妇科肿瘤学
医学
梅德林
背景(考古学)
模式
课程
医学教育
医学物理学
肿瘤科
心理学
政治学
法学
古生物学
社会科学
教育学
社会学
生物
作者
Ben‐Lawrence Kemah,Nanak Bhagat,Aayushi Pandya,Richard Sullivan,Sudha Sundar
出处
期刊:International Journal of Gynecological Cancer
[BMJ]
日期:2023-11-21
卷期号:34 (4): 619-626
被引量:1
标识
DOI:10.1136/ijgc-2023-004557
摘要
Several recent advances in gynecologic cancer care have improved patient outcomes. These include national screening and vaccination programs for cervical cancer as well as neoadjuvant chemotherapy for ovarian cancer. Conversely, these advances have cumulatively reduced surgical opportunities for training creating a need to supplement existing training strategies with evidence-based adjuncts. Technologies such as virtual reality and augmented reality, if properly evaluated and validated, have transformative potential to support training. Given the changing landscape of surgical training in gynecologic oncology, we were keen to summarize the evidence underpinning current training in gynecologic oncology. In this review, we undertook a literature search of Medline, Google, Google Scholar, Embase and Scopus to gather evidence on the current state of training in gynecologic oncology and to highlight existing evidence on the best methods to teach surgical skills. Drawing from the experiences of other surgical specialties we examined the use of training adjuncts such as cadaveric dissection, animation and 3D models as well as simulation training in surgical skills acquisition. Specifically, we looked at the use of training adjuncts in gynecologic oncology training as well as the evidence behind simulation training modalities such as low fidelity box trainers, virtual and augmented reality simulation in laparoscopic training. Finally, we provided context by looking at how training curriculums varied internationally. Whereas some evidence to the reliability and validity of simulation training exists in other surgical specialties, our literature review did not find such evidence in gynecologic oncology. It is important that well conducted trials are used to ascertain the utility of simulation training modalities before integrating them into training curricula.
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