Environmental Behavior

Predicting adolescents’ environmental action: From individual to national-level factors using an explainable machine learning approach
As a key force in future environmental actions, youth play a crucial role in driving societal transformation. However, the factors influencing youth environmental actions have not been fully validated, and the role of national-level influences is often overlooked. This study aims to identify the factors that are associated with adolescents’ public-sphere and private-sphere environmental actions. Unlike prior studies, which typically use single-level analyses, we simultaneously examine individual, school, and national factors to capture the often-overlooked national context. Using PISA-2018 data on 420,339 adolescents from 66 countries, we used LightGBM and XGBoost to build predictive models. Shapley Additive Explanations (SHAP) were then applied to detect non-linear threshold effects and to quantify each feature’s contribution to environmental action. Results indicate that individual-level factors, such as environmental attitudes, the discussion of international events in school, and critical thinking, are significantly associated with adolescents’ private-sphere environmental actions. Conversely, national-level factors, such as Sustainable Development Goal (SDG) performance and country vulnerability, play a particularly strong role in shaping public-sphere environmental actions. This study underscores the importance of incorporating national-level factors, which have often been under-emphasized in research on youth environmental behavior.
Environmental Education in Low-income and Middle-income Countries: A Systematic Review and Meta-Analysis
Behavior change is a critical part of effectively addressing climate change. Environmental education stands out as a sustainable long-term strategy for mitigating its impacts. Despite the growing implementation of environmental education in low- and middle-income countries (LMICs), comprehensive data on its successes or shortcomings remain relatively scarce compared to the wealth of evidence available from non-LMIC contexts. This study performed a robust variance estimation meta-analysis on 187 independent effect sizes, involving 34,283 participants. The results indicated a positive and significant effect of environmental education in LMICs (Hedges’ g = 1.11, 95% CI [0.87, 1.35]). Specifically, participation in environmental education programmers was associated with increased environmental knowledge (Hedges’ g = 1.35, 95% CI [1.02, 1.69]), environmental attitudes (Hedges’ g = 0.94, 95% CI [0.56, 1.32]), and environmental behaviors (Hedges’ g = 0.68, 95% CI [0.46, 0.90]). Moderator analyses revealed that outcomes differed by intervention length, measurement time, age, and national development level, while study design, education level, intervention type, and gender did not show significant differences in outcomes. This study underscores the importance of implementing environmental education in LMICs, providing valuable insights for future research and practical applications in these contexts.