Abstract
BACKGROUND: With the change of human disease spectrum and the increase of public emergencies, the public’s demand for health services and health is gradually increasing and higher expectations are placed on public health personnel. OBJECTIVE: Research needs to establish a comprehensive system of evaluation indices for accurate assessment of the core competencies of public health personnel, to enhance their core competitiveness, and introduce novel approaches to evaluate talent development in the field of public health. METHODS: The study is based on the CIPP (Context Input Process Product) model and uses literature analysis, semi-structured interviews, and Delphi methods to construct an evaluation index system for the core competitiveness of public health talent cultivation. The entropy method is used to determine the weight of the model evaluation index. Finally, the improved Artistic Be Colony algorithm (ABC) is used to optimize the BP network, and apply it to evaluate the core competitiveness of public health talent cultivation. RESULTS: The improved BP network achieved the target accuracy within 11 iterations, with the optimal value observed after 16 iterations, producing an MSE (Mean Square Error) value of 10–13. The evaluation of the index system reported a 97% accuracy, and upon application to the university’s public health training programme, nearly 50% of students and teachers achieved core competitiveness quality scores above 90. CONCLUSIONS: The aforementioned method suggests that it can proficiently assess the fundamental competitiveness of training for public health personnel and offer guidance for future development in the domain of public health.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.