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Integration of Game-Based Chatbot With Kahoot! for High-Alert Medication Education for Newly Graduated Nurses: A
Ting-I He1, Shu-Fen Niu1, Chu-Yu Huang2
1Department of Nursing, Shin Kong Wu Ho-Su Memorial Hospital, Taipei City, Taiwan, Republic of China.
Background:
Unsafe medication administration poses significant risks to global health care, and insufficient nurse knowledge of high-alert medications (HAMs) further elevates the likelihood of errors. Integrating a game-based chatbot with Kahoot! may enhance HAM learning outcomes.
Method:
In this two-group, repeated-measures randomized controlled trial, 77 newly graduated nurses were randomized to (1) game-based chatbot + Kahoot! with classroom (n = 42) or (2) Kahoot! with classroom (n = 35). Participants completed HAM knowledge (HAMK) and HAM self-competence (HAMSC) assessments pre-intervention (T0), at training completion (T1), and 1-month post-intervention (T2).
Results:
Demographic characteristics were comparable between the groups, except for work unit. Generalized estimating equation analysis showed no significant group-by-time interaction on HAMK or HAMSC (p > .05), but difference-in-differences analysis revealed superior retention in the experimental group from T1 to T2 (p < .05).
Conclusion:
Both groups improved in HAM knowledge and competence, affirming the value of traditional teaching approaches. It is essential to optimize the chatbot design for enhanced learning outcomes and engagement.
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