ArticleEpidemiology and infection2022
Trust in the scientific research community predicts intent to comply with COVID-19 prevention measures: An analysis of a large-scale international survey dataset.
Article in Epidemiology and infection, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Using Normative Language When Describing Scientific Findings: Randomized Controlled Trial of Effects on Trust and Credibility.Journal of medical Internet research · 2023Trial
- A Method to Explore the Best Mixed-Effects Model in a Data-Driven Manner with Multiprocessing: Applications in Public Health Research.European journal of investigation in health, psychology and education · 2024Article
- Exploring Attitudes Toward "Sugar Relationships" Across 87 Countries: A Global Perspective on Exchanges of Resources for Sex and Companionship.Archives of sexual behavior · 2024Article
- Article
- Using the diffusion of innovations theory to understand factors associated with COVID-19 vaccination among tobacco users.PloS one · 2024Article
- A Big Data and FRAM-Based Model for Epidemic Risk Analysis of Infectious Diseases.Risk management and healthcare policy · 2024Article
- Cross-language validation of COVID-19 Compliance Scale in 28 languages.Epidemiology and infection · 2023Article
- Acceptance of the COVID-19 vaccine based on the health belief model: a multicenter national survey among medical care workers in China.Human vaccines & immunotherapeutics · 2022Article
- Validity testing of the conspiratorial thinking and anti-expert sentiment scales during the COVID-19 pandemic across 24 languages from a large-scale global dataset.Epidemiology and infection · 2022Article
- Using Normative Language When Describing Scientific Findings: Protocol for a Randomized Controlled Trial of Effects on Trust and Credibility.JMIR research protocols · 2022Article
Corrections and comments
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Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In the present study, I explored the relationship between people's trust in different agents related to the prevention of the spread of coronavirus disease 2019 (COVID-19) and their compliance with pharmaceutical and non-pharmaceutical preventive measures. The COVIDiSTRESSII Global Survey dataset, which was collected from international samples, was analysed to examine the aforementioned relationship across different countries. For data-driven exploration, network analysis and Bayesian generalised linear model (GLM) analysis were performed. The result from network analysis demonstrated that trust in the scientific research community was most central in the network of trust and compliance. In addition, the outcome from Bayesian GLM analysis indicated that the same factor, trust in the scientific research community, was most fundamental in predicting participants' intent to comply with both pharmaceutical and non-pharmaceutical preventive measures. I briefly discussed the implications of the findings, the importance of trust in the scientific research community in explaining people's compliance with a measure to prevent the spread of COVID-19.
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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.