Reliability generalization meta-analysis of the Climate Change Worry Scale.

Climate change worry is an increasingly critical issue in eco-psychology literature. A commonly used instrument for measuring this construct is the Climate Change Worry Scale (CCWS), developed by Stewart. This Likert-type scale assesses individuals' climate change worry through 10 items clustered under a single factor. It has been adapted for multiple cultures and utilized in numerous studies conducted across various countries. Nevertheless, no study has synthesized the reliability values obtained from individual studies for the scale. The purpose of the current meta-analysis was to perform a reliability generalization for the CCWS. To this end, an exhaustive literature search was conducted from July 14 to November 17, 2024, in the EBSCO, ERIC, Taylor & Francis, PubMed, and Web of Science databases, as well as Google Scholar, using the keyword "Climate Change Worry Scale." After scrutinizing the identified studies for duplicates and applying inclusion and exclusion criteria, the research focused on the 40 Cronbach's alpha coefficients acquired from 37 papers. The results of the analysis, which involved running the random effects model and the Bonnet transformation, indicated that the pooled Cronbach's alpha was 0.932 (95% CI = 0.919-0.942). The results of the moderator analysis revealed that the sample descriptors and study characteristics included in the meta-analysis did not significantly affect the reliability estimates. Accordingly, the CCWS was found to be an instrument that produces highly reliable measurements regardless of factors such as region, language, participants' age, and the total number of items answered during administration. Finally, the reliability induction rate was determined to be 29.41%. However, the high heterogeneity observed among the reliability estimates of the primary studies exposed the limitations of generalizing the reliability of CCWS scores across different populations and research conditions. This situation also emphasized the importance of providing detailed information about the scale's sample demographics and administration conditions when reporting reliability.