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How weird is the development of children's gratitude in the United States? Cross-cultural comparisons.

Lia B L FreitasFernanda PalharesHongjian CaoYue LiangNan ZhouIrina L MokrovaSoeun LeeAyse PayirLisa KiangSara E MendonçaElisa A Merçon-VargasLia O'BrienJonathan R H Tudge
Published in: Developmental psychology (2022)
Our interest is in the development of gratitude as a moral virtue, and its variability across different cultural contexts. Given psychology's overreliance on samples collected from the United Sates, Western Europe, and Australasia, we contrasted patterns of age-related expressions of gratitude among a sample of U.S. 7- to 14-year-old children with those from same-age samples from Brazil, China, Russia, South Korea, and Turkey ( N = 2,540, 54.7% female, M age = 10.61 years). The U.S. sample was diverse ( n = 730: Black 26.4%, White 40.4%, Latinx 19.9%, Asian 3.8%, Other 1.6%, Missing 7.0%; 55.7% female, M age = 10.52 years). The remaining samples were largely homogeneous by ethnicity. Our data were gathered using one quantitative scale to measure variations in the extent of gratitude that children expressed, and one qualitative measure to assess variability in the types of gratitude expressed by children of different ages. Both measures were chosen for their fit with the definition of virtuous gratitude. Hypotheses that the U.S. sample would differ from the others in extent and type of gratitude were largely supported. However, age-related differences in the type of gratitude expressed were similar across societies (e.g., in most samples older children were less likely to express concrete gratitude and more likely to express connective gratitude). Our results reveal the importance of treating gratitude as a virtue that develops during childhood and that is influenced by one's cultural group. Reliance on samples from a limited set of cultures is thus to be avoided. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
Keyphrases
  • young adults
  • systematic review
  • gene expression
  • deep learning
  • single cell
  • artificial intelligence