Journal of neurosurgery. Spine · 2024
Innovative growth and development of a neurological surgery residency cadaveric spine-simulation training program: a single-institution experience.
СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Unger Robert, Schreiner Bryan, Pang Brandi W, Obayashi James T, McCartney Shirley, Dingman Jackie, Selden Nathan R, Dogan Aclan, Ciporen Jeremy N
Аннотация
OBJECTIVE: Cadaveric and dry 3D model-based simulation training is a valuable educational tool for neurosurgical residents. Such simulation training is an opportunity for residents to hone technical skills and decision-making and enhance their neuroanatomy knowledge. The authors describe the growth and development of the Oregon Health & Science University Department of Neurological Surgery resident-focused, hands-on, spine-simulation surgery courses and provide details of course evaluations, layout, and setup.
METHODS: A four-part spine surgical simulation series, including two human cadaveric and two dry 3D model-based courses, was created to provide resident spine procedure training. Residents participated in the spine simulation series (2017-2021) and completed annual course curriculum and anonymous post-course evaluations. Evaluations included both Likert scale items and free-text responses. Responses to Likert scale items were analyzed in Python. Free-text responses were quantified using the Valence Aware Dictionary for Sentiment Reasoner. Descriptive statistics were calculated and plotted using Python's seaborn and matplotlib library modules.
RESULTS: The analysis included 129 spine (occipitocervical, thoracolumbar, and spine model fusion I and II) simulation course evaluations. Likert responses demonstrated high average responses for evaluation questions (4.67 ± 0.90 and above). The average compound sentiment value was 0.58 ± 0.28.
CONCLUSIONS: This is the first time Likert responses and sentiment analysis have been used to demonstrate how neurosurgical residents positively value a hands-on spine simulation training. Simulation is an essential component of neurosurgical resident education training. The authors encourage other neurosurgical education programs to develop and leverage spine simulation as a teaching tool.
METHODS: A four-part spine surgical simulation series, including two human cadaveric and two dry 3D model-based courses, was created to provide resident spine procedure training. Residents participated in the spine simulation series (2017-2021) and completed annual course curriculum and anonymous post-course evaluations. Evaluations included both Likert scale items and free-text responses. Responses to Likert scale items were analyzed in Python. Free-text responses were quantified using the Valence Aware Dictionary for Sentiment Reasoner. Descriptive statistics were calculated and plotted using Python's seaborn and matplotlib library modules.
RESULTS: The analysis included 129 spine (occipitocervical, thoracolumbar, and spine model fusion I and II) simulation course evaluations. Likert responses demonstrated high average responses for evaluation questions (4.67 ± 0.90 and above). The average compound sentiment value was 0.58 ± 0.28.
CONCLUSIONS: This is the first time Likert responses and sentiment analysis have been used to demonstrate how neurosurgical residents positively value a hands-on spine simulation training. Simulation is an essential component of neurosurgical resident education training. The authors encourage other neurosurgical education programs to develop and leverage spine simulation as a teaching tool.