificial “skin” component and this led to reduced sensitivity of the camera and probe. Future studies can ascertain the implication of simulation mechanics and maintenance to understand it's feasibility as a training tool. Additionally, the relatively low number of completed simulations across the groups in this study suggests that while the simulation provides a valuable learning tool, its utilization may be limited by factors such as time availability, institutional resources, and competing educational demands.

This study has several notable strengths. Firstly, it provides a comprehensive evaluation of virtual reality (VR)-based arthroscopic knee simulation in a real-world clinical setting, offering valuable insights into its effectiveness as an adjunct to traditional surgical training. The inclusion of participants from various stages of residency (Junior Residents, Senior Residents, and Consultants) allows for a broad assessment of the technology's utility across different levels of experience, time availability and competing demands from responsibilities at day to day work. Furthermore, the study utilized a robust methodology, employing objective performance metrics such as time to completion, camera movements, and procedure duration, which enhances the validity and reliability of the findings. These metrics offer immediate feedback, allowing trainees to identify areas for improvement and track their progress over time.²⁸

However, there are several limitations to consider. The study's sample size was relatively small, particularly in the Consultant group, which may limit the generalizability of the results. Additionally, the study did not assess the long-term retention of skills learned through VR simulation or its direct impact on clinical outcomes, which would provide more concrete evidence of its effectiveness. Large-scale trials with long-term follow-up are necessary to establish the efficacy and validity of simulation-based training across different surgical specialties.²⁹^,³⁰ Another limitation is the lack of control for potential confounding variables, such as individual learning styles or prior exposure to arthroscopic procedures, which could influence performance. Finally, the study primarily focused on technical aspects of training and did not incorporate subjective measures, such as participant satisfaction or perceived value, which could provide a more holistic understanding of the training experience.

5 Conclusion

In conclusion, this study provides valuable insights into the potential role of VR-based arthroscopy simulation in orthopedic residency training in Singapore. While the results indicate positive trends in performance improvement, there is a need for further research to assess the long-term impact of VR simulation on clinical outcomes and to explore how best to integrate this technology into the existing educational framework. Addressing the barriers to adoption and ensuring that VR simulation is effectively incorporated into residency curricula could help to enhance the quality of surgical training and, ultimately, patient care.

CRediT authorship contribution statement

R. Radhakrishnan: Formal analysis, Writing – original draft, Visualization. A. Padki: Methodology, Investigation, Writing – review & editing. D.M.E. Huang: Conceptualization, Supervision, Project administration, Writing – review & editing.

IRB

Centralised institutional review board (IRB) approval was obtained for this study.

Authorship statement

All authors agree to be accountable for all aspects of the paper, ensuring its accuracy and integrity, in accordance to the International Committee on Medical Journal Editors (ICMJE) recommendation for authorship.

Ethics statement

Funding statement

No funding was acquired.

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Introduction

Methods

Participant selection
Simulator assessment
Statistical analysis

Results

Discussion

Conclusion

CRediT authorship contribution statement

Patient's consent

Authorship statement

Ethics statement

Funding statement

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[Google Scholar]

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[Google Scholar]

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Arthroscopic knee simulation in Singapore: Will virtual reality simulation-based training become a mainstay of surgical education?

Abstract