Evidence map›Paper›PMID 36164429›Full record

ArticleComputational intelligence and neuroscience2022

Mobility and Quality of Life in Chinese Elderly and Geriatric Patients and Biomedical Diagnosis.

Jing Xin, Liyuan Li

RetractedAbstract readRetracted Publication
In one paragraph

Article in Computational intelligence and neuroscience, 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 It has been retracted, and should not be counted.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 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

  • Retraction · 2023-08-09Concerns/Issues about Data · Concerns/Issues about Results and/or Conclusions · Concerns/Issues about Referencing/Attributions · Concerns/Issues about Peer Review · Informed/Patient Consent - None/Withdrawn · Investigation by Journal/Publisher · Investigation by Third Party · Lack of IRB/IACUC Approval and/or Compliance · Paper Mill · Computer-Aided Content or Computer-Generated Content · Unreliable Results and/or Conclusions · · See also: https://pubpeer.com/publications/07A4C13CCC5B890A5CA4D740DB5D82
  • Retracted
5 · Who and what money

Authors and funding

2 authors.

Jing XinSchool of Public Administration, Zhongnan University of Economics and Law, Wuhan 430073, China.ORCID https://orcid.org/0000-0002-7647-9922
Liyuan LiFanling Business School, Nanyang Institute of Technology, Nanyang 473004, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mobilization hugely affects the personal satisfaction of old people. We found that preparing old and geriatric patients expands their personal satisfaction using statistical comparisons of observed groups. As a technique of evaluation, we employed the nonparametric Mann-Whitney test. The Pearson correlation coefficient was employed to determine relationships between variables. In both the BREF questionnaire (item 15) and the ADL test, geriatric individuals had similar mobility rates. Physical activity is a crucial feature of mobility in seniors, according to findings from other studies. In hospitalized geriatric patients, reduced mobility is the most significant impediment. Seniors' confidence in their own talents grew as a result of the favourable overall influence of physical activity. Geriatric patients must be mobilized on a regular basis in nursing, depending on their level of dependency. Physical activity had a positive overall effect on older people's confidence in their own abilities, and this was shown in how they felt about themselves. Nursing staff must constantly move geriatric patients based on how much assistance they require.

Indexed as

Asian PeopleQuality of LifeActivities of Daily LivingAgedChinaHumansSurveys and Questionnaires

Identifiers

PMID36164429
PMCPMC9509261

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.