Suppr超能文献

一次一个 Twitter 民意调查,解决酸碱失衡问题。

Tackling acid-base disorders, one Twitter poll at a time.

机构信息

Division of Nephrology, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, New York.

Division of Nephrology, Department of Medicine, Duke University School of Medicine and Renal Section, Durham Veterans Affairs Health Care System, Durham, North Carolina.

出版信息

Adv Physiol Educ. 2020 Dec 1;44(4):706-708. doi: 10.1152/advan.00099.2020.

Abstract

Understanding and interpretation of acid-base disorders is an important clinical skill that is applicable to the majority of physicians. Although this topic is taught early in medical school, acid-base disturbances have been described as challenging by postgraduate trainees. We describe the use of Twitter, an online microblogging platform, to augment education in acid-base disturbances by using polls in which the user is shown laboratory values and then asked to select the most likely etiology of the disorder. The answer and a brief explanation are then shared in a subsequent tweet. Both polling questions and answers are shared from the account for the online, mobile-optimized, nephrology teaching tool NephSIM (https://www.nephsim.com/). An anonymous survey was administered to assess attitudes toward these polls. Using Twitter as an approach to enhance teaching of acid-base disturbances was both feasible and an engaging way to teach a challenging topic for trainees and physicians. Moreover, the coronavirus disease 2019 (COVID-19) pandemic has demonstrated the importance of incorporating virtual learning opportunities in all levels of medical education.

摘要

理解和解释酸碱失衡是一项重要的临床技能,适用于大多数医生。尽管这个主题在医学院早期就有教授,但酸碱紊乱被研究生培训生描述为具有挑战性。我们描述了使用 Twitter(一个在线微博平台)来增强酸碱紊乱教育的方法,通过在其中进行民意测验,向用户展示实验室值,然后要求他们选择最可能的紊乱病因。答案和简要解释随后会在后续的推文中分享。投票问题和答案都来自在线、移动优化的肾脏病教学工具 NephSIM(https://www.nephsim.com/)的账户。我们进行了一项匿名调查,以评估对这些民意测验的态度。使用 Twitter 作为一种方法来加强酸碱紊乱的教学,对于培训生和医生来说,这是一种可行且引人入胜的方式,可以教授一个具有挑战性的主题。此外,2019 冠状病毒病(COVID-19)大流行表明,在医学教育的各个层面纳入虚拟学习机会非常重要。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验