Content area

Abstract

Background

Although beneficial for patients through its minimally invasive nature, laparoscopic surgery creates unique training challenges due to limited instrument maneuverability, absence of stereovision, and inadequate real-time feedback. Traditional training models rely on subjective instructor evaluations, which are time-consuming and lack objective error detection. This study evaluates the efficacy of an Automated Error Detection System (AEDS), designed to provide real-time feedback on mistouch error counts, in improving laparoscopic skill acquisition compared to conventional methods.

Methods

Forty novice participants were recruited and randomized into Group A (AEDS-enhanced training) and Group B (traditional training). Group A underwent a crossover design: 10 min of baseline training without AEDS followed by 10 min with AEDS. Group B completed 20 min of traditional training. The training program encompassed standardized laparoscopic tasks designed to simulate real surgical procedures. Performance metrics, including task completion time and the number of errors made, were recorded for each participant through AEDS. Confidence levels were assessed through self-reported questionnaires. Furthermore, statistical analysis was performed to evaluate the effectiveness of AEDS. A paired t-test was utilized to assess error reductions within the AEDS group, and Bland-Altman analysis was used to analyze the self-estimate error bias. Also, a Wilcoxon signed-rank test evaluated improvements in confidence levels attributable to the system, while a Mann-Whitney U test was conducted to compare performance metrics between the AEDS and traditional training groups.

Results

Group A demonstrated a 24% reduction in errors post-AEDS (mean: 78.1 to 59.4, p < 0.001), outperforming Group B (mean: 67.4, p < 0.001). Participants significantly underestimated errors without AEDS (mean bias: +9.9 errors). Confidence levels in Group A increased from 2.4 to 3.6, significantly surpassing Group B’s improvement (median: 3) (p < 0.001). Real-time feedback bridged perceptual gaps, enhancing both technical precision and self-assessment accuracy.

Conclusion

The integration of AEDS into laparoscopic training significantly reduces operational errors, accelerates skill acquisition, and boosts trainee confidence by providing objective feedback. These findings advocate for adopting AEDS in surgical education to standardize training outcomes, mitigate overconfidence, and improve patient safety. Future studies should explore AEDS scalability across advanced procedural modules and diverse trainee cohorts.

Clinical trial number

Not applicable.

Details

1009240
Business indexing term
Title
Enhancing laparoscopic surgery training: a comparative study of traditional models and automated error detection system
Publication title
Volume
25
Pages
1-12
Publication year
2025
Publication date
2025
Section
Research
Publisher
Springer Nature B.V.
Place of publication
London
Country of publication
Netherlands
e-ISSN
14726920
Source type
Scholarly Journal
Language of publication
English
Document type
Journal Article
Publication history
 
 
Online publication date
2025-05-08
Milestone dates
2025-01-16 (Received); 2025-04-25 (Accepted); 2025-05-08 (Published)
Publication history
 
 
   First posting date
08 May 2025
ProQuest document ID
3201523502
Document URL
https://www.proquest.com/scholarly-journals/enhancing-laparoscopic-surgery-training/docview/3201523502/se-2?accountid=208611
Copyright
© 2025. This work is licensed under http://creativecommons.org/licenses/by-nc-nd/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Last updated
2025-05-09
Database
ProQuest One Academic