Factors Predicting Public Perceptions of Nuclear Energy

Presentation on paper by Ho et al. 2019

1. Science Literacy or Value Predisposition? A MetaAnalysis of Factors Predicting Public Perceptions of Benefits, Risks, and Acceptance of Nuclear Energy Shirley S. Ho, Alisius D. Leong, Jiemin Looi , Liang Chen, Natalie Pang & Edson Tandoc Jr. 2019 Rubens Yanes

2.  The study seeks to identify and measure the magnitude of the key determinants of public perceptions of (a) benefits, (b) risks, and (c) acceptance of nuclear energy, across different countries and different time periods

3. Trust Knowledge Benefit Perception

4. Trust Knowledge Sex Age Education Income Public Engagement Benefit Perception Risk Perception

5. Trust Knowledge Sex Age Education Income Public Engagement Benefit Perception Risk Perception Public Acceptance Cost Perception

6. methodology They gathered 34 studies, which represented a total sample of 32,938 participants and produced 129 independent correlations. Keywords: “Nuclear” or “Nuclear plant” or “Nuclear power plant”… Databases: PsycINFO, MEDLINE, Communication & Mass Media Complete, EBSCO, Educational Resources Information Center, Web of Science Direct, PubMed, and Nursing & Allied Health Source Stats: sample sizes, means, correlations, odds ratios, and standardized regression coefficient ( β) Comprehensive Meta-Analysis 3.0 software

7.       . . . r Pearson effect Small .10–.23 Medium .24–.36 Large .37– metaanalysis

8. Trust Knowledge Benefit Perception Risk Perception Public Acceptance +

9. Trust Knowledge Sex Age Education Income Public Engagement Benefit Perception Risk Perception Public Acceptance - + - - +

10. Trust Knowledge Sex Age Education Income Public Engagement Benefit Perception Risk Perception Public Acceptance - + + + - Cost Perception -

11. Cohen’s r effect Small .10–.23 Medium .24–.36 Large .37– HETEROGENEITY

12. 17 before Fukushima 17 after Fuskushima moderators

13. STEPS FOR METANALYSIS  Define inclusión criteria based on the theortical or empirical guidelines Indentify studies to be included in the metanalysis Developing a coding schema in roder to recode the appropiate elements from each study  Calculate effect sizes for each study by transforming individual study statistics into a common effect size metric D- effect : means R- effect – effect size & direction Odds ratio – when dealing with discontinuous variables Testing homogeneity of effect size across studies Hedges Q Test and I 2 Cochran test