ArticlePNAS nexus2024
Using survey experiment pretesting to support future pandemic response.
Article in PNAS nexus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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
2 citing papers in PubMed.
- A Web-Based Cancer Prevention Intervention for Rural Emerging Adults: Mixed Methods Development and Pilot-Testing Study.Journal of medical Internet research · 2026Trial
- Impact of COVID-19 lived experiences on future influenza pandemic worry: a cross-sectional survey in China.BMC public health · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The world could witness another pandemic on the scale of COVID-19 in the future, prompting calls for research into how social and behavioral science can better contribute to pandemic response, especially regarding public engagement and communication. Here, we conduct a cost-effectiveness analysis of a familiar tool from social and behavioral science that could potentially increase the impact of public communication: survey experiments. Specifically, we analyze whether a public health campaign that pays for a survey experiment to pretest and choose between different messages for its public outreach has greater impact in expectation than an otherwise-identical campaign that does not. The main results of our analysis are 3-fold. First, we show that the benefit of such pretesting depends heavily on the values of several key parameters. Second, via simulations and an evidence review, we find that a campaign that allocates some of its budget to pretesting could plausibly increase its expected impact; that is, we estimate that pretesting is cost-effective. Third, we find pretesting has potentially powerful returns to scale; for well-resourced campaigns, we estimate pretesting is robustly cost-effective, a finding that emphasizes the benefit of public health campaigns sharing resources and findings. Our results suggest survey experiment pretesting could cost-effectively increase the impact of public health campaigns in a pandemic, have implications for practice, and establish a research agenda to advance knowledge in this space.
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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.