Evidence map›Paper›PMID 36253602›Full record

ArticleAnnals of biomedical engineering2022

Consensus Head Acceleration Measurement Practices (CHAMP): Study Design and Statistical Analysis.

Steve Rowson, Jason Mihalik, Jillian Urban, Julianne Schmidt, Steve Marshall, Jaroslaw Harezlak, Brian D Stemper, Mike McCrea, Jim Funk

Abstract read
In one paragraph

Article in Annals of biomedical engineering, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 1 pooled it
–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

19 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Observational
  4. Article
  5. Article
  6. Article
  7. Article
  8. Observational
  9. Article
  10. Quantitative video analysis of head acceleration events: a review.Frontiers in bioengineering and biotechnology · 2025
    Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. Review
  16. Observational
  17. Article
  18. Article
  19. Measuring Head Acceleration Like a CHAMP.Journal of athletic training · 2023
    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

9 authors.

Steve RowsonBiomedical Engineering and Mechanics, Virginia Tech, Blacksburg, VA, 24060, USA. rowson@vt.edu.ORCID http://orcid.org/0000-0002-3227-0596
Jason MihalikExercise and Sport Science, The University of North Carolina, Chapel Hill, NC, 27599, USA.
Jillian UrbanBiomedical Engineering, School of Medicine, Wake Forest University, Winston-Salem, NC, 27106, USA.
Julianne SchmidtDepartment of Kinesiology, Mary Frances Early College of Education, University of Georgia, Athens, GA, 30602, USA.
Steve MarshallGillings School of Public Health, The University of North Carolina, Chapel Hill, NC, 27599, USA.
Jaroslaw HarezlakSchool of Public Health, Indiana University Bloomington, Bloomington, IN, 47405, USA.
Brian D StemperJoint Department of Biomedical Engineering, Marquette University & Medical College of Wisconsin, Department of Neurosurgery, Medical College of Wisconsin, Neuroscience Research, Zablocki Veterans Affairs Medical Center, Milwaukee, WI, 53295, USA.
Mike McCreaDepartment of Neurosurgery, Medical College of Wisconsin, Neuroscience Research, Zablocki Veterans Affairs Medical Center, Milwaukee, WI, 53295, USA.
Jim FunkBiocore LLC, 1627 Quail Run, Charlottesville, VA, 22911, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Head impact measurement devices enable opportunities to collect impact data directly from humans to study topics like concussion biomechanics, head impact exposure and its effects, and concussion risk reduction techniques in sports when paired with other relevant data. With recent advances in head impact measurement devices and cost-effective price points, more and more investigators are using them to study brain health questions. However, as the field's literature grows, the variance in study quality is apparent. This brief paper aims to provide a high-level set of key considerations for the design and analysis of head impact measurement studies that can help avoid flaws introduced by sampling biases, false data, missing data, and confounding factors. We discuss key points through four overarching themes: study design, operational management, data quality, and data analysis.

Indexed as

Brain ConcussionFootballAccelerationBiomechanical PhenomenaConsensusHeadHead Protective DevicesHumansPractice Guidelines as TopicResearch DesignBiomechanicsConcussionHead accelerationHead impact exposureHead impact measurement devicesHead impact sensorsSports

Identifiers

PMID36253602
PMCPMC9652215

What OpenQuestion holds

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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.