ArticlePloS one2018
Choosing the perfect shot - The loaded narrative of imagery in online news coverage of vaccines.
Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- The Effect of Science-Related Populism on Vaccination Attitudes and Decisions.Journal of behavioral medicine · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Images in health communication have been shown to affect perspectives and attitudes towards health issues including vaccination. We seek to quantify the frequency of images used in online news coverage of vaccines that may convey varying sentiments about vaccination. To capture a breadth of vaccine-related news coverage, including international sources, we searched the following terms in Google News Archives: "autism and vaccine", "flu and vaccine", and "measles and Disneyland". We developed a coding tool that classified images as negative (eg, screaming child), positive (eg, happy child), neutral (eg, vaccine vial), or irrelevant (eg, picture of journalist). All images were coded independently by two researchers and discussed for consensus. We analyzed 734 images. Of the images which featured vaccines and/or a medical encounter (322), 28% had negative features and 30% had positive features. The remaining 137 images (43%) were neutral. There was no statistically significant difference between proportions of negative and positive imagery for each pair of search terms, which may be a reflection of random image selection. Ultimately, nearly one in eight images included in vaccine-related news coverage contains negative features which may be selected without careful consideration of the potential negative impact on public health initiatives regarding vaccination.
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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.