Transition from Nurses to Medicalized Elderly Caregivers: Comparison on Willingness between Traditional and Modern Regions in China

Int J Environ Res Public Health. 2022 May 13;19(10):5950. doi: 10.3390/ijerph19105950.

Abstract

As China is transitioning to an aging society, the Chinese government has proposed an eldercare pattern, called medicalized elderly care, to help solve the rapid aging and health care problems together. However, the shortage of elderly caregivers is a critical issue, with deficiency both in quantity and quality. This study aims to survey nurses' willingness to transition into medicalized elderly caregivers and compare it between modern and traditional regions. Nurses working in Guangdong (modern region) and Jilin (traditional region) were investigated using a self-administered questionnaire in October 2021. We analyzed the influencing factors through χ²-test, t-test a and binary logistic regression model and further explored the influence of region using propensity score matching (PSM). A total of 1227 nurses were included, with 726 (59.2%) of them showing willingness to transition. Nurses from traditional regions showed a significantly higher willingness to transition after PSM (p = 0.027). Other factors influencing nurses' willingness were age, education, lived with older adults, participated in voluntary activities related to older adults, visited eldercare institutions, attitudes toward older adults, knowledge about older adults, hospice care attitudes and death attitudes. The willingness of nurses to transition was not high enough. To have more willing and skillful human resources for eldercare, we need a more "intimate society for older adults" in the first place.

Keywords: China; influencing factors; medicalized elder caregivers; nurses; transition willingness.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Caregivers*
  • China
  • Cross-Sectional Studies
  • Hospice Care*
  • Humans
  • Surveys and Questionnaires

Grants and funding

This study was funded by the General Program of the National Natural Science Foundation of China (72174207).