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A New Brief Scale to Measure Optimism.

Cirilo H Garcia Cadena, Leopoldo Daniel González1, Adrián Valle de la O2

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Summary

A shorter, valid, and reliable version of the Interactive Optimism Scale-Garcia was developed using maximum likelihood analysis. The Brief Interactive Optimism Scale-G demonstrates excellent fit and reliability for measuring optimism.

Keywords:
Optimismconfirmatory factor analysisfactorial invariancereliabilityvalidity

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Area of Science:

  • Psychological assessment
  • Psychometrics
  • Social psychology

Background:

  • The Interactive Optimism Scale-Garcia is a widely used measure of optimism.
  • A need exists for a shorter, more efficient version of the scale for practical applications.
  • Maximum likelihood methods offer a robust approach for scale reduction and validation.

Purpose of the Study:

  • To develop and validate a brief version of the Interactive Optimism Scale-Garcia using maximum likelihood estimation.
  • To assess the psychometric properties, including reliability and validity, of the new brief scale.
  • To confirm factorial invariance across sexes.

Main Methods:

  • Confirmatory factor analysis (CFA) was employed on data from 502 adult participants (263 women, 239 men).
  • Maximum likelihood estimation was used to reduce the scale items.
  • Goodness-of-fit indices (GFI, NFI, CFI, RMSEA, SRMR) and internal consistency measures (omega, alpha) were calculated.

Main Results:

  • A four-item scale, the Brief Interactive Optimism Scale-G, was successfully developed.
  • The scale demonstrated excellent goodness of fit (e.g., CFI=1.000, RMSEA=0.000) and factorial invariance across sexes.
  • High internal consistency (ordinal alpha=0.906) and significant correlations with self-esteem (r=0.779), depression (r=-0.810), and psychopathy (r=-0.670) were observed.

Conclusions:

  • The Brief Interactive Optimism Scale-G is a valid, reliable, and psychometrically sound measure.
  • This brief scale offers an efficient alternative for assessing optimism in Mexican populations.
  • The findings support the utility of maximum likelihood methods in developing concise psychological instruments.