Evidence map›Paper›PMID 38711832›Full record

ArticleFrontiers in rehabilitation sciences2024

Application of the international classification of functioning, disability, and health to disability assessment for older people in China.

Yuanping Zhao, Hong Xie, Kun Wang, Shouguo Liu, Juan Yan, Jianan Li

Abstract read
In one paragraph

Article in Frontiers in rehabilitation sciences, 2024. 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

6 authors.

Yuanping ZhaoDepartment of Educational Administration, Rizhao Health School, Rizhao, China.
Hong XieSchool of Nursing, Peking University, Beijing, China.
Kun WangDepartment of Surgery, People's Hospital of Rizhao, Rizhao, China.
Shouguo LiuDepartment of Rehabilitation Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Juan YanChina Association of Social Security, Beijing, China.
Jianan LiDepartment of Rehabilitation Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: In the previous research, the Disability Assessment Scale based on ICF had been constructed for LTC insurance in China. To apply this scale in further studies, it is essential to establish assessment standards for disability levels. Objective: To establish standardized disability classification criteria and identify the disability statuses and levels in older people. Methods: This is a cross-sectional study, in which 1,610 older individuals in 15 long-term care institutions in China were assessed by the disability assessment scale based on ICF. Cluster analysis was used for classification of the disability levels. Mean (SD) and median (IQR) were used to describe the scores for each item and each dimension. Results: The total scores of the disability assessment scale were classified into six disability levels. The overall disability level of the 1,610 participants was moderate-to-severe. The disability in the dimension of "self-care ability and activity" was the most obvious and severe. Conclusion: The Disability Assessment Scale is capable of identifying disability statuses and levels of older people, and it can serve as a valuable tool for investigating the disabilities among old people and for conducting cross-national comparisons of disability levels.

Indexed as

classificationdisability and healthdisability assessment tooldisability levelinternational classification of functioninglong-term care

Identifiers

PMID38711832
PMCPMC11072710

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.