Evidence map›Paper›PMID 35617241›Full record

ArticlePloS one2022

Top-down effect of body representation on pain perception.

Miki Matsumuro, Ning Ma, Yuki Miura, Fumihisa Shibata, Asako Kimura

Abstract read
In one paragraph

Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. 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

5 authors.

Miki MatsumuroCollege of Information Science and Engineering, Ritsumeikan University, Kusatsu, Shiga, Japan.ORCID 0000-0002-0647-1263
Ning MaGraduate School of Information Science and Engineering, Ritsumeikan University, Kusatsu, Shiga, Japan.
Yuki MiuraGraduate School of Information Science and Engineering, Ritsumeikan University, Kusatsu, Shiga, Japan.
Fumihisa ShibataCollege of Information Science and Engineering, Ritsumeikan University, Kusatsu, Shiga, Japan.
Asako KimuraCollege of Information Science and Engineering, Ritsumeikan University, Kusatsu, Shiga, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Many studies on body representation intend to change the perceived size, material, and structure of the body. However, whether the perception of a stimulus can be modified by manipulating body representation remains largely unexplored. Thus, the current study investigated the relationship between transparency of body representation and pain perception. Using augmented reality technology, we made the participants' limbs transparent and analyzed changes in body representation. Using a questionnaire, we confirmed that the participants perceived their limb as transparent. Simultaneously, their sense of ownership of the limb decreased, because they felt that it no longer belonged to their body. The participants were given an electrical stimulus to assess their subjective perception of pain intensity. An increase in limb opacity decreased the perception of pain, which, in turn, increased the feeling of transparency. These results suggested that the feeling of transparency in their limb favored the decrease in perceived pain. This effect was modified by body ownership, where high levels reinforced the analgesic effect. However, body ownership displayed a positive relationship with perceived pain. The study suggests that body transparency may constitute a strategy for decreasing refractory pain given that body ownership is retained at a high level.

Indexed as

Body ImageTouch PerceptionEmotionsHumansOwnershipPainPain PerceptionVisual Perception

Identifiers

PMID35617241
PMCPMC9135274

What OpenQuestion holds

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Registered trials

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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.