Evidence map›Paper›PMID 41248122›Full record

ArticlePloS one2025

Prediction of disability levels and research on nursing economic costs for elderly people in China.

Shiyan Lu, Yongxiu Kuang

Abstract read
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Shiyan LuInfectious diseases Department, Wenshan People's Hospital, Wenshan, Yunnan, China.ORCID https://orcid.org/0009-0003-7113-3185
Yongxiu KuangInfectious diseases Department, Wenshan People's Hospital, Wenshan, Yunnan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aims to solve the problem of the shortage of professional nursing staff and the inability of the quality of nursing services to meet the needs of the elderly. Therefore, a longitudinal research type was adopted for long-term tracking and observation, with a time span from 2017 to 2020. The disability status of the elderly in China was analyzed, and appropriate sample data were selected to construct a comprehensive disability level assessment system. Then, a prediction method for disability scale and level based on the queue element method was proposed. Finally, based on the prediction results, a pension cost optimization strategy was designed, and the current pension methods and economic costs of the elderly were discussed, aiming to providing new ways to solve the deep aging dilemma of Chinese society and families. The results showed that the disability scale prediction method calculated that the growth rate of elderly people from 2025 to 2035 would exceed 65%. Moreover, the prediction error accuracy of elderly people nationwide in 2025 was only -0.03%, and the growth rate of elderly people has reached 69.07%. Compared with mainstream random forests, artificial neural networks, and long short-term memory networks, the research method showed excellent prediction performance, with average absolute error, mean square error, average prediction error, and running time of 0.617576, 0.000053, 0.005007, and 10.24 ms, respectively. The economic cost of nursing for severe disabilities in institutions was nearly 3 times that of mild disabilities and 3.8 times that of home care. The above information shows that the research method can accurately assess the disability level and care needs of the elderly and propose targeted improvement strategies. This method can strengthen the establishment of the nursing service system for disabled elderly people, and build a full chain nursing system including hospitals, elderly care institutions, families, and communities. The study provides strong support for the comprehensive implementation of the long-term care insurance system.

Indexed as

Persons with DisabilitiesAgedAged, 80 and overChinaDisability EvaluationFemaleHumansLongitudinal StudiesMale

Identifiers

PMID41248122
PMCPMC12622809

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.