JOURNAL ARTICLE

Initial Development of the Child Responsiveness Scale for Early Childhood Settings.

  • Published In: Journal of Emotional & Behavioral Disorders, 2025, v. 33, n. 3. P. 159 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: McLeod, Bryce D.; Sutherland, Kevin S.; Broda, Michael D.; Granger, Kristen L.; Hollins, Nicole; Frey, Andy J.; Markowicz, Katrina A.; Dear, Emma 3 of 3

Abstract

This article focuses on the development and initial psychometric evaluation of the Child Responsiveness Scale (CRS), an observational tool designed to assess child responsiveness to teacher-delivered practices aimed at promoting social-emotional competencies in early childhood classrooms. Across two studies involving children at risk for emotional and behavioral disorders and their teachers, the CRS demonstrated acceptable interrater reliability and a stable two-factor structure distinguishing positive and negative responsiveness. The CRS scores showed preliminary evidence of construct validity, sensitivity to variation across teachers, children, and coders, and potential utility as a component of treatment integrity measurement in classroom-based interventions. The findings suggest the CRS may fill a measurement gap by providing a multi-item, reliable, and valid tool to better understand child engagement in intervention delivery, though further research is needed to expand its validation and applicability.

Additional Information

  • Source:Journal of Emotional & Behavioral Disorders. 2025/09, Vol. 33, Issue 3, p159
  • Document Type:Article
  • Subject Area:Social Sciences and Humanities
  • Publication Date:2025
  • ISSN:1063-4266
  • DOI:10.1177/10634266241271392
  • Accession Number:187593449
  • Copyright Statement:Copyright of Journal of Emotional & Behavioral Disorders is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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