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Facing the pandemic with trust in science

Author

Listed:
  • Justin Sulik

    (Ludwig Maximilian University of Munich)

  • Ophelia Deroy

    (Ludwig Maximilian University of Munich
    University of London)

  • Guillaume Dezecache

    (CNRS)

  • Martha Newson

    (University of Kent
    University of Oxford)

  • Yi Zhao

    (Indiana University)

  • Marwa El Zein

    (University College London
    Max Planck Centre for Human Development)

  • Bahar Tunçgenç

    (University of Oxford
    University of Nottingham)

Abstract

How essential is trust in science to prevent the spread of COVID-19? People who trust in science are reportedly more likely to comply with official guidelines, implying that higher levels of adherence could be achieved by improving trust in science. However, analysis of a global dataset (n = 4341) suggests otherwise. Trust in science had a small, indirect effect on adherence to the rules. Nonetheless, it predicted people’s approval of prevention measures such as social distancing, and bridged political ideology and approval of the measures (conservatives trusted science less and in turn approved of the measures less). These effects were stronger in the USA than in other countries. Even though any increase in trust in science is unlikely to yield strong behavioural changes, given its relationships with both ideology and individuals’ attitudes to the measures, trust in science may be leveraged to yield longer-term sustainable social benefits.

Suggested Citation

  • Justin Sulik & Ophelia Deroy & Guillaume Dezecache & Martha Newson & Yi Zhao & Marwa El Zein & Bahar Tunçgenç, 2021. "Facing the pandemic with trust in science," Palgrave Communications, Palgrave Macmillan, vol. 8(1), pages 1-10, December.
    • Handle: RePEc:pal:palcom:v:8:y:2021:i:1:d:10.1057_s41599-021-00982-9
    DOI: 10.1057/s41599-021-00982-9
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    References listed on IDEAS

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    Cited by:

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    2. Anders Brostrom & Cornelia Lawson & Mabel Sanchez Barrioluengo, 2024. "Are Scientists Perceived as Credible Experts?," MIOIR Working Paper Series 2024-06, The Manchester Institute of Innovation Research (MIoIR), The University of Manchester.
    3. Yating Wen & Xiaodong Zhao & Yuqi Zang & Xingguo Li, 2024. "How the crisis of trust in experts occurs on social media in China? Multiple-case analysis based on data mining," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-18, December.

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