Medical Student Western Michigan University Homer Stryker M.D. School of Medicine Kalamazoo, Michigan, United States
Background: Human papillomavirus (HPV) is the most common sexually transmitted infection worldwide, attributed to approximately 5% of global cancers. Despite low adverse effects, rates for HPV vaccination remain below U.S national goals. The use of standardized patients (SPs), while well-integrated into the continuum of medical education, poses a set of unique challenges in the context of adolescent HPV vaccination, including recruiting adolescents as SPs. Meanwhile, artificial intelligence (AI) has shown increased potential for use in industry and medical education. Objective: We aimed to test the feasibility of AI simulation for developing communication skills around HPV adolescent vaccination in Family Medicine residents. We hypothesize that this format would be acceptable to learners, would improve their communication and shared decision-making skills, and would increase rates of HPV vaccination among eligible patients compared to learners receiving education as usual. Design/Methods: Approved by institutional IRB (#2023-1056), our two-cohort study includes a control group receiving an asynchronous education module on HPV vaccination and an experimental group receiving interactive AI simulation with crossover between the groups 3 months later. A survey (developed by the team and refined by cognitive interview process) would assess utility, ease of use, and satisfaction with the modules and post-modular knowledge, skills and attitudes. Patient vaccination rates would be measured via electronic health record data collected in 3-month increments (pre-intervention, during intervention, and crossover). Module design was guided by the extant literature and feedback from near-peers, while simulation was developed in partnership between clinicians and AI technology experts. Apart from descriptive data, associations between categorical variables will be explored using chi-square tests or Fisher’s Exact test, and differences in vaccination rates using paired t-tests. Data analysis expected to be completed by February 2024.
