Browsing by Author "Smith, Sarah"

Now showing 1 - 3 of 3
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    Impact of a USMLE Step 2 Prediction Model on Medical Student Motivations
    (Sage, 2025-02-18) Shanks, Anthony L.; Steckler, Ben; Smith, Sarah; Rusk, Debra; Walvoord, Emily; Dafoe, Erin; Wallach, Paul
    PURPOSE: With the transition of USMLE Step 1 to Pass/Fail, Step 2 CK carries added weight in the residency selection process. Our goal was to develop a Step 2 predicted score to provide to students earlier in medical school to assist with career mentoring. We also sought to understand how the predicted scores affected student’s plans. METHOD: Traditional statistical models and machine learning algorithms to identify predictors of Step 2 CK performance were utilized. Predicted scores were provided to all students in the Class of 2024 at a large allopathic medical school. A cross-sectional survey was conducted to assess if the estimated score in uenced career or study plans. RESULTS: The independent variables that resulted in the most predictive model included CBSE score, Organ System course exam scores and Phase 2 (Third Year Clinical Clerkships) NBME percentile scores (Step2CK= 191.984 + 0.42 (CBSE score) + 0.294 (Organ Systems) + 0.409 (Average NBME). The standard error of the prediction model was 7.6 with better accuracy for predicted scores greater than 230 (SE 8.1) as compared to less than 230 (SE 12.8). Nineteen percent of respondents changed their study plan based on the predicted score result. Themes identified from the predicted score included reassurance for career planning and the creation of anxiety and stress. CONCLUSION: A Step 2 Predicted Score, created from pre-existing metrics, was a good estimator of Step 2 CK performance. Given the timing of Step 2 CK, a predicted score would be a useful tool to counsel students during the specialty and residency selection process.
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    Lift and Shift: The Effect of Fundraising Interventions in Charity Space and Time
    (American Economic Association, 2022) Scharf, Kimberley; Smith, Sarah; Ottoni-Wilhelm, Mark; Economics, School of Liberal Arts
    Fundraising interventions may lift donations and/or shift their composition and timing. Using data rich in both the charity space and time dimensions, we find that major fundraising appeals lift donations to the appeal charity and that this increase is not offset by lower donations later in time. Strikingly, major appeals also forward-shift donations to other (nonappeal) charities that are offset by lower donations later. To understand these response patterns, we introduce a two-period, two-charity "lift-shift" model. The model indicates that the observed response patterns are possible only if warm glow is substitutable, both intertemporally and between charities.
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    Mutational Landscape and Interaction of SARS-CoV-2 with Host Cellular Components
    (MDPI, 2021-09) Srivastava, Mansi; Hall, Dwight; Omoru, Okiemute Beatrice; Gill, Hunter Mathias; Smith, Sarah; Janga, Sarath Chandra; BioHealth Informatics, School of Informatics and Computing
    The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its rapid evolution has led to a global health crisis. Increasing mutations across the SARS-CoV-2 genome have severely impacted the development of effective therapeutics and vaccines to combat the virus. However, the new SARS-CoV-2 variants and their evolutionary characteristics are not fully understood. Host cellular components such as the ACE2 receptor, RNA-binding proteins (RBPs), microRNAs, small nuclear RNA (snRNA), 18s rRNA, and the 7SL RNA component of the signal recognition particle (SRP) interact with various structural and non-structural proteins of the SARS-CoV-2. Several of these viral proteins are currently being examined for designing antiviral therapeutics. In this review, we discuss current advances in our understanding of various host cellular components targeted by the virus during SARS-CoV-2 infection. We also summarize the mutations across the SARS-CoV-2 genome that directs the evolution of new viral strains. Considering coronaviruses are rapidly evolving in humans, this enables them to escape therapeutic therapies and vaccine-induced immunity. In order to understand the virus’s evolution, it is essential to study its mutational patterns and their impact on host cellular machinery. Finally, we present a comprehensive survey of currently available databases and tools to study viral–host interactions that stand as crucial resources for developing novel therapeutic strategies for combating SARS-CoV-2 infection.