Evidence map›Paper›PMID 34434689›Full record

ArticleEuropean journal of investigation in health, psychology and education2020

The Development of a BMI-Guided Shape Morphing Technique and the Effects of an Individualized Figure Rating Scale on Self-Perception of Body Size.

Geoffrey M Hudson, Yao Lu, Xiaoke Zhang, James Hahn, Johannah E Zabal, Finza Latif, John Philbeck

Abstract read
In one paragraph

Article in European journal of investigation in health, psychology and education, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

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

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. 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

7 authors.

Geoffrey M HudsonDepartment of Health, Kinesiology and Sport, University of South Alabama, Mobile, AL 36695, USA.ORCID 0000-0001-9780-941X
Yao LuDepartment of Computer Science, The George Washington University, Washington, DC 20052, USA.
Xiaoke ZhangDepartment of Statistics, The George Washington University, Washington, DC 20052, USA.
James HahnDepartment of Computer Science, The George Washington University, Washington, DC 20052, USA.ORCID 0000-0001-6535-8175
Johannah E ZabalDepartment of Exercise and Nutrition Science, The George Washington University, Washington, DC 20052, USA.
Finza LatifDepartment of Psychology, The George Washington University, Washington, DC 20052, USA.
John PhilbeckDepartment of Psychology, The George Washington University, Washington, DC 20052, USA.

Funding

Calculation of Percent Body Fat by Analyzing Virtual Body ModelsR21HL124443 · NHLBI · GEORGE WASHINGTON UNIVERSITY · PI HAHN, JAMES K · 2015 to 2016
$422k
NHLBI NIH HHS R21 HL124443
6 · The paper itself

Abstract

The creation of personalized avatars that may be morphed to simulate realistic changes in body size is useful when studying self-perception of body size. One drawback is that these methods are resource intensive compared to rating scales that rely upon generalized drawings. Little is known about how body perception ratings compare across different methods, particularly across differing levels of personalized detail in visualizations. This knowledge is essential to inform future decisions about the appropriate tradeoff between personalized realism and resource availability. The current study aimed to determine the impact of varying degrees of personalized realism on self-perception of body size. We explored this topic in young adult women, using a generalized line drawing scale, as well as several types of personalized avatars, including 3D textured images presented in immersive virtual reality (VR). Body perception ratings using generalized line drawings were often higher than responses using individualized visualization methods. While the personalized details seemed to help with identification, there were few differences among the three conditions containing different amounts of individualized realism (e.g., photo-realistic texture). These results suggest that using scales based on personalized texture and limb dimensions are beneficial, although presentation in immersive VR may not be essential.

Indexed as

avatarbody imagefigure rating scaleself-perceptionvirtual reality

Identifiers

PMID34434689
PMCPMC8314286

What OpenQuestion holds

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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.