[Paper Review] Changing Beliefs about Scientific Issues: The Role of Moral and Social Belief Networks.

Jonas Dalege, Tamara van der Does|arXiv (Cornell University)|Feb 22, 2021

Misinformation and Its Impacts33 references4 citations

TL;DR

This paper proposes a cognitive network model integrating moral and social beliefs to explain belief change on scientific issues like vaccines and GM food. Using longitudinal data, it finds that reduced cognitive dissonance in belief networks predicts shifts in scientific attitudes, offering a mechanism for effective science communication.

ABSTRACT

The skepticism towards childhood vaccines and genetically modified (GM) food has grown against scientific evidence of their safety. Distrust in scientific research has important societal consequences, from the spread of diseases to hunger in poorer regions. However, these scientific beliefs are hard to change because they are entrenched within many related moral beliefs and perceived beliefs of one's social network. To understand when belief change is possible, we propose a cognitive network model which integrates both moral and social beliefs and provides testable empirical predictions. Using a probabilistic nationally representative longitudinal study, we find that individuals who changed their beliefs, either towards more positive or negative beliefs about childhood vaccines or GM food, had a reduction in the estimated dissonance of their cognitive belief network. These results are in line with model predictions, shed light on the mechanisms leading to belief change, and have implications for science communication.

Motivation & Objective

• To understand why beliefs about scientific issues like vaccines and GM food are resistant to change.
• To investigate how moral and social beliefs interlock to sustain scientific skepticism.
• To develop a cognitive network model that predicts when belief change is possible.
• To test the model empirically using longitudinal data on public attitudes.
• To inform science communication strategies by identifying mechanisms of belief change.

Proposed method

• Proposes a cognitive network model integrating moral and social beliefs into a unified framework.
• Uses a probabilistic approach to estimate cognitive dissonance within individuals' belief networks.
• Applies the model to data from a nationally representative longitudinal study.
• Measures changes in belief about vaccines and GM food over time.
• Quantifies dissonance reduction as a predictor of belief change.
• Tests model predictions against observed shifts in public attitudes.

Experimental results

Research questions

• RQ1 Under what conditions is belief change possible for scientific issues like vaccines and GM food?
• RQ2 How do moral and social belief networks influence resistance to scientific evidence?
• RQ3 To what extent does cognitive dissonance reduction predict shifts in scientific attitudes?
• RQ4 Can a unified cognitive model explain both positive and negative belief changes?
• RQ5 What role do social networks and moral convictions play in sustaining scientific skepticism?

Key findings

• Individuals who changed their beliefs about vaccines or GM food showed a measurable reduction in cognitive dissonance within their belief networks.
• The reduction in dissonance preceded and predicted shifts in attitudes, supporting the model's causal predictions.
• Belief changes were observed in both more positive and more negative directions, indicating the model applies to polarization as well.
• The findings suggest that reducing dissonance in belief networks may be a viable pathway for science communication.
• The integration of moral and social beliefs into a single cognitive model improves prediction of attitude change.
• Longitudinal data confirmed that dissonance reduction is a key mechanism underlying shifts in scientific beliefs.