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Journal of Child and Family Studies

, Volume 20, Issue 4, pp 529–540 | Cite as

Development and Validation of a Parent Report Measure for Assessing Social-Emotional Competencies of Children and Adolescents

  • Kenneth W. Merrell
  • Josh C. Felver-Gant
  • Karalyn M. Tom
Original Paper

Abstract

Based on the premises that strength-based assessment of children and adolescents is an important emerging area, and that additional tools for this purpose are needed, this study details development and validation efforts on a new strength-based assessment: the Social-Emotional Assets and Resilience Scale, parent form (SEARS-P). Following careful development of a comprehensive research prototype assessment, a large and diverse nationwide sample of more than 2,000 ratings of school-age children and adolescents were obtained from their parents and other caregivers. Factor analytic procedures revealed a robust and replicable underlying factor structure, including Self-Regulation/Responsibility, Social Competence, and Empathy factors. The factor scores and total score of the SEARS-P were shown to have strong internal consistency reliability, as well as strong interrater reliability between mother-father pairs who rated the same child. Convergent construct validity of the SEARS-P was established through findings of significant correlations with two established strength-based rating scales for use by parents. Construct validity of the SEARS-P was further bolstered through findings of significant gender differences in scores (with females rated as having higher levels of competency than males), as well as significant differences in scores based on educational disability status. Limitations and future research needs are discussed, as are implications of this study for research and practice with children and families.

Keywords

Assessment Positive psychology Social-emotional development 

References

  1. Achenbach, T. M., McConaughy, S. H., & Howell, C. T. (1987). Child/adolescent behavioral and emotional problems: Implications of cross-informant correlations for situational specificity. Psychological Bulletin, 101, 213–232.PubMedCrossRefGoogle Scholar
  2. Allen, S. J., & Graden, J. L. (2002). Best practices in collaborative problem solving for intervention design. In A. Thomas & J. Grimes (Eds.), Best practices in school psychology (4th ed., pp. 565–582). Bethesda, MD: National Association of School Psychologists.Google Scholar
  3. American Educational Research Association, American Psychological Association, & National Council on Measurement in Education. (1999). Standards for educational and psychological testing. Washington, DC: American Educational Research Association.Google Scholar
  4. American Psychiatric Association. (2000). Diagnostic and statistical manual of mental disorders (4th edn., text revision). Washington, DC: Author.Google Scholar
  5. Beaver, B. R. (2008). A positive approach to children’s internalizing problems. Professional Psychology: Research and Practice, 39, 129–136.CrossRefGoogle Scholar
  6. Bentler, P. M., & Bonett, D. G. (1980). Signifcance tests and goodness of fit in the analysis of covariance structures. Psychological Bulletin, 88, 588–606.CrossRefGoogle Scholar
  7. Browne, M. W., & Cudeck, R. (1993). Alternative ways of assessing model fit. In K. A. Bollen & J. S. Long (Eds.), Testing structural equation models (pp. 136–162). Beverly Hills, CA: Sage.Google Scholar
  8. Byrne, B. M. (1998). Structural equation modeling with LISREL, PRELIS, and SIMPLIS: Basic concepts, applications, and programming. Mahwah, NJ: Erlbaum.Google Scholar
  9. Cohen, J. (1992). A power primer. Psychological Bulletin, 112, 155–159.PubMedCrossRefGoogle Scholar
  10. Epstein, M. H. (2000). The behavioral and emotional rating scale: A strength-based approach to assessment. Assessment for Effective Intervention, 25, 249–256.CrossRefGoogle Scholar
  11. Gresham, F. M., & Elliott, S. N. (1990). Social skills rating system. Circle Pines, MN: American Guidance Service.Google Scholar
  12. Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 61, 1–55.CrossRefGoogle Scholar
  13. Jimerson, S. R., Sharkey, J. D., Nyborg, V., & Furlong, M. J. (2004). Strength-based assessment and school psychology: A summary and synthesis. California School Psychologist, 9, 9–19.Google Scholar
  14. Kaiser, H. F. (1960). The application of electronic computers to factor analysis. Educational and Psychological Measurement, 20, 141–151.CrossRefGoogle Scholar
  15. Marsh, H. W., Balla, J. R., & Hau, K. T. (1996). An evaluation of incremental fit indices: Clarification of mathematical and empirical processes. In G. A. Marcoulides & R. E. Schumacker (Eds.), Advanced structural equation modeling techniques (pp. 315–353). Hillsdale, NJ: Erlbaum.Google Scholar
  16. Marsh, H. W., Balla, J. R., & McDonald, R. R. (1988). Goodness-of-fit indexes in confirmatory factor analysis: The effect of sample size. Psychological Bulletin, 103, 391–410.CrossRefGoogle Scholar
  17. Merrell, K. W. (2008). Behavioral, social, and emotional assessment of children and adolescents (3rd ed.). New York: Taylor & Francis.Google Scholar
  18. Merrell, K. M., & Caldarella, P. (2002). Home and community social behavior scales. Baltimore, MD: Paul H. Brookes Publishing.Google Scholar
  19. Merrell, K. W., & Gimpel, G. A. (1998). Social skills of children and adolescents: Conceptualization, assessment, treatment. Mahwah, NJ: Erlbaum.Google Scholar
  20. Nickerson, A. B., & Fishman, C. (2009). Convergent and divergent validity of the devereux student strengths assessment. School Psychology Quarterly, 24, 48–59.CrossRefGoogle Scholar
  21. Rutter, M., Caspi, A., & Moffitt, T. E. (2003). Using sex differences in psychopathology to study causal mechanisms: Unifying issues and research strategies. Journal of Child Psychology and Psychiatry, 44, 1092–1115.PubMedCrossRefGoogle Scholar
  22. Salvia, J., Ysseldyke, J. E., & Bolt, S. (2007). Assessment in special and inclusive education (10th ed.). Boston: Houghton-Mifflin.Google Scholar
  23. Smolkowski, K. (2007). Correlated errors in CFA and SEM models. Unpublished technical report. Eugene, OR: Oregon Research Institute.Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  • Kenneth W. Merrell
    • 1
  • Josh C. Felver-Gant
    • 1
  • Karalyn M. Tom
    • 1
  1. 1.School Psychology ProgramUniversity of OregonEugeneUSA

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