Public Attitudes Toward Health Inequality: Explanatory Framings, cognitive appraisals, and the Moderating Effect of Political Orientation

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Authors: Orla , Chris Noone, Hannah J McLoughlin
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Abstract

Health inequalities are often presented alongside explanatory factors, such as income or genetics, which implicitly suggest causal explanations. These framings influence public perceptions of fairness and support for intervention. This study replicates and extends Bridger et al. (2024), who found that socioeconomic framings of life expectancy differences elicited greater moral concern than biological or lifestyle explanations. Approximately 330 population representative adults from the UK will be recruited via Prolific and randomly assigned to view graphs illustrating life expectancy differences between groups. Participants will receive one of seven explanatory framing conditions (socioeconomic factors: income, neighborhood, education, or social class; genetic factors; lifestyle factors; or no explanation). Primary outcomes assess perceived acceptability of the inequality and support for intervention. Secondary outcomes examine cognitive appraisals (malleability, inevitability, complexity) and causal attributions. This study extends the original design by measuring economic and social political orientation separately, along with more comprehensive demographic information, to examine whether individual differences moderate responses to explanatory framings. The study addresses three broad research questions: (1) How do different explanatory framings affect public acceptability of health inequality and support for intervention? (2) What cognitive mechanisms (appraisals and causal attributions) mediate these framing effects? (3) Does political orientation moderate the relationship between explanatory framings and public attitudes toward health inequality?

Fields of Study & Subjects

Public Health and Social Inequalities Health disparities and outcomes Public Health Policies and Education

Publication details

Publication date
1 January 2026
Language
EN
Document type
Preprint