The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.
Can Children Provide Coherent, Stable, and Valid Self-Reports on the Big Five Dimensions? A Longitudinal Study From Ages 5 to 7.
Abstract
Research on early childhood personality has been scarce. Self-reports of Big Five personality traits were measured longitudinally with the Berkeley Puppet Interview when children were 5, 6, and 7 years of age. For comparative purposes, Big Five self-reports were collected in a sample of college students. The children's self-reports showed levels of consistency and differentiation that approached those of the college age sample. Children's personality self-reports demonstrated significant correlations across the 1- and 2-year longitudinal intervals. Substantial and increasing convergence was found between children's self-reports of Extraversion, Agreeableness, and Conscientiousness and conceptually relevant behavior ratings provided by mothers, fathers, and teachers. Children's self-reports of Neuroticism were unrelated to adults' reports but did predict sadness and anxious behavior observed in the laboratory. The results provide the beginnings of an account of how the Big Five dimensions begin to be salient and emerge as coherent, stable, and valid self-perceptions in childhood.
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Metadata
- Authors
- Measelle, J. R., John, O. P., Ablow, J. C., Cowan, P. A., & Cowan, C. P.
- Venue
- Journal of Personality and Social Psychology
- Published
- 2005
- Volume
- 89
- Issue
- 1
- Pages
- 90-106
- ISSN
- 0022-3514 (ISSN-L)
- 1939-1315
- OpenAlex
- W2018205067
- Cited by
- 240
- References
- 13
- FWCI
- 10.29
- Type
- journal article
- Language
- en
- Open access
- closed
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- Measelle, J. R., John, O. P., Ablow, J. C., Cowan, P. A., & Cowan, C. P. (2005). Can Children Provide Coherent, Stable, and Valid Self-Reports on the Big Five Dimensions? A Longitudinal Study From Ages 5 to 7. Journal of Personality and Social Psychology. https://doi.org/10.1037/0022-3514.89.1.90
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.