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A Multi-Group Investigation of the CES-D's Measurement Structure Across Adolescents, Young Adults and Middle-Aged Adults

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  • Marc Blais
  • Ursula Hess
  • Andrea S. Riddle

Abstract

The aim of the present research was to investigate, via multi-group analyses, the dimensional structure of the CES-D (Radloff, 1977) across three age groups. For this, three studies were conducted on cross-sectional samples of French speaking respondents, varying in age and drawn from the Quebec educational system: 599 adolescent high school students, 291 young adults attending university, and 844 middle-aged adult employees of a school board. Five a priori hypothesized models were tested via structural equation modeling: a single-factor, two three-factors, a four-factor and a second-order factor model. The four-factor and the second-order factor model provided the best fit and the latter model remained largely invariant across the groups when tested via multi-group comparisons. Other psychometric characteristics of the French Canadian version of the scale (e.g., test-retest reliability, internal consistency, convergent-discriminant validity) were also shown to be satisfactory. Possible applications of subcomponent scores in research (based on the multidimensional structure of the scale), rather than the commonly used composite CES-D score, are discussed. Le but de cette recherche était d'évaluer, à l'aide d'analyses multi-groupes, la structure factorielle de notre version française du CES-D (Radloff, 1977) parmi trois groupes d'âge. Trois études transversales ont été réalisées auprès d'échantillons francophones du Québec provenant du système d'éducation : 599 élèves du secondaire, 291 étudiants à l'Université et 844 employés d'une commission scolaire. Cinq modèles a priori ont été évalués à l'aide d'analyses de modélisation par équations structurales : un modèle unidimensionnel, deux modèles à trois dimensions, un modèle à quatre facteurs et un modèle hiérarchique. Les deux derniers modèles se sont avérés les meilleurs. Les analyses multi-groupes révèlent que le modèle hiérarchique était le plus invariant parmi les différents groupes d'âges. D'autres caractéristiques psychométriques de cette version canadienne française du CES-D, au niveau de la fiabilité temporelle, de la consistance interne et de la validité convergente-discriminante, se sont avérées satisfaisantes. Les implications concernant l'utilisation des scores des dimensions plutôt que du score total de l'ensemble de la mesure sont discutées.

Suggested Citation

  • Marc Blais & Ursula Hess & Andrea S. Riddle, 2002. "A Multi-Group Investigation of the CES-D's Measurement Structure Across Adolescents, Young Adults and Middle-Aged Adults," CIRANO Working Papers 2002s-36, CIRANO.
  • Handle: RePEc:cir:cirwor:2002s-36
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    References listed on IDEAS

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    1. Iwata, Noboru & Roberts, Robert E., 1996. "Age differences among Japanese on the center for epidemiologic studies depression scale: An ethnocultural perspective on somatization," Social Science & Medicine, Elsevier, vol. 43(6), pages 967-974, September.
    2. Hamparsum Bozdogan, 1987. "Model selection and Akaike's Information Criterion (AIC): The general theory and its analytical extensions," Psychometrika, Springer;The Psychometric Society, vol. 52(3), pages 345-370, September.
    3. Hirotugu Akaike, 1987. "Factor analysis and AIC," Psychometrika, Springer;The Psychometric Society, vol. 52(3), pages 317-332, September.
    4. Guarnaccia, Peter J. & Angel, Ronald & Worobey, Jacqueline Lowe, 1989. "The factor structure of the CES-D in the Hispanic health and nutrition examination survey: The influences of ethnicity, gender and language," Social Science & Medicine, Elsevier, vol. 29(1), pages 85-94, January.
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