Expectations Versus Reality: Understanding the Accuracy of Impressions Made During Virtual Interviews of Pediatric Pulmonary Fellowship Programs

C34. ADVANCEMENTS IN MEDICAL EDUCATION AND PROFESSIONAL DEVELOPMENT(2022)

引用 0|浏览8
暂无评分
摘要
Rationale As a result of the SARS-CoV-2 pandemic, all pediatric pulmonary fellowship programs conducted virtual interviews for the first time in the Fall of 2020. This study aimed to understand the accuracy of virtual-interview derived-impressions of fellowship programs, as well as applicant preference for future fellowship interview cycles. Methods A group of pediatric pulmonary fellows and Program Directors designed a REDCap survey. The survey was distributed to all first-year pediatric pulmonary fellows who participated in the 2020-2021 virtual interview season. Results 23/52 (44%) of first-year pediatric pulmonary fellows completed the survey. 96% were able to form general impressions about fellowship programs during their virtual interviews. 96% reported that generally their fellowship experience matched their virtual-interview derived-impressions. 17 of the 19 factors applicants use to rank programs had no statistically significant change (p > 0.05) in impression from virtual interview to fellowship experience. The two factors with a statistically significant (p < 0.05) change in impression were patient care related-volume of "bread and butter" pediatric pulmonary patients and volume of tertiary care pediatric pulmonary patients. 87% prefer some form of in-person interview option in future application cycles. A tiered interview format in which applicants are first invited to a virtual interview day followed by an optional in-person second look day was the most popular preference for future interview cycles (48%). Conclusions Virtual interviews may provide accurate representations of pediatric pulmonary fellowship programs and applicants prefer some type of in-person interview option in future application cycles.
更多
查看译文
关键词
COVID-19,education,fellowship,pediatric pulmonary,virtual interview
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要