A Picture Paints a Thousand Words: Perspectives of the Use of Images and Videos of Physical Findings in Virtual OSCE Teaching Sessions.

Abstract

The COVID-19 pandemic has resulted in medical students' education being disrupted and a new direction of learning towards the online classroom, with students frequently learning to identify clinical signs via online conferencing platforms. Given this shift in student study techniques in the pandemic and post-pandemic era, we set out to analyse the confidence levels of students recognizing clinical signs in patients and the opinions and patterns of resources students would use to build up the knowledge and confidence for their future clinical practice. OSCEazy, a student-led medical education organisation, delivered an online teaching session and disseminated a questionnaire containing ten-point Likert scales, multiple-choice questions and free text options. The majority (over 75%) of respondents reported using digital resources to learn physical examinations. Most respondents were somewhat confident with recognising clinical signs during physical examinations (Median 7, IQR 6-8). Kruskal-Wallis H-test on students' impression of the quality of current OSCE materials showed a statistically significant difference between cohorts (X2(2) = 14.209, p = 0.014). A large proportion of students (98.41%) agreed that an online resources bank would be beneficial for their learning. Wilcoxon rank test showed a statistically significant preference for learning physical examinations using clinical images rather than videos (p = 0.014). A 29% of respondents mentioned the use of physical textbooks as a resource, while online platforms such as OSCE revision websites, YouTube and Google Images had become the mainstream platforms. The findings reported here suggest that there needs to be a greater emphasis on providing online image-based resources to support medical students in learning clinical signs. A resource containing these clinical signs would prove to be of benefit for students to access high-quality self-directed learning to identify and verify clinical signs.