Evidence map›Paper›PMID 30072360›Full record

ArticleJMIR research protocols2018

Multifactorial Screening Tool for Determining Fall Risk in Community-Dwelling Adults Aged 50 Years or Over (FallSensing): Protocol for a Prospective Study.

Anabela Correia Martins, Juliana Moreira, Catarina Silva, Joana Silva, Cláudia Tonelo, Daniela Baltazar, Clara Rocha, Telmo Pereira, Inês Sousa

Open access · goldAbstract read
In one paragraph

Article in JMIR research protocols, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
8.4field-weighted citation impact, top 3% 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

12 citing papers in PubMed, 1 synthesis or guideline pooled it, 30 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

9 authors at 3 institutions in 1 country.

Anabela Correia MartinsPhysiotherapy Department, Coimbra Health School, Polytechnic Institute of Coimbra, Coimbra, Portugal.ORCID http://orcid.org/0000-0002-2696-2086
Juliana MoreiraPhysiotherapy Department, Coimbra Health School, Polytechnic Institute of Coimbra, Coimbra, Portugal.ORCID http://orcid.org/0000-0003-0123-4960
Catarina SilvaPhysiotherapy Department, Coimbra Health School, Polytechnic Institute of Coimbra, Coimbra, Portugal.ORCID http://orcid.org/0000-0002-5710-9918
Joana SilvaFraunhofer Portugal AICOS, Porto, Portugal.ORCID http://orcid.org/0000-0002-6214-5868
Cláudia ToneloSensing Future Technologies, Coimbra, Portugal.ORCID http://orcid.org/0000-0001-5620-6321
Daniela BaltazarPhysiotherapy Department, Coimbra Health School, Polytechnic Institute of Coimbra, Coimbra, Portugal.ORCID http://orcid.org/0000-0003-3029-4831
Clara RochaComplementary Sciences Department, Coimbra Health School, Polytechnic Institute of Coimbra, Coimbra, Portugal.ORCID http://orcid.org/0000-0002-4724-1843
Telmo PereiraClinical Physiology Department, Coimbra Health School, Polytechnic Institute of Coimbra, Coimbra, Portugal.ORCID http://orcid.org/0000-0001-9119-7774
Inês SousaFraunhofer Portugal AICOS, Porto, Portugal.ORCID http://orcid.org/0000-0002-8488-256X
Polytechnic Institute of Coimbra · PTFraunhofer Portugal Research · PTIntelligent Sensing Anywhere (Portugal) · PT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundFalls are a major health problem among older adults. The risk of falling can be increased by polypharmacy, vision impairment, high blood pressure, environmental home hazards, fear of falling, and changes in the function of musculoskeletal and sensory systems that are associated with aging. Moreover, individuals who experienced previous falls are at higher risk. Nevertheless, falls can be prevented by screening for known risk factors.

objectiveThe objective of our study was to develop a multifactorial, instrumented, screening tool for fall risk, according to the key risk factors for falls, among Portuguese community-dwelling adults aged 50 years or over and to prospectively validate a risk prediction model for the risk of falling.

methodsThis prospective study, following a convenience sample method, will recruit community-dwelling adults aged 50 years or over, who stand and walk independently with or without walking aids in parish councils, physical therapy clinics, senior's universities, and other facilities in different regions of continental Portugal. The FallSensing screening tool is a technological solution for fall risk screening that includes software, a pressure platform, and 2 inertial sensors. The screening includes questions about demographic and anthropometric data, health and lifestyle behaviors, a detailed explanation about procedures to accomplish 6 functional tests (grip strength, Timed Up and Go, 30 seconds sit to stand, step test, 4-Stage Balance test "modified," and 10-meter walking speed), 3 questionnaires concerning environmental home hazards, and an activity and participation profile related to mobility and self-efficacy for exercise.

resultsThe enrollment began in June 2016 and we anticipate study completion by the end of 2018.

conclusionsThe FallSensing screening tool is a multifactorial and evidence-based assessment which identifies factors that contribute to fall risk. Establishing a risk prediction model will allow preventive strategies to be implemented, potentially decreasing fall rate. REGISTERED REPORT IDENTIFIER: RR1-10.2196/10304.

Indexed as

accidental fallsadultsclinical protocolinertial sensorspressure platformprimary prevention

Identifiers

PMID30072360
PMCPMC6096167
OpenAlexW2800473442

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.