Evidence map›Paper›PMID 35801251›Full record

ArticleFrontiers in public health2022

Multidimensional Disability Evaluation and Confirmatory Analysis of Older Adults in a Home-Based Community in China.

Ying Han, Liangwen Zhang, Ya Fang

Open access · goldAbstract read
In one paragraph

Article in Frontiers in public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.9field-weighted citation impact, top 15% 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

5 citing papers in PubMed, 14 citations in OpenAlex.

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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

3 authors at 1 institution in 1 country.

Ying HanState Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, China.
Liangwen ZhangState Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, China.
Ya FangState Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, China.
Xiamen University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A robust multi-dimensional disability assessment standard was constructed to consider physical condition, care resources, and social interaction that might lead to disability, to provide a basis for accurate identification of care needs for older people aged 60 and above in a home-based community. Based on the "Capability approach" theory, the Alkire-Foster method was applied to assess the multidimensional disability. This was followed by the confirmatory analysis of the Seemingly Unrelated Regression Estimation. Adjusted Bourguignon and Chakravarty index was also calculated to analyze the sensitivity to further support our conclusions. We constructed a multi-dimensional disability indicator system by combining physical condition, care resources, and social interaction. Findings presented that the impairment of individuals' motor ability, ability to manage disease, cognitive psychology, and communication skills and social interaction contributed to multidimensional disability the most. And older people who are female, aged over 65, with lower BMI, living in rural areas, with a lower education level, getting more formal care, and with relatively higher creatinine, tend to face a higher risk of deprivation in overall multidimensional disability. Therefore, the targeted interventions to improve health literacy, nutrition, skill of disease management, social networks, and communication skills for older people and also timely detection of the abnormal changes in potential biomarker indicators of them is necessary to delay disability and prevent its occurrence.

Indexed as

Health LiteracyPersons with DisabilitiesAgedChinaDisability EvaluationFemaleHumansMaleAlkire and Foster approachdisabilityhome-based careindicator systemSeemingly Unrelated Regression

Identifiers

PMID35801251
PMCPMC9253425
OpenAlexW4283207496

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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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.