Comprehensive Summary
This study evaluated the impact of including a knowledge-based AI chatbot into nursing training programs in Egypt and Saudi Arabia. This was tested among 146 nurses with 73 being in Egypt and 73 being in Saudi Arabia. A quasi-experimental design was conducted and a pre and post intervention assessment was given to the nurses who participated in the 2 week training program integrated with the AI chatbot. The chatbot provided interactive and evidence-based content on nursing protocols to allow the nurses to do self-paced learning through the program. The study showed that there was a significant improvement in the knowledge, confidence, and attitude that nurses had about AI being used in a clinical setting. They also provided satisfaction and acceptance rate among these nurses that exceeded 85%. The author ends by discussing how integrating AI chatbots into nursing education and training can improve memory retention, increase digital literacy, and continue to promote a positive attitude about technology innovation in clinical settings.
Outcomes and Implications
This research demonstrates the potential of reinforcement-learning algorithms to support complex, data-driven care-management decisions for patients with diverse medical and social needs. Clinically, the SARSA-guided model shows that AI can recommend safe, equitable, and personalized interventions that reduce acute-care events. However, human oversight remains essential to monitor performance, adapt recommendations over time, and prevent unintended harm. Together, AI and clinician judgment may provide a powerful framework for improving individualized treatment planning and patient outcomes.