Evidence map›Paper›PMID 35251565›Full record

ArticleJournal of healthcare engineering2022

Construction of a Physical and Medical Care Integrated Model for the Elderly in the Community Based on Artificial Intelligence and Machine Learning.

Zongyou Yang, Siyong Xia, Sheng Feng

RetractedOpen access · hybridAbstract readRetracted Publication
In one paragraph

Article in Journal of healthcare engineering, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.8field-weighted citation impact, top 30% of its field
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

3 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Promoting the Integration of Elderly Healthcare and Elderly Nursing: Evidence from the Chinese Government.International journal of environmental research and public health · 2022
    Article
  3. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors at 3 institutions in 1 country.

Zongyou YangDepartment of Physical Education, Chongqing Jiaotong University, Nanan, 400074 Chongqing, China.
Siyong XiaDepartment of Physical Education, Chongqing Jiaotong University, Nanan, 400074 Chongqing, China.
Sheng FengPhysical Education Department of Chongqing Medical and Pharmaceutical College, 401331 Chongqing, China.ORCID 0000-0003-3924-6924
Chongqing Jiaotong University · CNChongqing Medical and Pharmaceutical College · CNSouthwest University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the increasingly serious population aging, economic system transformation, and social transformation, the elderly have an increasingly strong demand for the elderly care service industry, but the development of China's elderly care service industry started late, and there are still many problems. For how to build a better elderly care service model, under the current situation of shortage of elderly care resources, community elderly care may become a solution. By analyzing the status quo, existing problems and development trends of home-based care services in Hangzhou's community, and learning from foreign experience, it explores the establishment of a "integrated physical, medical, and nursing care" community health management model for the elderly and provides a perfect solution for the development of Hangzhou's community elderly care services countermeasures and suggestions for mode operation. Based on the evaluation, problem analysis, and empirical research on the current situation of home care services in Hangzhou communities, this paper draws on relatively mature community care practices, proposes to build a community elderly health management model that combines medical care and care, and improves and innovates the overall design and medical care of the elderly service model measures for the health management of the elderly in the integrated community. The experimental results of this study show that, according to the demand for elderly care services, elderly people in need of care account for 86.6%, 79.5%, and 68.4% of the elderly population, especially in the areas of medical care, life care, and housekeeping services.

Indexed as

Artificial IntelligenceHome Care ServicesAgedAgingCommunity Health ServicesHumansMachine Learning

Identifiers

PMID35251565
PMCPMC8896920
OpenAlexW4214564327

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.