Evidence map›Paper›PMID 30022446›Full record

ArticleLearning & behavior2018

Similarity between an unfamiliar human and the owner affects dogs' preference for human partner when responding to an unsolvable problem.

Orsolya Kiss, Krisztina Kovács, Flóra Szánthó, József Topál

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Article in Learning & behavior, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

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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

3 citing papers in PubMed.

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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.

Orsolya KissInstitute of Cognitive Neuroscience and Psychology, Hungarian Academy of Sciences, Budapest, Hungary. kiss.orsolya@ttk.mta.hu.
Krisztina KovácsInstitute of Cognitive Neuroscience and Psychology, Hungarian Academy of Sciences, Budapest, Hungary.
Flóra SzánthóDepartment of Ethology, Loránd Eötvös University, Budapest, Hungary.
József TopálInstitute of Cognitive Neuroscience and Psychology, Hungarian Academy of Sciences, Budapest, Hungary.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study investigates whether dogs are able to differentiate between people according to whether or not they show similarities to their owners. We hypothesized that dogs would show a preference for the "similar" partner when interacting with unfamiliar humans. After having familiarized with two experimenters displaying different degrees of similarity to their owners, dogs (N = 36) participated in a situation where the desired toy object was made inaccessible in order to find out whether they initiate interaction with the two partners differently. Two different types of "similarity cues" were used (either alone or combined with each other): (1) persistent behavioral characteristics (i.e., familiar vs. strange motion pattern and language usage) and (2) an unfamiliar arbitrary group marker (i.e., one of the potential helpers was wearing clothing similar to that worn by the owner). Results show that although dogs payed equal attention to the human partners displaying various types of similarity to their owners during familiarization, they exhibited a visual attention preference for the human whose motion pattern and language usage were similar to their owner's in the inaccessible-toy task. However, there was weak evidence of discrimination based on the arbitrary group marker (clothing). Although dogs' different tendencies to interact with the potential helpers do not necessarily imply an underlying ability to create social categories based on the degree of similarity between the owner and unfamiliar people, these results suggest that functionally human infant-analogue forms of social categorization may have emerged in dogs.

Indexed as

Attentional BiasHuman-Animal BondRecognition, PsychologyAnimalsCuesDogsFemaleHumansMaleProblem SolvingDog (Canis familiaris)Dog–human interactionSimilarity cueSocial categorizationSocial preference

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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.