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Human values and beliefs and concern about climate change: a Bayesian longitudinal analysis

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  • Gabriele Prati

    (Università di Bologna)

  • Luca Pietrantoni

    (Università di Bologna)

  • Cinzia Albanesi

    (Università di Bologna)

Abstract

The aim of this study was to investigate the influence of human values on beliefs and concern about climate change using a longitudinal design and Bayesian analysis. A sample of 298 undergraduate/master students filled out the same questionnaire on two occasions at an interval of 2 months. The questionnaire included measures of beliefs and concern about climate change (i.e., perceived consequences, risk perception, and skepticism) and human values (i.e., the Portrait Values Questionnaire). After controlling for gender and the respective baseline score, universalism at Time 1 was associated with higher levels of perceived consequences of climate change and lower levels of climate change skepticism. Self-direction at Time 1 predicted Time 2 climate change risk perception and perceived consequences of climate change. Hedonism at Time 1 was associated with Time 2 climate change risk perception. The other human values at Time 1 were not associated with any of the measures of beliefs and concern about climate change at Time 2. The results of this study suggest that a focus on universalism and self-direction values seems to be a more successful approach to stimulate public engagement with climate change than a focus on other human values.

Suggested Citation

  • Gabriele Prati & Luca Pietrantoni & Cinzia Albanesi, 2018. "Human values and beliefs and concern about climate change: a Bayesian longitudinal analysis," Quality & Quantity: International Journal of Methodology, Springer, vol. 52(4), pages 1613-1625, July.
  • Handle: RePEc:spr:qualqt:v:52:y:2018:i:4:d:10.1007_s11135-017-0538-z
    DOI: 10.1007/s11135-017-0538-z
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    References listed on IDEAS

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    1. Anna Bluszcz, 2016. "Erratum to: Classification of the European Union member states according to the relative level of sustainable development," Quality & Quantity: International Journal of Methodology, Springer, vol. 50(6), pages 2607-2607, November.
    2. Daniel Stegmueller, 2013. "How Many Countries for Multilevel Modeling? A Comparison of Frequentist and Bayesian Approaches," American Journal of Political Science, John Wiley & Sons, vol. 57(3), pages 748-761, July.
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    1. Gabriele Prati & Iana Tzankova & Cinzia Albanesi & Elvira Cicognani, 2022. "Longitudinal Predictors of Perceived Climate Change Importance and Worry among Italian Youths: A Machine Learning Approach," Sustainability, MDPI, vol. 14(23), pages 1-19, November.
    2. Seol-A Kwon & Seoyong Kim & Jae Eun Lee, 2019. "Analyzing the Determinants of Individual Action on Climate Change by Specifying the Roles of Six Values in South Korea," Sustainability, MDPI, vol. 11(7), pages 1-24, March.
    3. Audronė Minelgaitė & Genovaitė Liobikienė, 2021. "Changes in pro-environmental behaviour and its determinants during long-term period in a transition country as Lithuania," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(11), pages 16083-16099, November.

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