An Epiduroscopy Simulator Based on a Serious Game for Spatial Cognitive Training (EpiduroSIM): User-Centered Design Approach.

catheters endoscopy medical education surgery

Journal

JMIR serious games
ISSN: 2291-9279
Titre abrégé: JMIR Serious Games
Pays: Canada
ID NLM: 101645255

Informations de publication

Date de publication:
27 Aug 2019
Historique:
received: 05 11 2018
accepted: 16 04 2019
revised: 31 03 2019
entrez: 29 8 2019
pubmed: 29 8 2019
medline: 29 8 2019
Statut: epublish

Résumé

Performing high-level surgeries with endoscopy is challenging, and hence, an efficient surgical training method or system is required. Serious game-based simulators can provide a trainee-centered educational environment unlike traditional teacher-centered education environments since serious games provide a high level of interaction (feedback that induces learning). This study aimed to propose an epiduroscopy simulator, EpiduroSIM, based on a serious game for spatial cognitive training. EpiduroSIM was designed based on a serious game. For spatial cognitive training, the virtual environment of EpiduroSIM was modeled based on a cognitive map. EpiduroSIM was developed considering user accessibility to provide various functions. The experiment for the validation of EpiduroSIM focused on psychological fidelity and repetitive training effects. The experiments were conducted by dividing 16 specialists into 2 groups of 8 surgeons. The group was divided into beginner and expert based on their epiduroscopy experience. The psychological fidelity of EpiduroSIM was confirmed through the training results of the expert group rather than the beginner group. In addition, the repetitive training effect of EpiduroSIM was confirmed by improving the training results in the beginner group. EpiduroSIM may be useful for training beginner surgeons in epiduroscopy.

Sections du résumé

BACKGROUND BACKGROUND
Performing high-level surgeries with endoscopy is challenging, and hence, an efficient surgical training method or system is required. Serious game-based simulators can provide a trainee-centered educational environment unlike traditional teacher-centered education environments since serious games provide a high level of interaction (feedback that induces learning).
OBJECTIVE OBJECTIVE
This study aimed to propose an epiduroscopy simulator, EpiduroSIM, based on a serious game for spatial cognitive training.
METHODS METHODS
EpiduroSIM was designed based on a serious game. For spatial cognitive training, the virtual environment of EpiduroSIM was modeled based on a cognitive map.
RESULTS RESULTS
EpiduroSIM was developed considering user accessibility to provide various functions. The experiment for the validation of EpiduroSIM focused on psychological fidelity and repetitive training effects. The experiments were conducted by dividing 16 specialists into 2 groups of 8 surgeons. The group was divided into beginner and expert based on their epiduroscopy experience. The psychological fidelity of EpiduroSIM was confirmed through the training results of the expert group rather than the beginner group. In addition, the repetitive training effect of EpiduroSIM was confirmed by improving the training results in the beginner group.
CONCLUSIONS CONCLUSIONS
EpiduroSIM may be useful for training beginner surgeons in epiduroscopy.

Identifiants

pubmed: 31456580
pii: v7i3e12678
doi: 10.2196/12678
pmc: PMC6734856
doi:

Types de publication

Journal Article

Langues

eng

Pagination

e12678

Informations de copyright

©Junho Ko, Jong Joo Lee, Seong-Wook Jang, Yeomin Yun, Sungchul Kang, Dong Ah Shin, Yoon Sang Kim. Originally published in JMIR Serious Games (http://games.jmir.org), 27.08.2019.

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Auteurs

Junho Ko (J)

BioComputing Lab, Institute for Bio-Engineering Application Technology, Korea University of Technology and Education, Cheonan, Republic of Korea.

Jong Joo Lee (JJ)

Department of Neurosurgery, Yonsei University College of Medicine, Seoul, Republic of Korea.

Seong-Wook Jang (SW)

BioComputing Lab, Institute for Bio-Engineering Application Technology, Korea University of Technology and Education, Cheonan, Republic of Korea.

Yeomin Yun (Y)

Department of Neurosurgery, Yonsei University College of Medicine, Seoul, Republic of Korea.

Sungchul Kang (S)

Robot Center, Samsung Research, Seoul, Republic of Korea.

Dong Ah Shin (DA)

Department of Neurosurgery, Yonsei University College of Medicine, Seoul, Republic of Korea.

Yoon Sang Kim (YS)

BioComputing Lab, Institute for Bio-Engineering Application Technology, Korea University of Technology and Education, Cheonan, Republic of Korea.

Classifications MeSH