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The Efficient Assessment of Self-Esteem: Proposing the Brief Rosenberg Self-Esteem Scale

Author

Listed:
  • Renan P. Monteiro

    (Federal University of Mato Grosso)

  • Gabriel Lins de Holanda Coelho

    (University College Cork)

  • Paul H. P. Hanel

    (University of Essex)

  • Emerson Diógenes Medeiros

    (Federal University of Delta do Parnaíba)

  • Phillip Dyamond Gomes Silva

    (Federal University of Mato Grosso)

Abstract

Self-esteem is defined as sense of self-worth and self-respect, being crucial for understanding people’s well-being and success. It is one of the most studied constructs in the social sciences, with the Rosenberg Self-Esteem Scale (RSES) being the most used measure. Across four studies (N = 1450), we tested the psychometric parameters of an abbreviated version of the RSES. Through Item Response Theory, the five best items were selected to form the unidimensional Brief Rosenberg Self-Esteem Scale (B-RSES), a reliable and valid measure of self-esteem, which is invariant across age groups and gender. In addition, both RSES and B-RSES correlated very similarly with the Big Five Personality Factors. Also, the B-RSES was strongly correlated with three other short measures of self-esteem, besides being more strongly associated with a range of variables such as conscientiousness and self-competence in comparison to the other three short scales. Together, the B-RSES is especially useful in research that requires rapid evaluation and the use of multiple variables.

Suggested Citation

  • Renan P. Monteiro & Gabriel Lins de Holanda Coelho & Paul H. P. Hanel & Emerson Diógenes Medeiros & Phillip Dyamond Gomes Silva, 2022. "The Efficient Assessment of Self-Esteem: Proposing the Brief Rosenberg Self-Esteem Scale," Applied Research in Quality of Life, Springer;International Society for Quality-of-Life Studies, vol. 17(2), pages 931-947, April.
    • Handle: RePEc:spr:ariqol:v:17:y:2022:i:2:d:10.1007_s11482-021-09936-4
    DOI: 10.1007/s11482-021-09936-4
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    References listed on IDEAS

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    1. Chalmers, R. Philip, 2012. "mirt: A Multidimensional Item Response Theory Package for the R Environment," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 48(i06).
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