Adaptation of the Climate Anxiety Scale in Indonesian version: The sample of young adults
DOI:
https://doi.org/10.21580/pjpp.v8i2.17462Keywords:
adaptation, Climate Anxiety Scale, factor analysis, internal consistencyAbstract
The negative emotional impact of climate change has been reported in numerous studies. However, the research on the topic in Indonesia is limited, partly due to the absence of a valid scale relating to the Indonesian context. This study aims to adapt and evaluate the psychometric properties of the Climate Anxiety Scale. The adaptation of the scale into Indonesian was made concerning the International Translating Commission. The study involved 306 young people aged 18 to 35 (M= 21.01, 80.4% female) from February to June 2023. Psychometric property analysis consisted of internal consistency, Exploratory Factor Analysis (EFA), and Confirmatory Factor Analysis (CFA). The results indicate satisfactory reliability (Cronbach’s α = .91; McDonald’s ω = .91). Although most items (apart from FI5) behaved similarly to the original 2-factor structure based on EFA, they did not achieve a reasonable fit based on CFA. Therefore, the authors carefully made modifications based on modified indices of the 2-factor structure to achieve reasonable local fit measurements. The authors recommend examining the original structure using different sample categories and approaches (e.g., criterion validity) in the Indonesian sample.
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Ágoston, C., Csaba, B., Nagy, B., Kőváry, Z., Dúll, A., Rácz, J., & Demetrovics, Z. (2022). Identifying types of eco-anxiety, eco-guilt, eco-grief, and eco-coping in a climate-sensitive population: A qualitative study. International Journal of Environmental Research and Public Health, 19(4), 2461. https://doi.org/10.3390/ijerph19042461
Bartlett, M. S. (1950). Tests of significance in factor analysis. British Journal of Psychology, 3(77–85).
Berge, J. M. F. ten, & Kiers, H. A. L. (1991). A numerical approach to the approximate and the exact minimum rank of a covariance matrix. Psychometrika, 56(2), 309–315. https://doi.org/10.1007/BF02294464
Berry, H. L., Bowen, K., & Kjellstrom, T. (2010). Climate change and mental health: A causal pathways framework. International Journal of Public Health, 55(2), 123–132. https://doi.org/10.1007/s00038-009-0112-0
Bourque, F., & Willox, A. C. (2014). Climate change: The next challenge for public mental health? International Review of Psychiatry, 26(4), 415–422. https://doi.org/10.3109/09540261.2014.925851
Brauer, K., Ranger, J., & Ziegler, M. (2023). Confirmatory factor analyses in psychological test adaptation and development. Psychological Test Adaptation and Development, 4(1), 4–12. https://doi.org/10.1027/2698-1866/a000034
Brown, T. A. (2015). Confirmatory factor analysis for applied research. Guilford Press.
Cianconi, P., Betrò, S., & Janiri, L. (2020). The impact of climate change on mental health: A systematic descriptive review. Frontiers in Psychiatry, 11, 74. https://doi.org/10.3389/fpsyt.2020.00074
Clayton, S. D., & Karazsia, B. T. (2020). Development and validation of a measure of climate change anxiety. Journal of Environmental Psychology, 69, 101434. https://doi.org/10.1016/j.jenvp.2020.101434
Clayton, S. D., Pihkala, P., Wray, B., & Marks, E. (2023). Psychological and emotional responses to climate change among young people worldwide: Differences associated with gender, age, and country. Sustainability, 15(4), 3540. https://doi.org/10.3390/su15043540
Coffey, Y., Bhullar, N., Durkin, J., Islam, M. S., & Usher, K. (2021). Understanding eco-anxiety: A systematic acoping review of current literature and identified knowledge gaps. The Journal of Climate Change and Health, 3, 100047. https://doi.org/10.1016/j.joclim.2021.100047
Diffey, J., Wright, S., Uchendu, J. O., Masithi, S., Olude, A., Juma, D. O., Anya, L. H., Salami, T., Mogathala, P. R., Agarwal, H., Roh, H., Aboy, K. V., Cote, J., Saini, A., Mitchell, K., Kleczka, J., Lobner, N. G., Ialamov, L., Borbely, M., … Lawrance, E. (2022). “Not about us without us” – the feelings and hopes of climate-concerned young people around the world. International Review of Psychiatry, 34(5), 499–509. https://doi.org/10.1080/09540261.2022.2126297
Dziuban, C. D., & Shirkey, E. C. (1974). When is a correlation matrix appropriate for factor analysis? Some decision rules. Psychological Bulletin, 81(6), 358–361. https://doi.org/10.1037/h0036316
Ekström, J. (2011). On the relation between the Polychoric correlation coefficient and Spearman’s Rank correlation coefficient. UCLA Department of Statistics Papers. https://escholarship.org/uc/item/7j01t5sf
Fabrigar, L. R., Wegener, D. T., MacCallum, R. C., & Strahan, E. J. (1999). Evaluating the use of exploratory factor analysis in psychological research. Psychological Methods, 4(3), 272–299. https://doi.org/10.1037/1082-989X.4.3.272
Feather, G., & Williams, M. (2022). A psychometric evaluation of the Climate Change Anxiety Scale. PsyArXiv.
Galway, L. P., & Field, E. (2023). Climate emotions and anxiety among young people in Canada: A national survey and call to action. The Journal of Climate Change and Health, 9, 100204. https://doi.org/https://doi.org/10.1016/j.joclim.2023.100204
Hair Jr, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2009). Multivariate data analysis (7th ed.). Prentice Hall International.
Hickman, C., Marks, E., Pihkala, P., Clayton, S., Lewandowski, R. E., Mayall, E. E., Wray, B., Mellor, C., & van Susteren, L. (2021). Climate anxiety in children and young people and their beliefs about government responses to climate change: A global survey. The Lancet Planetary Health, 5(12), e863–e873. https://doi.org/10.1016/S2542-5196(21)00278-3
Hogg, T. L., Stanley, S. K., & O’Brien, L. V. (2023). Synthesising psychometric evidence for the Climate Anxiety Scale and Hogg Eco-Anxiety Scale. Journal of Environmental Psychology, 88, 102003. https://doi.org/10.1016/j.jenvp.2023.102003
Hogg, T. L., Stanley, S. K., O’Brien, L. V., Wilson, M. S., & Watsford, C. R. (2021). The Hogg Eco-Anxiety Scale: Development and validation of a multidimensional scale. Global Environmental Change, 71, 102391. https://doi.org/10.1016/j.gloenvcha.2021.102391
Horn, J. L. (1965). A rationale and test for the number of factors in factor analysis. Psychometrika, 30(2), 179–185. https://doi.org/10.1007/BF02289447
Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55. https://doi.org/10.1080/10705519909540118
International Test Commission. (2017). ITC guidelines for translating and adapting tests (2nd ed.). InTestCom.org. https://www.intestcom.org/files/guideline_test_adaptation_2ed.pdf
Jang, S. J., Chung, S. J., & Lee, H. (2023). Validation of the Climate Change Anxiety Scale for Korean adults. Perspectives in Psychiatric Care, 2023, 1–8. https://doi.org/10.1155/2023/9718834
Kaiser, H. F., & Rice, J. (1974). Little Jiffy, Mark IV. Educational and Psychological Measurement, 34(1), 111–117. https://doi.org/10.1177/001316447403400115
Kim, H.-Y. (2013). Statistical notes for clinical researchers: Assessing normal distribution (2) using skewness and kurtosis. Restorative Dentistry & Endodontics, 38(1), 52. https://doi.org/10.5395/rde.2013.38.1.52
Kline, R. B. (2023). Principles and practice of structural equation modeling. Guilford Press.
Larionow, P., Sołtys, M., Izdebski, P., Mudło-Głagolska, K., Golonka, J., Demski, M., & Rosińska, M. (2022). Climate change anxiety assessment: The Psychometric properties of the Polish version of the Climate Anxiety Scale. Frontiers in Psychology, 13. https://doi.org/10.3389/fpsyg.2022.870392
Leiserowitz, A., Carman, J., Buttermore, N., Wang, X., Rosenthal, S., Marlon, J., & Mulcahy, K. (2021). International public opinion on climate change. Yale Program on Climate Change Communication and Facebook Data for Good.
Li, C.-H. (2016). Confirmatory factor analysis with ordinal data: Comparing robust maximum likelihood and diagonally weighted least squares. Behavior Research Methods, 48(3), 936–949. https://doi.org/10.3758/s13428-015-0619-7
Lloret, S., Ferreres, A., Hernández, A., & Tomás, I. (2017). El análisis factorial exploratorio de los ítems: Análisis guiado según los datos empíricos y el software. Anales de Psicología, 33(2), 417. https://doi.org/10.6018/analesps.33.2.270211
Lorenzo-Seva, U., & Ferrando, P. J. (2006). Factor: A computer program to fit the exploratory factor analysis model. Behavior Research Methods, 38(1), 88–91. https://doi.org/10.3758/BF03192753
Mîndrilă, D. (2010). Maximum Likelihood (ML) and Diagonally Weighted Least Squares (DWLS) estimation procedures: A comparison of estimation bias with ordinal and multivariate non-normal data. International Journal for Digital Society, 1(1), 60–66. https://doi.org/10.20533/ijds.2040.2570.2010.0010
Mouguiama-Daouda, C., Blanchard, M. A., Coussement, C., & Heeren, A. (2022). On the measurement of climate change anxiety: French validation of the Climate Anxiety Scale. Psychologica Belgica, 62(1), 123. https://doi.org/10.5334/pb.1137
Muthén, L. K., & Muthén, B. O. (1998). Mplus user’s guide, (8th ed.). Muthén & Muthén.
Muthén, L. K., & Muthén, B. O. (2019). Mplus [Computer software]. Muthén Muthén.
Norman, G. R., & Streiner, D. L. (1994). Biostatistics: The bare essentials. Mosby.
Nunnally, J., & Bernstein, I. (1994). Psychometric theory (3rd ed.). McGraw Hill.
Nye, C. D., & Drasgow, F. (2011). Assessing goodness of fit: Simple rules of thumb simply do not work. Organizational Research Methods, 14(3), 548–570. https://doi.org/10.1177/1094428110368562
Ogunbode, C. A., Doran, R., Hanss, D., Ojala, M., Salmela-Aro, K., van den Broek, K. L., Bhullar, N., Aquino, S. D., Marot, T., Schermer, J. A., Wlodarczyk, A., Lu, S., Jiang, F., Maran, D. A., Yadav, R., Ardi, R., Chegeni, R., Ghanbarian, E., Zand, S., … Karasu, M. (2022). Climate anxiety, wellbeing and pro-environmental action: Correlates of negative emotional responses to climate change in 32 countries. Journal of Environmental Psychology, 84, 101887. https://doi.org/10.1016/j.jenvp.2022.101887
Ogunbode, C. A., Pallesen, S., Böhm, G., Doran, R., Bhullar, N., Aquino, S., Marot, T., Schermer, J. A., Wlodarczyk, A., Lu, S., Jiang, F., Salmela-Aro, K., Hanss, D., Maran, D. A., Ardi, R., Chegeni, R., Tahir, H., Ghanbarian, E., Park, J., … Lomas, M. J. (2023). Negative emotions about climate change are related to insomnia symptoms and mental health: Cross-sectional evidence from 25 countries. Current Psychology, 42(2), 845–854. https://doi.org/10.1007/s12144-021-01385-4
Posit Team. (2023). RStudio: Integrated development environment for R [Computer software]. Posit Software, PBC.
Price, P. C., Jhangiani, R. S., & Chiang, I.-C. A. (2015). Reliability and validity of measurement. In Research Methods in Psychology. Pressbooks.
R Core Team. (2023). R: A language and environment for statistical computing. R Foundation for Statistical Computing.
Shapiro, A., & ten Berge, J. M. F. (2002). Statistical inference of minimum rank factor analysis. Psychometrika, 67(1), 79–94. https://doi.org/10.1007/BF02294710
Simon, P. D., Pakingan, K. A., & Aruta, J. J. B. R. (2022). Measurement of climate change anxiety and its mediating effect between experience of climate change and mitigation actions of Filipino youth. Educational and Developmental Psychologist, 39(1), 17–27. https://doi.org/10.1080/20590776.2022.2037390
Stewart, A. E. (2021). Psychometric properties of the Climate Change Worry Scale. International Journal of Environmental Research and Public Health, 18(2), 494. https://doi.org/10.3390/ijerph18020494
The Jamovi Project. (2023). Jamovi-Open statistical software for the dekstop and cloud. The Jamovi Project.
Timmerman, M. E., & Lorenzo-Seva, U. (2011). Dimensionality assessment of ordered polytomous items with parallel analysis. Psychological Methods, 16(2), 209–220. https://doi.org/10.1037/a0023353
Usher, K., Durkin, J., & Bhullar, N. (2019). Eco‐anxiety: How thinking about climate change‐related environmental decline is affecting our mental health. International Journal of Mental Health Nursing, 28(6), 1233–1234. https://doi.org/10.1111/inm.12673
Uzun, K., Öztürk, A. F., Karaman, M., Cebeci, F., Altin, M. O., Arici, A., & Artan, T. (2022). Adaptation of the Eco-Anxiety Scale to Turkish: A validity and reliability study. Archives of Health Science and Research, 9(2), 110–115. https://doi.org/10.54614/ArcHealthSciRes.2022.21151
van Zomeren, M., Saguy, T., & Schellhaas, F. M. H. (2013). Believing in “making a difference” to collective efforts: Participative efficacy beliefs as a unique predictor of collective action. Group Processes & Intergroup Relations, 16(5), 618–634. https://doi.org/10.1177/1368430212467476
Watkins, M. W. (2018). Exploratory factor analysis: A guide to best practice. Journal of Black Psychology, 44(3), 219–246. https://doi.org/10.1177/0095798418771807
Wu, J., Snell, G., & Samji, H. (2020). Climate anxiety in young people: A call to action. The Lancet Planetary Health, 4(10), e435–e436. https://doi.org/10.1016/S2542-5196(20)30223-0
Wullenkord, M. C., Tröger, J., Hamann, K. R. S., Loy, L. S., & Reese, G. (2021). Anxiety and climate change: A validation of the Climate Anxiety Scale in a German-speaking quota sample and an investigation of psychological correlates. Climatic Change, 168(3–4), 20. https://doi.org/10.1007/s10584-021-03234-6
Zwick, W. R., & Velicer, W. F. (1986). Comparison of five rules for determining the number of components to retain. Psychological Bulletin, 99(3), 432–442. https://doi.org/10.1037/0033-2909.99.3.432
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