ArticleThe patient2021
Public Preferences for Government Response Policies on Outbreak Control.
Article in The patient, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed.
- Preferences for the Societal Impacts of a Pandemic when it Transitions into an Endemic: A Discrete Choice Experiment.The patient · 2025Article
- Stepping into the shoes of the policy maker: Results of a Participatory Value Evaluation for the Dutch long term COVID-19 strategy.Social science & medicine (1982) · 2022Article
- Using Societal Values to Inform Public Health Policy During the COVID-19 Pandemic: The Role of Health Preference Research.The patient · 2021Article
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
Abstract
objectiveThe aim of this study was to assess the extent to which public support for outbreak containment policies varies with respect to the severity of an infectious disease outbreak.
methodsA web-enabled survey was administered to 1017 residents of Singapore during the coronavirus disease 2019 (COVID-19) pandemic, and was quota-sampled based on age, sex, and ethnicity. A fractional-factorial design was used to create hypothetical outbreak vignettes characterised by morbidity and fatality rates, and local and global spread of an infectious disease. Each respondent was asked to indicate which response policies (among five policies restricting local movement and four border control policies) they would support in five randomly assigned vignettes. Binomial logistic regressions were used to predict the probabilities of support as a function of outbreak attributes, personal characteristics, and perceived policy effectiveness.
resultsLikelihood of support varied across government response policies but was generally higher for border control policies compared with internal policies. The fatality rate was the most important factor for internal policies, while the degree of global spread was the most important for border control policies. In general, individuals who were less healthy, had higher-income, and were older were more likely to support these policies. Perceived effectiveness of a policy was a consistent and positive predictor of public support.
conclusionsOur findings suggest that campaigns to promote public support should be designed specifically to each policy and tailored to different segments of the population. They should also be adapted based on the evolving conditions of the outbreak in order to receive continued public support.
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.