Evidence map›Paper›PMID 38410354›Full record

ArticleFrontiers in sports and active living2024

An interdisciplinary framework to optimize the anticipation skills of high-level athletes using virtual reality.

Gilles Montagne, Nicolas Mascret, Martin Bossard, Loïc Chomienne, Simon Ledouit, Guillaume Rao, Nicolas Tordi, Eulalie Verhulst, Richard Kulpa

Open access · goldAbstract read
In one paragraph

Article in Frontiers in sports and active living, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
4.7field-weighted citation impact, top 6% 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

2 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. 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 at 3 institutions in 1 country.

Gilles Montagne *Aix-Marseille Univ, CNRS, ISM, Marseille, France.
Nicolas Mascret *Aix-Marseille Univ, CNRS, ISM, Marseille, France.
Martin Bossard *Aix-Marseille Univ, CNRS, ISM, Marseille, France.
Loïc ChomienneAix-Marseille Univ, CNRS, ISM, Marseille, France.
Simon LedouitUniv Rennes, Inria, M2S, Rennes, France.
Guillaume RaoAix-Marseille Univ, CNRS, ISM, Marseille, France.
Nicolas TordiPEPITE EA4267, (EPSI), University Bourgogne Franche-Comté, Besançon, France.
Eulalie VerhulstUniv Rennes, Inria, M2S, Rennes, France.
Richard KulpaUniv Rennes, Inria, M2S, Rennes, France.
Centre National de la Recherche Scientifique · FRUniversité Rennes 2 · FRUniversité Bourgogne Franche-Comté · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The ambition of our contribution is to show how an interdisciplinary framework can pave the way for the deployment of innovative virtual reality training sessions to improve anticipation skills in top-level athletes. This improvement is so challenging that some authors say it is like "training for the impossible". This framework, currently being implemented as part of a project to prepare athletes for the 2024 Olympic Games in Paris, based on the ecological-dynamics approach to expertise, is innovative in its interdisciplinary nature, but also and above all because it overcomes the limitations of more traditional training methods in the field designed to optimize anticipation skills in top-level athletes. The ambition is to tackle successive challenges ranging from the design of virtual partners and opponents to the deployment of training programs in virtual reality, while ensuring the acceptability and acceptance of such innovative virtual reality training protocols and measuring associated workloads.

Indexed as

anticipation skillsecological-dynamicsinterdisciplinarytop level sportvirtual reality

Identifiers

PMID38410354
PMCPMC10895038
OpenAlexW4391750312

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.