Department of Psychology, Faculty of Education, Universitas Negeri Surabaya, Surabaya - Indonesia
ORCID: https://orcid.org/0000-0002-6923-883X
Google Scholar:
https://scholar.google.com/citations?user=ko5CP-0AAAAJ&hl=en
Adaptation of the Climate Anxiety Scale in Indonesian version: The sample of young adults
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 É = .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.
Keywords: adaptation; Climate Anxiety Scale; factor analysis; internal consistency
- ÃÂgoston, 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 ÃÂtems: Análisis guiado según los datos empÃÂricos y el software. Anales de PsicologÃÂa, 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). Ecoâ€Âanxiety: How thinking about climate changeâ€Ârelated 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
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.