Research on the prediction mechanism of working ability of elderly nursing staff based on neural network: Perspective of professionalization

Corresponding author: Hu Hongwei, whuhhw@126.com

DOI: 10.12201/bmr.202104.00022

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  Abstract: Objective: To explore the influencing factors and prediction mechanism of the working ability for elderly nursing staff in China under the perspective of professional development. Methods: 1212 effective sample data were obtained from 27 cities in 22 provinces in China by questionnaire survey. Based on the multi-layer perceptual neural network model, the prediction mechanism of working ability of elderly nursing staff in China was constructed. Results: The convergence effect of the multi-layer perceptual neural network prediction model was good, and the prediction accuracy of the characteristic elements in the professional perspective was high, the working ability of elderly nursing staff is mainly at middle level from the perspective of professionalization. Conclusion and suggestions: In order to improve the working ability of elderly nursing staff and promote the professional development of elderly care service industry, it is suggested to effectively use the neural network model, improve the talent evaluation system, adopt different management methods for the elderly nurses at different working ability levels, and build a professional monitoring system for working ability of the elderly nursing staff.

  Key words: professionalization, elderly nursing, neural network model, work ability

  Submit time: 29 November 2021

  Copyright: The copyright holder for this preprint is the author/funder, who has granted biomedRxiv a license to display the preprint in perpetuity.
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