ArticleHealth communication2021
Rating the Valence of Media Content about Electronic Cigarettes Using Crowdsourcing: Testing Rater Instructions and Estimating the Optimal Number of Raters.
Article in Health communication, 2021. 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.
- Valence of Media Coverage About Electronic Cigarettes and Other Tobacco Products From 2014 to 2017: Evidence From Automated Content Analysis.Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Electronic cigarettes (e-cigarettes) are a controversial public health topic due to their increasing popularity among youth and the uncertainty about their risks and benefits. Researchers have started to assess the valence of media content about e-cigarette use, mostly using expert coding. The current study aims to offer a methodological framework and guideline when using crowdsourcing to rate the valence of e-cigarette media content. Specifically, we present (1) an experiment to determine rating instructions that would result in reliable valence ratings and (2) an analysis to identify the optimal number of raters needed to replicate these ratings. Specifically, we compared ratings produced by crowdsourced raters instructed to rate from several different perspectives (e.g., objective vs. subjective) and determined the instructions that led to reliable ratings. We then used bootstrapping methods and a set of criteria to identify the minimum number of raters needed to replicate these ratings. Results suggested that when rating e-cigarette valence, instructing raters to rate from their own subjective perspective produced reliable results, and nine raters were deemed the optimal number of raters. We expect these findings to inform future content analyses of e-cigarette valence. The study procedures can be applied to crowdsourced content analyses of other health-related media content to determine appropriate rating instructions and the number of raters.
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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.