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Journal of Abnormal Child Psychology

, Volume 22, Issue 5, pp 611–628 | Cite as

Peer ratings of depression, anxiety, and aggression in inpatient and elementary school children: Rating biases and influence of rater's self-reported depression, anxiety, and aggression

  • Catherine C. Epkins
Article

Abstract

Using parallel self-, peer, and teacher rating scales, several rating biases in children's peer ratings of depression, anxiety, and aggression were examined. Participants were 66 inpatient and 133 elementary school children (N = 199, 109 boys, 90 girls; 61% white, 39% black) aged 8 to 12, and their teachers. Results showed significant halo bias in both the children's peer ratings and the teachers' ratings. Children's self-reports on each of the three traits were significantly related to their peer ratings of the same trait, while adjusting for socioeconomic status and the peers' teachers' ratings of the same trait. Children who rated themselves as high on each trait rated their peers significantly higher on the same trait than children who rated themselves as medium or low; and for depression and anxiety, those who rated themselves as medium rated their peers significantly higher on those traits than those who rated themselves as low. For both depression and aggression, children's self-reports on the trait were significantly related to their peer ratings of the same trait, but not significantly related to their peer ratings of different traits. Disagreements between children's and teachers' ratings of the peers on all three traits were significantly related to child self-reports on each trait, indicating a possible distortion in children's peer ratings due to self-report. The implications of the results for both peer and others' assessments are discussed, and further investigation of rating biases in other informants' assessments is encouraged.

Keywords

Socioeconomic Status Elementary School School Child School Psychology Teacher Rating 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Plenum Publishing Corporation 1994

Authors and Affiliations

  • Catherine C. Epkins
    • 1
  1. 1.Auburn UniversityAuburn

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