Evidence map›Paper›PMID 35737184›Full record

ArticleCognitive research: principles and implications2022

How sign language expertise can influence the effects of face masks on non-linguistic characteristics.

Wee Kiat Lau, Jana Chalupny, Klaudia Grote, Anke Huckauf

Abstract read
In one paragraph

Article in Cognitive research: principles and implications, 2022. 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

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

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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.

Wee Kiat LauGeneral Psychology, Institute of Psychology and Pedagogics, Ulm University, Albert-Einstein-Allee 47, 89081, Ulm, Germany. wee.lau@uni-ulm.de.ORCID 0000-0001-6472-0419
Jana ChalupnyRegionalstelle Bad Nauheim, Autismus-Therapieinstitut Langen, Karlstraße 57 - 59, 61231, Bad Nauheim, Germany.
Klaudia GroteCompetence Centre for Sign Language and Gesture (SignGes), RWTH Aachen, Theaterplatz 14, 52062, Aachen, Germany.
Anke HuckaufGeneral Psychology, Institute of Psychology and Pedagogics, Ulm University, Albert-Einstein-Allee 47, 89081, Ulm, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Face masks occlude parts of the face which hinders social communication and emotion recognition. Since sign language users are known to process facial information not only perceptually but also linguistically, examining face processing in deaf signers may reveal how linguistic aspects add to perceptual information. In general, signers could be born deaf or acquire hearing loss later in life. For this study, we focused on signers who were born deaf. Specifically, we analyzed data from a sample of 59 signers who were born deaf and investigated the impacts of face masks on non-linguistic characteristics of the face. Signers rated still-image faces with and without face masks for the following characteristics: arousal and valence of three facial expressions (happy, neutral, sad), invariant characteristics (DV:sex, age), and trait-like characteristics (attractiveness, trustworthiness, approachability). Results indicated that, when compared to masked faces, signers rated no-masked faces with stronger valence intensity across all expressions. Masked faces also appeared older, albeit a tendency to look more approachable. This experiment was a repeat of a previous study conducted on hearing participants, and a post hoc comparison was performed to assess rating differences between signers and hearing people. From this comparison, signers exhibited a larger tendency to rate facial expressions more intensely than hearing people. This suggests that deaf people perceive more intense information from facial expressions and face masks are more inhibiting for deaf people than hearing people. We speculate that deaf people found face masks more approachable due to societal norms when interacting with people wearing masks. Other factors like age and face database's legitimacy are discussed.

Indexed as

DeafnessSign LanguageFacial ExpressionHumansLinguisticsMasksDeafEmotion and personality recognitionFacemasksHearingSign language

Identifiers

PMID35737184
PMCPMC9219384

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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.