Evidence map›Paper›PMID 38487775›Full record

ArticleWearable technologies2023

Evaluation of U.S. Army Soldiers wearing a back exosuit during a field training exercise.

P R Slaughter, K M Rodzak, S J Fine, C C Ice, D N Wolf, K E Zelik

Open access · goldAbstract read
In one paragraph

Article in Wearable technologies, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
13.1field-weighted citation impact, top 1% 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

6 citing papers in PubMed, 17 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

6 authors at 1 institution in 1 country.

P R SlaughterDepartment of Mechanical Engineering, Vanderbilt University, Nashville, Tennessee, United States.ORCID https://orcid.org/0000-0003-1854-1713
K M RodzakDepartment of Mechanical Engineering, Vanderbilt University, Nashville, Tennessee, United States.
S J FineDepartment of Mechanical Engineering, Vanderbilt University, Nashville, Tennessee, United States.
C C IceDepartment of Mechanical Engineering, Vanderbilt University, Nashville, Tennessee, United States.
D N WolfDepartment of Mechanical Engineering, Vanderbilt University, Nashville, Tennessee, United States.
K E ZelikDepartment of Mechanical Engineering, Vanderbilt University, Nashville, Tennessee, United States.
Vanderbilt University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Back overuse injuries are a significant problem in the U.S. Army, responsible for nearly a quarter of musculoskeletal injuries. Back exosuits are wearable devices that relieve musculoskeletal strain, make lifting easier, and could potentially reduce Soldier overuse injuries. But published studies have not evaluated exosuits during realistic field operations to assess acceptability to Soldiers. We tested a back exosuit on field artillery Soldiers during a field training exercise. Afterward, Soldiers completed a survey to quantify their satisfaction, intent to use, and performance impact of the exosuit. Feedback was overwhelmingly positive: Approximately 90% of Soldiers reported that exosuits increased their ability to perform their duties, and 100% said that if the exosuit were further developed and made available to them, they would be likely to wear it. These numerical survey results indicated that exosuits can provide a practical and acceptable way to assist lifting and augment physical performance during realistic Army operations without interfering with other duties.

Indexed as

designexosuitsindustryperformance augmentation

Identifiers

PMID38487775
PMCPMC10936316
OpenAlexW4383562666

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.