Evidence map›Paper›PMID 35585184›Full record

ArticleInternational journal of obesity (2005)2022

Obesity and individual performance: the case of eSports.

Petr Parshakov, Iuliia Naidenova, Arthur Assanskiy, Cornel Nesseler

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Article in International journal of obesity (2005), 2022. 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
–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

2 citing papers in PubMed.

  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

4 authors.

Petr ParshakovHSE University, Perm, Russia.
Iuliia NaidenovaHSE University, Perm, Russia.
Arthur AssanskiyHSE University, Moscow, Russia.
Cornel NesselerNorwegian University of Science and Technology, Trondheim, Norway. Cornel.M.Nesseler@ntnu.no.ORCID 0000-0001-7900-4175

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND/

objectivesThe study considers the problem of the inclusion of people with obesity in the context of the growing role of computer-based work. Negative stereotypes about people with obesity still hold even when they are irrelevant in tasks that require little physical activity. SUBJECTS/

methodsUsing data from the realm of competitive video gaming (eSports) and image recognition-based metric of body mass index metric derived from artificial intelligence, we examine the individual performance depending on weight. The sample includes 821 players and 127,533 player performance observations.

resultsFor shorter tasks, individuals with normal weight performed better than individuals with obesity. For longer tasks, however, people with Class III (severe) obesity outperformed all others, and their advantage increased with task duration.

conclusionsOur findings shed light on an understanding of how actually body features are related to objective individual performance in a competitive context.

Indexed as

Artificial IntelligenceVideo GamesBody Mass IndexExerciseHumansObesity

Identifiers

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Textmetadata
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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.