Assessing the novel finding information framework mobile application in a medical education setting
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INTRODUCTION: Recently, the faculty from the Department of Family Medicine in conjunction with the Vertical Integration Group at Boston University School of Medicine (BUSM) developed the Finding Information Framework or FIF to assist medical students in building skills utilizing Evidence Based Medicine (EBM). The FIF is an educational algorithm that guides students on how to ask a clinical question and then assists them in finding the most appropriate online resource. This past year, together with the Division of Graduate Medical Sciences and the Alumni Medical Library, the FIF tool was developed into an EBM mobile application (app) to help the students transition from their second to third year of medical school, where they transition from a more didactic to clinical curriculum. This current study aims to assess the aesthetics as well as functionalities of the FIF mobile app by surveying current medical students. METHODS: The author presented initial outlines of the survey to the research team following a review of relevant studies. From this, the final survey was created and submitted for Boston University (BU) Institutional Review Board Approval (IRB) for a study on human subjects. A recruitment email, requesting volunteers to participate in the survey study, was sent to the third and fourth year medical students. RESULTS: Data were categorized into four sections: (1) preliminary questions, (2) app-specific questions, (3) clinical questions, and (4) open-ended questions. Survey results were divided into two parts: part one was with a mixed population and part two was exclusively for third and fourth year medical students. Ease of use and aesthetic appeal generally received higher scores than potential future use of the app. Clinical question responses varied significantly. DISCUSSION: The survey assessing the FIF mobile app shed light into potential areas that the research team should address in further improvements to the app. These areas include easier log-in, preferably earlier in the app to assure easier access to databases, and the option to go directly to a specific known resource without requiring movement through the decision tree if desirable. A major limitation of the study was the small sample size. Further studies would help in further validating the results gained in this study.