Evidence map›Paper›PMID 41822936›Full record

ArticleFrontiers in public health2026

Fall risk, fall awareness, and social support among 825 community-dwelling older adults with functional limitations: a cross-sectional study.

Li Xiao, Rong Hu, Xiaocui Zou, Hong Wu

Abstract read
In one paragraph

Article in Frontiers in public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. 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

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

4 authors.

Li XiaoSichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China.
Rong HuSichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China.
Xiaocui ZouSichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China.
Hong WuSichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: This study aimed to examine the level of fall risk and its associations with fall awareness and social support among community-dwelling older adults with functional limitations. Methods: A cross-sectional study was conducted from January to October 2025. Using cluster sampling, 825 older adults with functional limitations were recruited from four communities in Chengdu, China. Fall risk was assessed using the Modified Falls Risk for Older People in the Community Assessment (MFROP-com), fall awareness was measured with the Self-awareness of Falls in Elderly Scale (SAFE), and social support was evaluated via the Social Support Rating Scale (SSRS). Data were analyzed using Pearson correlation and multiple linear regression. Results: Participants exhibited a high fall risk (mean score 26.51 ± 10.95). The regression model explained a significant proportion of variance in fall risk (Adjusted Conclusion: Fall awareness and social support were identified as key modifiable factors associated with reduced fall risk among community-dwelling older adults with functional limitations. Fall prevention programs should focus on enhancing risk perception and strengthening social support networks for this population.

Indexed as

Accidental FallsAwarenessIndependent LivingSocial SupportAgedAged, 80 and overAging in PlaceChinaCross-Sectional StudiesFemaleGeriatric AssessmentHumansMaleRisk AssessmentRisk Factorscommunity-dwelling older adults with functional limitationscross-sectional studyfall riskself- awarenesssocial support

Identifiers

PMID41822936
PMCPMC12975942

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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.