Use of AI for Nurse Practitioner Students to Practice Conversations With Vaccine-Hesitant Patients and Caregivers
As vaccine hesitancy continues to pose a significant public health challenge, nurse practitioners (NPs) should be equipped with the skills to engage in informed, empathetic conversations with patients. Artificial intelligence (AI)-driven simulation offers a promising pedagogical tool to prepare future NPs for these complex discussions. AI-driven simulations promote real-time feedback and learner engagement while providing a space for developing language around a potentially difficult conversation.1 These innovative approaches not only enhance clinical reasoning but also support the development of trust-based patient interactions, essential for promoting vaccine acceptance in diverse populations. By integrating virtual simulations and evolving AI patient scenarios into nursing curricula, educators can foster critical thinking, communication, and cultural competence in their students. Strengthening these skills better prepares students to help overcome this public health challenge. Overview Students enrolled in a pediatric NP primary care Master of Science in Nursing program at a private university in the southeastern United States received content on improving vaccine confidence as part of their coursework. As a required assignment for this course, students participated in 2 AI-driven vaccine hesitancy simulations, BodySwaps (https://bodyswaps.co), and Re:course AI (https://recourseai.com), to practice navigating difficult conversations with patients and caregivers. This article describes the strategy and student feedback about this experience, which builds on prior evaluation of using Re:course AI alone in a similar learner population.2 Students participated in a 2-hour interactive lecture on increasing vaccine confidence in pediatrics in which they learned about the concept of vaccine hesitancy, common vaccine myths, and communication skills for having conversations with vaccine-hesitant patients and caregivers in the clinical setting. The students participated in a small group activity where they practiced having conversations using the American Academy of Pediatrics’ framework for improving vaccine communication and uptake. Following the lecture and group activity, they had an in-person 20-minute pre-brief session led by 2 pediatric primary care faculty to discuss the simulation, objectives, and logistics before completing the simulations after class. The prebrief session provided instructions on how to access and complete the simulations. Both simulations are structured as routine outpatient visits. Learners initiate the encounter with an introduction, and the avatars respond with concerns and questions. The student provides education and practices communication and shared decision-making. BodySwaps is an immersive learning program using AI to develop soft skills among health care professionals. It is compatible with virtual reality headsets and PC, as well as iOS and Android mobile devices. Virtual reality headsets were not used as part of this simulation. The simulation completed on BodySwaps was Increasing Immunization Confidence. It was developed in collaboration with the American Academy of Pediatrics and included a vaccine-hesitant caregiver with concerns about administering the measles vaccine to their child. Students conversed with the avatar in segments while being given guidance and feedback by the AI program throughout the conversation.3 Re:course AI is a platform for health and life sciences to enhance conversational skills using generative AI sessions. The simulation completed with Re:course AI was a caregiver and an 11-year-old girl expressing hesitancy about the human papillomavirus vaccine. Students were scored and given feedback by the program at the end of their simulation.4 The 2 simulations were completed on students’ personal devices and outside of class time in their location of choice. Some students completed them on campus and some off campus. To help mitigate technical difficulties, it was recommended that they use either Google Chrome or Microsoft Edge browsers for the simulation. To reduce distractions and maximize their experience, students were asked to use reliable internet with good connectivity, plug their device into a power source, and close all other tabs on their devices during the simulation. Instructions stated for the BodySwaps simulation to be completed first, followed by the Re:course AI simulation. The BodySwaps simulation provided an opportunity to practice the skills individually that are needed in the Re:course AI simulation. The day following the simulations, students engaged in a 30-minute debrief session where they reviewed their experience in the classroom setting. The debrief included reflection on their experience with both the individual platforms and their overall experience. Following the debrief, students were given 2 optional surveys to complete to capture their perception of the experience. The surveys were anonymous and part of course quality improvement measures and had no impact on their grade. The first survey, the Simulation Effectiveness Tool—Modified (SET-M), was used to assess the global outcomes of learning from both activities. The SET-M is a standardized 19-question assessment used to gauge a participant’s perception of how effective an experiential learning exercise was to their personal development, with questions about the prebrief, debrief, and simulation itself. The tool was altered to a 5-point scale with the author’s permission, ranging from 1 (strongly disagree) to 5 (strongly agree).5 A second survey, created by the course faculty, was used to assess the quality of each software. This 25-question survey asked about each platform’s realism, ease of use, and how AI benefited students’ learning in both experiences. Both surveys were administered via REDCap. Exempt status was granted by the Institutional Review Board to disseminate the results of the surveys. Results Based on the SET-M results, the overall experience of using AI simulations in class was positive. The overall experience received an average of 4.18 on the SET-M (n = 29, 59% response rate). The series of questions with regard to perceived confidence averaged 4.28, indicative of promoting learner confidence in this particular experience. The debrief was the highest scoring section of the survey (M = 4.39), indicative of a positive learning experience for learners after the conclusion of the scenario. The second survey assessed concepts such as realism, ease of use, and usefulness to learning of each software on a 5-point scale. Learners who completed the survey (n = 19, 38% response rate) had a more positive experience with Recourse AI (M = 4.10) than with BodySwaps (M = 3.67). Learners also stated that they would opt for future experiences with AI-embedded simulations (81%). Most learners felt that AI-driven simulation was equally effective for their learning as other modalities, such as task trainers and standardized patients (65%). Learners reported a few limitations. They noted delayed responses and unlimited time to complete the simulation as factors that reduced realism. The inability to read body language was identified as a hindrance to their ability to learn. Conclusion NPs are critical partners with families and children as they make informed health care decisions on vaccines. As families consider vaccines, NPs must be skilled in engaging in open, trusting conversations that address vaccine concerns and promote the health and well-being of their pediatric patients. NP programs should prioritize the creation of learning opportunities for students to develop competency in essential communication skills related to vaccines. Innovative approaches like AI simulations through companies such as Bodyswaps and Re:Course AI offer valuable learning experiences to practice communication techniques, receive immediate feedback, and build confidence. Student feedback on this approach indicates positive experiences with the AI simulations and could be a valuable addition to nursing education.
Authors
- Jennifer Ridgway (ORCID: https://orcid.org/0000-0002-5546-7156)
- Natasha McClure (ORCID: https://orcid.org/0000-0002-3938-4967)
- Eric Hall
- Brittany Nelson
- Anna Brown (ORCID: https://orcid.org/0000-0003-0380-0903)
Institutions
- Vanderbilt University (US)
Publication Details
- Journal
- Nurse Educator
- Published
- 2026-06-08
- DOI
- https://doi.org/10.1097/nne.0000000000002185
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00