Measuring Children's Emotion Knowledge: Steps Toward an Anti-Racist Approach to Early Childhood Assessments.

Anti-racist approach Emotion knowledge Pre-Kindergarten Race/ethnicity

Journal

Affective science
ISSN: 2662-205X
Titre abrégé: Affect Sci
Pays: Switzerland
ID NLM: 101766948

Informations de publication

Date de publication:
Mar 2022
Historique:
received: 30 12 2020
accepted: 21 01 2022
entrez: 1 9 2022
pubmed: 2 9 2022
medline: 2 9 2022
Statut: epublish

Résumé

Emotion knowledge (EK) is a malleable set of skills that is central to social interactions and school success during early childhood. The current study describes an anti-racist approach to adapting an EK measure that assesses knowledge of facial expressions to be ecologically valid for young children of color attending pre-Kindergarten (pre-K) programs in a large urban school district. This approach involved (1) attending to race/ethnicity in selection of visual stimuli, (2) ensuring appropriate translation and language for administration, and (3) exploring the functioning of the measure within a racially, ethnically, and linguistically diverse group of children. A total of 235 children (67.4% Latinx, 14.1% non-Latinx Black, 7.1% non-Latinx White, 7.8% Asian, 3.6% another racial/ethnicity) were assessed in English (74%) or Spanish (26%) during the fall of pre-K (mean age = 4.4). Both English and Spanish versions appear to have similar reliability, although accuracy levels were lower when administered in Spanish. No differences in mean accuracy scores were found across racial/ethnic groups or for boys versus girls. This study contributes to the growing literature necessary to advance anti-racist research in affective science. The online version contains supplementary material available at 10.1007/s42761-022-00105-w.

Identifiants

pubmed: 36046093
doi: 10.1007/s42761-022-00105-w
pii: 105
pmc: PMC9382994
doi:

Types de publication

Case Reports

Langues

eng

Pagination

62-68

Subventions

Organisme : NHLBI NIH HHS
ID : K01 HL138114
Pays : United States

Informations de copyright

© The Society for Affective Science 2022.

Déclaration de conflit d'intérêts

Conflict of InterestThe authors declare no conflict of interest.

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Auteurs

Dimitra Kamboukos (D)

Department of Population Health, NYU Grossman School of Medicine, 227 East 30th Street, 7th Floor, New York, NY 10016 USA.

Alexandra Ursache (A)

Department of Population Health, NYU Grossman School of Medicine, 227 East 30th Street, 7th Floor, New York, NY 10016 USA.

Sabrina Cheng (S)

Department of Population Health, NYU Grossman School of Medicine, 227 East 30th Street, 7th Floor, New York, NY 10016 USA.

Vanessa Rodriguez (V)

Department of Population Health, NYU Grossman School of Medicine, 227 East 30th Street, 7th Floor, New York, NY 10016 USA.

Gena Gelb (G)

Department of Population Health, NYU Grossman School of Medicine, 227 East 30th Street, 7th Floor, New York, NY 10016 USA.

R Gabriela Barajas-Gonzalez (RG)

Department of Population Health, NYU Grossman School of Medicine, 227 East 30th Street, 7th Floor, New York, NY 10016 USA.

Spring Dawson-McClure (S)

Department of Population Health, NYU Grossman School of Medicine, 227 East 30th Street, 7th Floor, New York, NY 10016 USA.

Laurie M Brotman (LM)

Department of Population Health, NYU Grossman School of Medicine, 227 East 30th Street, 7th Floor, New York, NY 10016 USA.

Classifications MeSH