Evidence map›Paper›PMID 35707718›Full record

ArticleiScience2022

Human but not robotic gaze facilitates action prediction.

Emmanuele Tidoni, Henning Holle, Michele Scandola, Igor Schindler, Loron Hill, Emily S Cross

Abstract read
In one paragraph

Article in iScience, 2022. 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
–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

4 citing papers in PubMed.

  1. Article
  2. Article
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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

6 authors.

Emmanuele TidoniHuman Technology Laboratory, Department of Psychology, University of Hull, Hull HU6 7RX, UK.
Henning HolleDepartment of Psychology, University of Hull, Hull HU6 7RX, UK.
Michele ScandolaNPSY.Lab.VR & BASIC_NPSY, Department of Human Sciences, University of Verona, 37129 Verona, Italy.
Igor SchindlerDepartment of Psychology, University of Hull, Hull HU6 7RX, UK.
Loron HillHuman Technology Laboratory, Department of Psychology, University of Hull, Hull HU6 7RX, UK.
Emily S CrossDepartment of Cognitive Science, Macquarie University, Sydney, NSW 2109, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Do people ascribe intentions to humanoid robots as they would to humans or non-human-like animated objects? In six experiments, we compared people's ability to extract non-mentalistic (i.e., where an agent is looking) and mentalistic (i.e., what an agent is looking at; what an agent is going to do) information from gaze and directional cues performed by humans, human-like robots, and a non-human-like object. People were faster to infer the mental content of human agents compared to robotic agents. Furthermore, although the absence of differences in control conditions rules out the use of non-mentalizing strategies, the human-like appearance of non-human agents may engage mentalizing processes to solve the task. Overall, results suggest that human-like robotic actions may be processed differently from humans' and objects' behavior. These findings inform our understanding of the relevance of an object's physical features in triggering mentalizing abilities and its relevance for human-robot interaction.

Indexed as

cognitive neuroscienceresearch methodology social sciencesRobotics

Identifiers

PMID35707718
PMCPMC9189121

What OpenQuestion holds

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LicenceCC BY
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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.