Mixed methods study examines chatbot perception in nursing education, highlighting adoption factors and ethical concerns.
Background: Generative artificial intelligence (AI) chatbots create new opportunities and risks in nursing education; stakeholder perspectives are needed for thoughtful integration. The purpose of this study was to examine factors influencing chatbot adoption among nursing faculty and baccalaureate nursing (BSN) students using the Technology Acceptance Model. Method: A convergent, mixed methods, cross-sectional survey included BSN students and faculty ( N = 254). Quantitative analyses (e.g., t-tests, multiple regression) assessed perceived usefulness (PU), perceived ease of use (PEOU), and behavioral intention (BI). Qualitative open-ended responses underwent direct content analysis. Findings were integrated with joint displays. Results: Participants reported moderately high PU, PEOU, and BI scores. Greater self-rated technology proficiency predicted high PEOU for both groups and high PU for faculty. Qualitative data emphasized efficiency and learning support alongside concerns about accuracy, ethics, and overreliance. Integration showed alignment between subscale scores and themes. Conclusion: Targeted AI literacy and faculty development, paired with ethical guidance, may enhance adoption while safeguarding core nursing values, such as compassion, integrity, human connection, and therapeutic communication.
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Ostick et al. (2026) studied this question.
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