Evidence map›Paper›PMID 41991581›Full record

ArticleScientific reports2026

Perceived human-robot relational structures: a pictogram-based questionnaire to assess ideal and assumed relationships.

Tomonori Kubota, Takahisa Uchida, Hideyuki Takahashi, Midori Ban, Hiroshi Ishiguro

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Tomonori Kubota *Graduate School of Engineering, Nagoya University, Nagoya, 464-8601, Japan.
Takahisa Uchida *Graduate School of Engineering Science, The University of Osaka, Toyonaka, 560-8531, Japan. uchida.takahisa@irl.sys.es.osaka-u.ac.jp.
Hideyuki Takahashi *Graduate School of Engineering Science, The University of Osaka, Toyonaka, 560-8531, Japan. h-takahashi@haruka.otemon.ac.jp.
Midori BanGraduate School of Engineering Science, The University of Osaka, Toyonaka, 560-8531, Japan.
Hiroshi IshiguroGraduate School of Engineering Science, The University of Osaka, Toyonaka, 560-8531, Japan.

Funding

JST PRESTO JPMJPR23I2
6 · The paper itself

Abstract

Evaluations in human-robot interaction (HRI) have traditionally focused on surface-level impressions such as likability and anthropomorphism, often neglecting the underlying relational structures that define mutual contributions and shared goals. Understanding these relational dynamics is crucial for fostering effective and sustainable human-robot collaborations. Here, we developed and validated a novel pictogram-based questionnaire grounded in social psychology to capture relational structures, conducting three scenario-based online surveys. We examined ideal and assumed relational structures in human-human and human-robot contexts across varying robot appearances, roles, and utterances. We distinguish between ideal relational structures (what users would like to establish; Surveys A and B) and assumed (expected) relational structures (what users believe would emerge under the described conditions; Survey C). Our results reveal that ideal relational structures vary by human relationship type, and that a robot's communicative behavior significantly influences perceived relational structures, often more than physical appearance. These findings suggest that assessing relational perceptions can inform the design of robots better aligned with user expectations, enhancing long-term engagement and collaboration in HRI.

Indexed as

RoboticsAdultFemaleHumansMaleSurveys and QuestionnairesYoung Adult

Identifiers

PMID41991581
PMCPMC13246732

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.