A Cross-Sectional Survey on Medical Learning Applications Used by Undergraduate Medical Students in Cluj-Napoca
Keywords:
Medical Learning Application (MLA), Learning resources, Undergraduate, Educational technologies, Problem-Based LearningAbstract
Introduction: This study explores the utility of and attitude towards medical learning applications (MLAs) among undergraduate students of medicine in Cluj-Napoca and the use of these apps in finding solutions to five case-based medical scenarios. Materials and methods: A cross-sectional design using an online survey was conducted between June 8th and July 19th, 2019. The English/Romanian students were personally invited to participate in the survey via social media platforms (Facebook/WhatsApp student groups). A three-section questionnaire was developed to anonymously collect demographic data, study habits and the answers to the five case-based medical scenarios. Results: Ninety-three students between the age of 19 and 50 (median 24 years) participated. Most of the responding students (81.7%) were in the clinical years of study and studied up to 3 hours per day (67.7%). The use of MLAs ≥2 hours per day is reported by 18.3% of respondents. The MLAs were mainly used for studying throughout the semester (69.1%); 30.9% of the students used MLAs only for their exam preparation. The top-three MLAs were ‘AMBOSS’ (30/93), ‘Medscape’ (9/93) and ‘Dr. Najeeb Lectures’ (6/93). In around half of the cases, the students paid for the MLA (46.4%). The maximum obtainable score (6 points) in the clinical cases was reached only by 3 students without significant differences between the scores of those students who used or did not use resources (MLAs, books, other) to find the case solutions (Mann-Whitney test P=0.594, median of correct answers = 3 for both groups) or between the scores of those who used or did not use MLAs for learning (P=0.594, median of correct answers = 3 for both groups). Conclusion: One third of the participating students used MLAs but this is not reflected in the number of correctly answered clinical cases.
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