Document Type
Abstract
Publication Date
1-2021
Abstract
Introduction: Although medical schools are implementing programs to promote student scholarship, few programs exist to informally promote inter-student collaboration. Considering many medical students are early in the process of deciding what they want to spend their lives pursuing, and high levels of social connection and engagement may reduce burnout, we sought to evaluate medical students’ attitudes about inter-student collaboration.
Methods: Approximately 1000 medical students in all classes at Sidney Kimmel Medical College (SKMC) were invited to complete a questionnaire. Data collection remains active. Survey questions included a rank order choice on how respondents would use a tool to learn about their classmates and a Likert scale measuring respondents’ attitudes about collaboration. We secondarily investigated the number of SKMC students for whom the responding student was aware of their background.
Results: 166 students have responded to the survey; 24% were first year students, 32% were second year students, 23% were third year students, and 21% were fourth year students. 77.1% of respondents agreed that they had experience they would share with classmates if the opportunity was available and 78.8% agreed that they would engage a classmate who had knowledge in a topic the respondent wanted to explore. Students ranked “Hobbies” and “Community involvement” as the areas they most wanted to learn about their classmates. On average, respondents were aware of the backgrounds of 10 students in their class (IQR = 3.5 - 20) and 2 in other classes (IQR = 0 - 5).
Discussion: Our results suggest that medical students at SKMC only know a small proportion of other students at SKMC. Students are eager to share their backgrounds and reach out to their peers to learn more about their hobbies and community involvement. Knowledge gained by this study will help us develop a tool that augments student connectivity in medical school.
Recommended Citation
Zeiger, Andrew; Gulick, Victoria; and Naik, Tejal U., "Impact of Algorithmic Bias on Hospital Risk Stratification Scores Among Insurance Recipients" (2021). Phase 1. Paper 10.
https://jdc.jefferson.edu/si_dh_2023_phase1/10
Language
English
