Assessment of Laparoscopic Surgical Skills Using Similarity Network Models in Conjunction with the NASA Task Load Index
Presenter Type
UNO Graduate Student (Doctoral)
Major/Field of Study
Information Systems and Quantitative Analysis
Author ORCID Identifier
0000-0002-2159-8617
Advisor Information
Hesham H Ali
Location
MBSC Ballroom Poster # 1208 - G (Doctoral)
Presentation Type
Poster
Start Date
24-3-2023 2:30 PM
End Date
24-3-2023 3:45 PM
Abstract
Over the past few decades, there has been a dramatic shift in the instructional strategy used to prepare future surgeons. The old-fashioned method of learning by doing as an apprentice surgeon is no longer the only way to become proficient in the field. The operating room is no longer the primary location for teaching fundamental surgical skills; rather, a surgical skills laboratory is used to train students through simulation. While Simulation-based training is helpful for medical students trying to hone their skills, it hasn't become the dramatic paradigm change in clinical education that many envisioned. One critical barrier to reaching such a desired goal is the lack of reliable and objective methods for assessing the effectiveness of training sessions and the development of students. in this study, we develop a new Similarity Network Model and employ the use of the obtained networks as the central concept in establishing a new assessment tool based to be used for the evaluation of the surgical learning abilities of trainees. We also show how the proposed model can be used to assess the training processes as well. In addition, we analyze the participants' subjective overload levels based on their NASA Task Load Index scores immediately after completing various tasks to further enrich the assessment process.
Scheduling
2:30 -3:45 p.m.
Assessment of Laparoscopic Surgical Skills Using Similarity Network Models in Conjunction with the NASA Task Load Index
MBSC Ballroom Poster # 1208 - G (Doctoral)
Over the past few decades, there has been a dramatic shift in the instructional strategy used to prepare future surgeons. The old-fashioned method of learning by doing as an apprentice surgeon is no longer the only way to become proficient in the field. The operating room is no longer the primary location for teaching fundamental surgical skills; rather, a surgical skills laboratory is used to train students through simulation. While Simulation-based training is helpful for medical students trying to hone their skills, it hasn't become the dramatic paradigm change in clinical education that many envisioned. One critical barrier to reaching such a desired goal is the lack of reliable and objective methods for assessing the effectiveness of training sessions and the development of students. in this study, we develop a new Similarity Network Model and employ the use of the obtained networks as the central concept in establishing a new assessment tool based to be used for the evaluation of the surgical learning abilities of trainees. We also show how the proposed model can be used to assess the training processes as well. In addition, we analyze the participants' subjective overload levels based on their NASA Task Load Index scores immediately after completing various tasks to further enrich the assessment process.