Back to Search
Start Over
Field interventions for climate change mitigation behaviors: A second-order meta-analysis.
- Source :
-
Proceedings of the National Academy of Sciences of the United States of America [Proc Natl Acad Sci U S A] 2023 Mar 28; Vol. 120 (13), pp. e2214851120. Date of Electronic Publication: 2023 Mar 21. - Publication Year :
- 2023
-
Abstract
- Behavioral change is essential to mitigate climate change. To advance current knowledge, we synthesize research on interventions aiming to promote climate change mitigation behaviors in field settings. In a preregistered second-order meta-analysis, we assess the overall effect of 10 meta-analyses, incorporating a total of 430 primary studies. In addition, we assess subgroup analyses for six types of interventions, five behaviors, and three publication bias adjustments. Results showed that climate change mitigation interventions were generally effective ( d <subscript>unadjusted</subscript> = 0.31, 95% CI [0.30, 0.32]). A follow-up analysis using only unique primary studies, adjusted for publication bias, provides a more conservative overall estimate ( d = 0.18, 95% CI [0.13, 0.24]). This translates into a mean treatment effect of 7 percentage points. Furthermore, in a subsample of adequately powered large-scale interventions ( n > 9,000, k = 32), the effect was adjusted downward to approximately 2 percentage points. This discrepancy might be because large-scale interventions often target nonvoluntary participants by less direct techniques (e.g., "home energy reports") while small-scale interventions often target voluntary participants by more direct techniques (e.g., face-to-face interactions). Subgroup analyses showed that interventions based on social comparisons or financial incentives were the most effective, while education or feedback was the least effective. These results provide a comprehensive state-of-the-art summary of climate change mitigation interventions, guiding both future research and practice.
- Subjects :
- Humans
Behavior
Climate Change
Subjects
Details
- Language :
- English
- ISSN :
- 1091-6490
- Volume :
- 120
- Issue :
- 13
- Database :
- MEDLINE
- Journal :
- Proceedings of the National Academy of Sciences of the United States of America
- Publication Type :
- Academic Journal
- Accession number :
- 36943888
- Full Text :
- https://doi.org/10.1073/pnas.2214851120