ArticleJournal of health politics, policy and law2010
Images of illness: how causal claims and racial associations influence public preferences toward diabetes research spending.
Article in Journal of health politics, policy and law, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it, 35 citations in OpenAlex.
- The relationship between stigma and psychological distress among people with diabetes: a meta-analysis.BMC psychology · 2023Pooled it
- Strategic Messaging to Promote Policies that Advance Racial Equity: What Do We Know, and What Do We Need to Learn?The Milbank quarterly · 2023Review
- Personal Responsibility for Health: Exploring Together with Lay Persons.Public health ethics · 2022Article
- A Cross-Sectional Analysis of the Stigma Surrounding Type 2 Diabetes in Colombia.International journal of environmental research and public health · 2021Article
- Invited Commentary: What Social Epidemiology Brings to the Table-Reconciling Social Epidemiology and Causal Inference.American journal of epidemiology · 2020Article
- Development and early implementation of the bigger picture, a youth-targeted public health literacy campaign to prevent type 2 diabetes.Journal of health communication · 2014Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 1 country.
Funding
Abstract
Despite the salience of health disparities in media and policy discourse, little previous research has investigated if imagery associating an illness with a certain racial group influences public perceptions. This study evaluated the influence of the media's presentation of the causes of type 2 diabetes and its implicit racial associations on attitudes toward people with diabetes and preferences toward research spending. Survey participants who viewed an article on genetic causation or social determinants of diabetes were more likely to support increased government spending on research than those viewing an article with no causal language, while participants viewing an article on behavioral choices were more likely to attribute negative stereotypes to people with diabetes. Participants who viewed a photo of a black woman accompanying the article were less likely to endorse negative stereotypes than those viewing a photo of a white woman, but those who viewed a photo of a glucose-testing device expressed the lowest negative stereotypes. The effect of social determinants language was significantly different for blacks and whites, lowering stereotypes only among blacks. Emphasizing the behavioral causes of diabetes, as is common in media coverage, may perpetuate negative stereotypes. While drawing attention to the social determinants that shape these behaviors could mitigate stereotypes, this strategy is unlikely to influence the public uniformly.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.