SIM: The Surgery Imagery Mindset and Preparing for Surgery

2021 ◽  
pp. 000313482110488
Author(s):  
Michael J. Asken ◽  
Vanessa A. Hortian ◽  
Colby Elder ◽  
Harold C. Yang

Discussed under various terms such as mental skills, mental rehearsal, cognitive training, and non-technical skills, psychological performance skills are gaining greater acceptance for their contributions to excellence in surgical performance. Mental imagery, specifically performance-enhancing mental imagery for surgeons, has received the greatest attention in the surgical literature. As part of the surgeon’s imagery mindset (SIM), this form of mental rehearsal contributes to optimal surgical performance for both developing and practicing surgeons. We discuss the nature of SIM and describe 5 basic guidelines for maximizing the application of performance-enhancing mental imagery in surgical contexts.

1982 ◽  
Vol 4 (1) ◽  
pp. 41-51 ◽  
Author(s):  
E. Dean Ryan ◽  
Jeff Simons

To investigate the mental imagery aspect of mental rehearsal, 80 male traffic officers from the California Highway Patrol learned a novel balancing task during a single session. Based on a pretest questionnaire, subjects were categorized as imagers, nonimagers, or occasional imagers and assigned to one of six groups accordingly: imagers asked to use imagery in mental rehearsal, imagers asked to try not to use imagery, nonimagers asked not to use imagery, nonimagers asked to try to use imagery, physical practice, or no practice. It was hypothesized that a person's preferred cognitive style would prove most effective for use in mental rehearsal and that using another style would cause a decrement in learning. Improvement scores indicated no differences between subjects who initially reported typically using imagery and those reported typically not using it, but groups asked to use imagery in mental rehearsal were superior to those asked not to (p<.001). Overall, physical practice was better than the grouped mental rehearsal conditions, and both were better than no practice. Subjects reporting strong visual imagery were superior to those with weak visual images (p<.03), and those reporting strong kinesthetic imagery were superior to those with weak kinesthetic images (p<.03). Regardless of one's typical cognitive style, the use of vivid imagery appears quite important for enhancement of motor performance through mental rehearsal.


2018 ◽  
Vol 122 (6) ◽  
pp. 1075-1081 ◽  
Author(s):  
Nicholas Raison ◽  
Kamran Ahmed ◽  
Takashige Abe ◽  
Oliver Brunckhorst ◽  
Giacomo Novara ◽  
...  

2014 ◽  
Vol 187 (1) ◽  
pp. 65-71 ◽  
Author(s):  
Carolyn Chen ◽  
Lee White ◽  
Timothy Kowalewski ◽  
Rajesh Aggarwal ◽  
Chris Lintott ◽  
...  

2016 ◽  
Vol 15 (7) ◽  
pp. 206
Author(s):  
N. Raison ◽  
K. Ahmed ◽  
O. Brunckhorst ◽  
D. Eldred-Evans ◽  
A. Gavazzi ◽  
...  

2015 ◽  
Vol 05 (02) ◽  
pp. 107-115
Author(s):  
Sabeur Hamrouni ◽  
Jaouad Alem ◽  
Sylvain Baert ◽  
Ines Bouguerra

Humaniora ◽  
2013 ◽  
Vol 4 (1) ◽  
pp. 500
Author(s):  
Esther Widhi Andangsari ◽  
Pingkan C.B. Rumondor

The present study analyzed a profiling of hope of Indonesian badminton athletes with international achievements. Previous studies have shown that hope was positively related to various outcomes such as sports, academics, physical health, psychological adjustment, and psychotherapy. The participants were consisted of athletes used to play between 70’s and 90’s. This study utilized a qualitative approach with interpretative phenomenological analysis. Nine mental skills of athletes were used as a guideline of semi-structured interview. The verbatim of interview then was analyzed with hope components. Hope was constructed by three components: goals, pathways, and agency thinking. The analysis of participants’ experience showed nine major themes that are: attitude, motivation, goals and commitment, people skills, self-talk, mental imagery, managing anxiety, managing emotion, and concentration, with twelve subordinates themes. These themes are similar with high-hope people’s characteristics. 


2017 ◽  
Vol 213 (2) ◽  
pp. 318-324 ◽  
Author(s):  
Dimitrios Stefanidis ◽  
Nicholas E. Anton ◽  
Lisa D. Howley ◽  
Eric Bean ◽  
Ashley Yurco ◽  
...  

2017 ◽  
Vol 197 (4S) ◽  
Author(s):  
Nicholas Raison ◽  
Kamran Ahmed ◽  
Takashige Abe ◽  
Abdullatif Aydin ◽  
Oliver Brunckhorst ◽  
...  

2021 ◽  
Vol 108 (Supplement_7) ◽  
Author(s):  
Recai Yilmaz ◽  
Alexander Winkler-Schwartz ◽  
Aiden Reich ◽  
Rolando Del Maestro

Abstract Aims Excellent surgical technical skills are of paramount importance to perform surgical procedures, safely and efficiently. Virtual reality surgical simulators can both simulate real operations while providing standardized, risk-free surgical hands-on experience. The integration of AI (artificial intelligence) and virtual reality simulators provides opportunities to carry out comprehensive continuous assessments of surgical performance. We developed and tested a deep learning algorithm which can continuously monitor and assess surgical bimanual performance on virtual reality surgical simulators. Methods Fifty participants from four expertise levels (14 experts/neurosurgeons, 14 senior residents, 10 junior residents, 12 medical students) performed a simulated subpial tumor resection 5 times and a complex simulated brain tumor operation once on the NeuroVR platform. Participants were asked to remove the tumors completely while minimizing bleeding and damage to surrounding tissues employing a simulated ultrasonic aspirator and bipolar forceps. A deep neural network continually tracked the surgical performance utilizing 16 performance metrics generated every 0.2-seconds. Results The deep neural network was successfully trained using neurosurgeons and medical students’ data, learning the composites of expertise comparing high and lower skill levels. The trained algorithm was able to score the technical skills of individuals continuously at 0.2-second intervals. Statistically significant differences in average scores were identified between the 4 groups. Conclusions AI-powered surgical simulators provide continuous assessment of bimanual technical skills during surgery which may further define the composites necessary to train surgical expertise. To our knowledge, this is the first attempt in surgery to continuously assess surgical technical skills using deep learning.


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