Evidence map›Paper›PMID 39141916›Full record

ArticleAsian/Pacific Island nursing journal2024

Demand Forecasting of Nurse Talents in China Based on the Gray GM (1,1) Model: Model Development Study.

XiuLi Wu, Aimei Kang

Abstract read
In one paragraph

Article in Asian/Pacific Island nursing journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

XiuLi Wu *Hubei Province Key Laboratory of Occupational Hazard Identification and Control, Institute of Nursing Research, School of Medicine, Wuhan University of Science and Technology, Wuhan Hubei, China.ORCID https://orcid.org/0009-0005-2038-2864
Aimei Kang *Department of Nursing, Wuhan Asia General Hospital Affiliated to Wuhan University of Science and Technology, WuHan, China.ORCID https://orcid.org/0009-0007-3723-0845

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn a global context, the shortage of nursing personnel has emerged as a significant challenge, particularly in countries such as China experiencing population aging. The inadequacy of nursing human resources has become one of the primary threats affecting the quality of health services available to Chinese residents. Therefore, forecasting the demand for nursing personnel has become an important issue.

objectiveThis study presents a Gray GM (1,1) forecasting model for predicting the future 10-year demand for nursing workforce and the number of specialized geriatric nurses, aiming to provide a scientific basis for the development of policies in health care institutions in China.

methodsBased on data from the China Statistical Yearbook 2022, the Gray GM (1,1) model was used to predict the demand for nursing jobs and geriatric nurses over the next 10 years (2024-2033).

resultsThe results indicate that from 2024 to 2033, amidst a continuous growth in the overall population and an increasingly pronounced trend of population aging, the demand for nursing workforce in China, especially for specialized geriatric nurses, is projected to steadily increase.

conclusionsThe paper provides a reference basis for the establishment of China's health care workforce system and the involvement of government departments in health care workforce planning.

Indexed as

forecastingGray GM (1,1) modelnursingnursing human resourcenursing manpower

Identifiers

PMID39141916
PMCPMC11358653

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.