Evidence map›Paper›PMID 37251279›Full record

ArticleInternational journal of social robotics2023

Mind Perception in HRI: Exploring Users' Attribution of Mental and Emotional States to Robots with Different Behavioural Styles.

Ilenia Cucciniello, Sara Sangiovanni, Gianpaolo Maggi, Silvia Rossi

Open access · hybridFull text read
In one paragraph

Article in International journal of social robotics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
8.0field-weighted citation impact, top 2% of its field
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

4 citing papers in PubMed, 24 citations in OpenAlex.

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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

4 authors at 2 institutions in 1 country.

Ilenia CuccinielloDepartment of Electrical Engineering and Information Technologies, University of Naples Federico II, Via Claudio 80, 80125 Naples, Italy.
Sara SangiovanniDepartment of Electrical Engineering and Information Technologies, University of Naples Federico II, Via Claudio 80, 80125 Naples, Italy.
Gianpaolo MaggiDepartment of Psychology, University of Campania Luigi Vanvitelli, Viale Ellittico, 31, 81100 Caserta, Italy.
Silvia RossiDepartment of Electrical Engineering and Information Technologies, University of Naples Federico II, Via Claudio 80, 80125 Naples, Italy.ORCID 0000-0002-3379-1756
Federico II University Hospital · ITUniversity of Campania "Luigi Vanvitelli" · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Theory of Mind is crucial to understand and predict others' behaviour, underpinning the ability to engage in complex social interactions. Many studies have evaluated a robot's ability to attribute thoughts, beliefs, and emotions to humans during social interactions, but few studies have investigated human attribution to robots with such capabilities. This study contributes to this direction by evaluating how the cognitive and emotional capabilities attributed to the robot by humans may be influenced by some behavioural characteristics of robots during the interaction. For this reason, we used the Dimensions of Mind Perception questionnaire to measure participants' perceptions of different robot behaviour styles, namely Friendly, Neutral, and Authoritarian, which we designed and validated in our previous works. The results obtained confirmed our hypotheses because people judged the robot's mental capabilities differently depending on the interaction style. Particularly, the Friendly is considered more capable of experiencing positive emotions such as Pleasure, Desire, Consciousness, and Joy; conversely, the Authoritarian is considered more capable of experiencing negative emotions such as Fear, Pain, and Rage than the Friendly. Moreover, they confirmed that interaction styles differently impacted the perception of the participants on the Agency dimension, Communication, and Thought.

Indexed as

Interaction styleMind attributionRobot behaviour

Identifiers

PMID37251279
PMCPMC10040176
OpenAlexW4360986216

What OpenQuestion holds

Textfull text, public
LicenceCC BY
measurements read11
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.