Evidence map›Paper›PMID 37796884›Full record

ArticlePloS one2023

Predicting use of a gait-stabilizing device using a Wii Balance Board.

Sean M Mullan, Nicholas J Evans, Daniel K Sewell, Shelby L Francis, Linnea A Polgreen, Alberto M Segre, Philip M Polgreen

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2023. 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
1.5field-weighted citation impact, top 16% 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

0 citing papers in PubMed, 2 citations in OpenAlex.

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

7 authors at 1 institution in 1 country.

Sean M MullanDepartment of Computer Science, University of Iowa, Iowa City, Iowa, United States of America.ORCID 0000-0003-4832-4453
Nicholas J EvansDepartment of Internal Medicine, University of Iowa, Iowa City, Iowa, United States of America.ORCID 0000-0002-5015-7183
Daniel K SewellDepartment of Biostatistics, University of Iowa, Iowa City, Iowa, United States of America.
Shelby L FrancisDepartment of Internal Medicine, University of Iowa, Iowa City, Iowa, United States of America.ORCID 0000-0002-1155-1794
Linnea A PolgreenDepartment of Pharmacy Practice and Science, University of Iowa, Iowa City, Iowa, United States of America.
Alberto M SegreDepartment of Computer Science, University of Iowa, Iowa City, Iowa, United States of America.
Philip M PolgreenDepartment of Internal Medicine, University of Iowa, Iowa City, Iowa, United States of America.
University of Iowa · US

Funding

The University of Iowa Clinical and Translational Science AwardUL1TR002537 · NCATS · UNIVERSITY OF IOWA · PI HANSEN, MARLAN R, WINOKUR, PATRICIA · 2018 to 2022
$20.0M
NCATS NIH HHS UL1 TR002537
6 · The paper itself

Abstract

Gait-stabilizing devices (GSDs) are effective at preventing falls, but people are often reluctant to use them until after experiencing a fall. Inexpensive, convenient, and effective methods for predicting which patients need GSDs could help improve adoption. The purpose of this study was to determine if a Wii Balance Board (WBB) can be used to determine whether or not patients use a GSD. We prospectively recruited participants ages 70-100, some who used GSDs and some who did not. Participants first answered questions from the Modified Vulnerable Elders Survey, and then completed a grip-strength test using a handgrip dynamometer. Finally, they were asked to complete a series of four 30-second balance tests on a WBB in random order: (1) eyes open, feet apart; (2) eyes open, feet together; (3) eyes closed, feet apart; and (4) eyes closed, feet together. The four-test series was repeated a second time in the same random order. The resulting data, represented as 25 features extracted from the questionnaires and the grip test, and data from the eight balance tests, were used to predict a subject's GSD use using generalized functional linear models based on the Bernoulli distribution. 268 participants were consented; 62 were missing data elements and were removed from analysis; 109 were not GSD users and 97 were GSD users. The use of velocity and acceleration information from the WBB improved upon predictions based solely on grip strength, demographic, and survey variables. The WBB is a convenient, inexpensive, and easy-to-use device that can be used to recommend whether or not patients should be using a GSD.

Indexed as

Hand StrengthVideo GamesAgedAged, 80 and overGaitHumansPostural BalanceReproducibility of Results

Identifiers

PMID37796884
PMCPMC10553233
OpenAlexW4387362967

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.