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A Follow up on the Continuum Theory of Eco-Anxiety: Analysis of the Climate Change Anxiety Scale Using Item Response Theory among French Speaking Population

Author

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  • Taha Hannachi

    (Laboratory of Psychology, Cognition, Behaviour, Communication (LP3C), Department of Psychology, Faculty of Human Science, Rennes 2 University, 35000 Rennes, France)

  • Sonya Yakimova

    (Laboratory of Psychology, Cognition, Behaviour, Communication (LP3C), Department of Psychology, Faculty of Human Science, Rennes 2 University, 35000 Rennes, France)

  • Alain Somat

    (Laboratory of Psychology, Cognition, Behaviour, Communication (LP3C), Department of Psychology, Faculty of Human Science, Rennes 2 University, 35000 Rennes, France)

Abstract

The mental health impact of the environmental crisis, particularly eco-anxiety, is a growing research topic whose measurement still lacks consensus. This study aims to use item response theory (IRT) to gain a deeper understanding of the constructs measured by existing questionnaires. To conduct this review, we applied the graded response model with the help of the MIRT package in R on open-access data from the short French version of the Climate Change Anxiety Questionnaire, which measures cognitive-emotional impairment and functional impairment. The models tested in this study are the one, two, and three-factor models, and the bifactor model. After model selection, the psychometric properties of the selected model were tested. Our results suggest that the unidimensional model seems to be the most appropriate for measuring eco-anxiety. The item difficulty parameter extracted from the IRT enabled us to discuss the severity levels of the items comprising this tool. The Climate Change Anxiety Questionnaire appears to be more appropriate for measuring moderate to severe eco-anxiety. Avenues for improving this questionnaire and the measurement of eco-anxiety in general are then discussed.

Suggested Citation

  • Taha Hannachi & Sonya Yakimova & Alain Somat, 2024. "A Follow up on the Continuum Theory of Eco-Anxiety: Analysis of the Climate Change Anxiety Scale Using Item Response Theory among French Speaking Population," IJERPH, MDPI, vol. 21(9), pages 1-16, August.
    • Handle: RePEc:gam:jijerp:v:21:y:2024:i:9:p:1158-:d:1468171
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    References listed on IDEAS

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    1. R. Bock & Murray Aitkin, 1981. "Marginal maximum likelihood estimation of item parameters: Application of an EM algorithm," Psychometrika, Springer;The Psychometric Society, vol. 46(4), pages 443-459, December.
    2. Pascal Jordan & Meike C Shedden-Mora & Bernd Löwe, 2017. "Psychometric analysis of the Generalized Anxiety Disorder scale (GAD-7) in primary care using modern item response theory," PLOS ONE, Public Library of Science, vol. 12(8), pages 1-14, August.
    3. 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.
    4. Hirotugu Akaike, 1987. "Factor analysis and AIC," Psychometrika, Springer;The Psychometric Society, vol. 52(3), pages 317-332, September.
    5. David J. Bartholomew & Panagiota Tzamourani, 1999. "The Goodness of Fit of Latent Trait Models in Attitude Measurement," Sociological Methods & Research, , vol. 27(4), pages 525-546, May.
    6. 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).
    7. Catriona Soutar & Anne P. F. Wand, 2022. "Understanding the Spectrum of Anxiety Responses to Climate Change: A Systematic Review of the Qualitative Literature," IJERPH, MDPI, vol. 19(2), pages 1-23, January.
    8. Alan E. Stewart, 2021. "Psychometric Properties of the Climate Change Worry Scale," IJERPH, MDPI, vol. 18(2), pages 1-22, January.
    Full references (including those not matched with items on IDEAS)

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