Evidence map›Paper›PMID 40913487›Full record

ArticleNursing open2025

Assessment of Fall Risk in Community-Dwelling Older Adults Using the Stopping Elderly Accidents, Deaths, and Injuries Algorithm.

Kyeongra Yang, Anita Van Wingerden, Marta Galagoza, Karla Soldevilla, Ethan A Lim, Mary L Wagner

Abstract read
In one paragraph

Article in Nursing open, 2025. 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

6 authors.

Kyeongra YangEntry to Baccalaureate Practice Division, Rutgers University, School of Nursing, Newark, New Jersey, USA.ORCID https://orcid.org/0000-0001-8333-912X
Anita Van WingerdenDepartment of Rehabilitation & Movement Sciences, Rutgers University, School of Health Professions, Newark, New Jersey, USA.
Marta GalagozaDepartment of Pharmacy Practice and Administration, Rutgers University, Ernest Mario School of Pharmacy, New Brunswick, New Jersey, USA.
Karla SoldevillaEntry to Baccalaureate Practice Division, Rutgers University, School of Nursing, Newark, New Jersey, USA.
Ethan A LimDepartment of Pharmacy Practice and Administration, Rutgers University, Ernest Mario School of Pharmacy, New Brunswick, New Jersey, USA.ORCID https://orcid.org/0009-0008-4195-3154
Mary L WagnerDepartment of Pharmacy Practice and Administration, Rutgers University, Ernest Mario School of Pharmacy, New Brunswick, New Jersey, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimTo identify individuals at risk of falls and the factors contributing to their risk, we screened community-dwelling older adults using the Centers for Disease Control and Prevention's Stopping Elderly Accidents, Deaths, and Injuries (STEADI) Assessments.

designA descriptive correlational study design.

methodsFall risk screenings with community-dwelling older adults aged 65 or older were conducted during a virtual interprofessional education event (IPE) for fall risk screening. The screening included demographic questions, perception of fall risks, medication questions and physical assessments (Timed Up and Go test, Single Leg test, 30-Second Sit to Stand) using the STEADI algorithm. Screening data were collected via Qualtrics, and descriptive data analyses were performed using SPSS.

resultsIn total, 114 community volunteers aged 65 or older were screened for fall risk. Using the STEADI Fall Risk questionnaire, 84 participants (73.7%) exhibited at least one clinically proven risk factor for falls, with 39 (34.2%) having four or more risk factors. The physical assessments identified 37 participants (32.5%) with functional leg weakness, 47 (41.2%) had poor mobility and 32 (28.1%) had poor balance. As a result, the modified STEADI algorithm identified 68 (59.6%) with fall risk and the most frequently discussed SMART objectives were related to physical assessment data issues (34.5%). PATIENT OR PUBLIC CONTRIBUTION: Our study confirmed the effectiveness of a multifaceted STEADI assessment in identifying community individuals at risk for falls who may not be detected through the normal standard of care. Educating nurses on performing comprehensive fall risk assessments and creating corresponding action plans with SMART objectives is essential to ensure thorough screening and care of their patients. A collaborative, interprofessional education programme can help train health professional students to gain valuable skills in conducting comprehensive fall risk screenings and developing objectives for future care plans based on those findings.

Indexed as

Accidental FallsAlgorithmsGeriatric AssessmentIndependent LivingAgedAged, 80 and overFemaleHumansMaleRisk AssessmentRisk FactorsSurveys and Questionnaires

Identifiers

PMID40913487
PMCPMC12413634

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.