Evidence map›Paper›PMID 37699941›Full record

ArticleScientific reports2023

Empathic embarrassment towards non-human agents in virtual environments.

Harin Hapuarachchi, Kento Higashihata, Maruta Sugiura, Atsushi Sato, Shoji Itakura, Michiteru Kitazaki

Abstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

6 authors.

Harin HapuarachchiDepartment of Computer Science and Engineering, Toyohashi University of Technology, Toyohashi, Aichi, Japan. harinmanujaya@gmail.com.ORCID http://orcid.org/0000-0002-3138-9229
Kento HigashihataDepartment of Computer Science and Engineering, Toyohashi University of Technology, Toyohashi, Aichi, Japan.
Maruta SugiuraDepartment of Computer Science and Engineering, Toyohashi University of Technology, Toyohashi, Aichi, Japan.
Atsushi SatoFaculty of Humanities, University of Toyama, Toyama, Japan.
Shoji ItakuraCenter for Baby Science, Doshisha University, Kyoto, Japan.
Michiteru KitazakiDepartment of Computer Science and Engineering, Toyohashi University of Technology, Toyohashi, Aichi, Japan. mich@tut.jp.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Humans feel empathic embarrassment by witnessing others go through embarrassing situations. We examined whether we feel such empathic embarrassment even with robot avatars. Participants observed a human avatar and a robot avatar face a series of embarrassing and non-embarrassing scenarios. We collected data for their empathic embarrassment and the cognitive empathy on a 7-point Likert scale. Both empathic embarrassment and cognitive empathy were significantly higher in the embarrassed condition compared to the non-embarrassed condition with both avatars, and the cognitive empathy was significantly higher with the human avatar. There was a tendency of participants showing a higher level of skin conductance while watching the human avatar go through embarrassing situations compared to the robot avatar. A following experiment showed that the average plausibility of the embarrassed condition was significantly higher with the human avatar compared to the robot avatar. However, plausibility scores for emotion were not significantly different among the conditions. These results suggest that humans can feel empathic embarrassment as well as cognitive empathy for robot avatars while cognitive empathy for robot avatars is comparatively lower, and that part of the empathic difference between human and robot avatars might be due to the difference of their plausibility.

Indexed as

EmbarrassmentEmpathyEmotionsHumans

Identifiers

PMID37699941
PMCPMC10497614

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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.