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

•  

  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.
• html

• 图表

• duxuejie, gehui. Study on the design of prediction and early warning model of hand, foot and mouth disease based on BP neural network.. 2021. doi: 10.12201/bmr.202102.00002

  HU Haiyang, ZHAO Congpu, Ma Lian, JIANG Huizhen, ZHANG Jing, ZHU Weiguo. Attention Mechanism And Dilated Convolution Neural Networks for Named Entity Recognition. 2021. doi: 10.12201/bmr.202102.00004

  WANG Xiaoxiao, GUO Qing, LIU Xingong, CHEN Yating, BIAN Sensen, SI Jianping, REN Jian-ping. Research on Public-Private Parthnership Model of Community Medical-Nursing Integration Service Based on Grounded Theory. 2021. doi: 10.12201/bmr.202010.00844

  Deng Lan, Xu Jin, Du Tongzhou, Huang Lihong, Yin Shiyu. An Intelligent Nursing Scheduling Management System Based on Answer Set Programming. 2021. doi: 10.12201/bmr.202107.00020

  Cui Bei, wanglei. Analysis of influencing factors of Chinas biomedical innovation ability based on ISM. 2022. doi: 10.12201/bmr.202111.00015

  YU YaHang, KONG Chen, YUAN Beibei. A systematic review of the influence of the integrated reform of medical and health service system on the working motivation and behavior of medical workers. 2021. doi: 10.12201/bmr.202011.00017

  houyanjie, wangyu, yanshiyuan, zhangwenjing, zhanglin, yaojun. Effects of Long-term Care Insurance on Medical Service Utilization, Medical Burden and Health of Middle-aged and Elderly People：An empirical research based on DID. 2021. doi: 10.12201/bmr.202107.00029

  Hong Yankun, Zouli. Research on the development of information technology ability of medical teachers in the Internet plus era. 2021. doi: 10.12201/bmr.202106.00009

  GAO Yang, GAO Wen-yue. Research on the cultivation strategy of network information security literacy of medical students from the perspective of big data. 2020. doi: 10.12201/bmr.202004.00030

  liuyan. Construction and Application of Knowledge Base of Intelligent Clinical Nursing Quality Inspection System. 2021. doi: 10.12201/bmr.202012.00011

• ID	Submit time	Number	Download
  1	2021-04-26	bmr.202104.00022V1	Download

• Public  Anonymous  To author only Submit Comments