Evidence map›Paper›PMID 33101099›Full record

ArticleFrontiers in psychology2020

A Robot Is Not Worth Another: Exploring Children's Mental State Attribution to Different Humanoid Robots.

Federico Manzi, Giulia Peretti, Cinzia Di Dio, Angelo Cangelosi, Shoji Itakura, Takayuki Kanda, Hiroshi Ishiguro, Davide Massaro, Antonella Marchetti

Abstract read
In one paragraph

Article in Frontiers in psychology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing 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

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

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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

9 authors.

Federico ManziResearch Unit on Theory of Mind, Department of Psychology, Università Cattolica del Sacro Cuore, Milan, Italy.
Giulia PerettiResearch Unit on Theory of Mind, Department of Psychology, Università Cattolica del Sacro Cuore, Milan, Italy.
Cinzia Di DioResearch Unit on Theory of Mind, Department of Psychology, Università Cattolica del Sacro Cuore, Milan, Italy.
Angelo CangelosiSchool of Computer Science, University of Manchester, Manchester, United Kingdom.
Shoji ItakuraCentre for Baby Science, Doshisha University, Kyoto, Japan.
Takayuki KandaHuman-Robot Interaction Laboratory, Graduate School of Informatics, Kyoto University, Kyoto, Japan.
Hiroshi IshiguroAdvanced Telecommunications Research Institute International, IRC/HIL, Keihanna Science City, Kyoto, Japan.
Davide MassaroResearch Unit on Theory of Mind, Department of Psychology, Università Cattolica del Sacro Cuore, Milan, Italy.
Antonella MarchettiResearch Unit on Theory of Mind, Department of Psychology, Università Cattolica del Sacro Cuore, Milan, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recent technological developments in robotics has driven the design and production of different humanoid robots. Several studies have highlighted that the presence of human-like physical features could lead both adults and children to anthropomorphize the robots. In the present study we aimed to compare the attribution of mental states to two humanoid robots, NAO and Robovie, which differed in the degree of anthropomorphism. Children aged 5, 7, and 9 years were required to attribute mental states to the NAO robot, which presents more human-like characteristics compared to the Robovie robot, whose physical features look more mechanical. The results on mental state attribution as a function of children's age and robot type showed that 5-year-olds have a greater tendency to anthropomorphize robots than older children, regardless of the type of robot. Moreover, the findings revealed that, although children aged 7 and 9 years attributed a certain degree of human-like mental features to both robots, they attributed greater mental states to NAO than Robovie compared to younger children. These results generally show that children tend to anthropomorphize humanoid robots that also present some mechanical characteristics, such as Robovie. Nevertheless, age-related differences showed that they should be endowed with physical characteristics closely resembling human ones to increase older children's perception of human likeness. These findings have important implications for the design of robots, which also needs to consider the user's target age, as well as for the generalizability issue of research findings that are commonly associated with the use of specific types of robots.

Indexed as

anthropomorphismchildrenchild–robot interaction (cHRI)differences among robotshumanoid and anthropomorphic robotsmental states attributionsocial robots

Identifiers

PMID33101099
PMCPMC7554578

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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.