TY  - JOUR
AU  - Noroozi, Mohammad
AU  - St John, Ace
AU  - Masino, Caterina
AU  - Laplante, Simon
AU  - Hunter, Jaryd
AU  - Brudno, Michael
AU  - Madani, Amin
AU  - Kersten-Oertel, Marta
PY  - 2024
DA  - 2024/7/25
TI  - Education in Laparoscopic Cholecystectomy: Design and Feasibility Study of the LapBot Safe Chole Mobile Game
JO  - JMIR Form Res
SP  - e52878
VL  - 8
KW  - gamification
KW  - serious games
KW  - surgery
KW  - education
KW  - laparoscopic cholecystectomy
KW  - artificial intelligence
KW  - AI
KW  - laparoscope
KW  - gallbladder
KW  - cholecystectomy
KW  - mobile game
KW  - gamify
KW  - educational game
KW  - interactive
KW  - decision-making
KW  - mobile phone
AB  - Background:  Major bile duct injuries during laparoscopic cholecystectomy (LC), often stemming from errors in surgical judgment and visual misperception of critical anatomy, significantly impact morbidity, mortality, disability, and health care costs. Objective:  To enhance safe LC learning, we developed an educational mobile game, LapBot Safe Chole, which uses an artificial intelligence (AI) model to provide real-time coaching and feedback, improving intraoperative decision-making. Methods:  LapBot Safe Chole offers a free, accessible simulated learning experience with real-time AI feedback. Players engage with intraoperative LC scenarios (short video clips) and identify ideal dissection zones. After the response, users receive an accuracy score from a validated AI algorithm. The game consists of 5 levels of increasing difficulty based on the Parkland grading scale for cholecystitis. Results:  Beta testing (n=29) showed score improvements with each round, with attendings and senior trainees achieving top scores faster than junior residents. Learning curves and progression distinguished candidates, with a significant association between user level and scores (P=.003). Players found LapBot enjoyable and educational. Conclusions:  LapBot Safe Chole effectively integrates safe LC principles into a fun, accessible, and educational game using AI-generated feedback. Initial beta testing supports the validity of the assessment scores and suggests high adoption and engagement potential among surgical trainees. 
SN  - 2561-326X
UR  - https://formative.jmir.org/2024/1/e52878
UR  - https://doi.org/10.2196/52878
DO  - 10.2196/52878
ID  - info:doi/10.2196/52878
ER  -