Comparative Analysis of the Application of Behavioural Insights of 33 Worldwide Governments on the Landing Pages of their COVID-19 Official Websites and their Impact on the Growth Scale of the Pandemic

This article has been Reviewed by the following groups

Read the full article See related articles

Abstract

The COVID-19 crisis has seen over a third of the world population locked down and this article has sought to understand human behaviour in response to a historical and unprecedented global pandemic. Through the analysis 18 behavioural mechanisms present on the landing pages of the websites of 33 institutional governments from March 1st til May 1st 2020 compared to the WHO data on the number of COVID-19 cases and deaths per million for each country, the authors show that a behavioural consensus was observed across all 33 countries and that Individual and Social nudges had no impact. Whilst the decisions in essentially every country on Earth, were taken with the same aim: to limit population movements and social life, two aggravating factors of the spread of the virus, only the environmental nudges effectively helped slow the virus growth scale. The authors explain the rationale behind these results and suggest that people seek information beyond governmental websites that they generally mistrust. They further suggest using Scientists as role models to encourage governmental website's traffic and designing recursive nudges to increase the impact of individual and social interventions. Together with the new phases of the spread of the virus will come new rules and guidance. Public health policies need to address behavioural change of the population on a global scale in a more targeted manner and it is hoped that this paper will provide some insight on how to do so.

Article activity feed

  1. SciScore for 10.1101/2020.05.15.20103424: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    No key resources detected.


    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).


    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.


    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


    Results from JetFighter: We did not find any issues relating to colormaps.


    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.