Covid-19

Academic Research

  • Journal Article

    Online Searches to Evaluate Misinformation Can Increase its Perceived Veracity

    Nature, 2024

    View Article View abstract

    Considerable scholarly attention has been paid to understanding belief in online misinformation, with a particular focus on social networks. However, the dominant role of search engines in the information environment remains underexplored, even though the use of online search to evaluate the veracity of information is a central component of media literacy interventions. Although conventional wisdom suggests that searching online when evaluating misinformation would reduce belief in it, there is little empirical evidence to evaluate this claim. Here, across five experiments, we present consistent evidence that online search to evaluate the truthfulness of false news articles actually increases the probability of believing them. To shed light on this relationship, we combine survey data with digital trace data collected using a custom browser extension. We find that the search effect is concentrated among individuals for whom search engines return lower-quality information. Our results indicate that those who search online to evaluate misinformation risk falling into data voids, or informational spaces in which there is corroborating evidence from low-quality sources. We also find consistent evidence that searching online to evaluate news increases belief in true news from low-quality sources, but inconsistent evidence that it increases belief in true news from mainstream sources. Our findings highlight the need for media literacy programmes to ground their recommendations in empirically tested strategies and for search engines to invest in solutions to the challenges identified here.

    Date Posted

    Dec 20, 2023

  • Journal Article

    A Synthesis of Evidence for Policy from Behavioural Science During COVID-19

    • Kai Ruggeri, 
    • Friederike Stock, 
    • S. Alexander Haslam, 
    • Valerio Capraro, 
    • Paulo Boggio, 
    • Naomi Ellemers, 
    • Aleksandra Cichocka, 
    • Karen M. Douglas, 
    • David G. Rand, 
    • Sander van der Linden, 
    • Mina Cikara, 
    • Eli J. Finkel, 
    • James N. Druckman, 
    • Michael J. A. Wohl, 
    • Richard E. Petty, 
    • Joshua A. Tucker
    • Azim Shariff, 
    • Michele Gelfand, 
    • Dominic Packer, 
    • Jolanda Jetten, 
    • Paul A. M. Van Lange, 
    • Gordon Pennycook, 
    • Ellen Peters, 
    • Katherine Baicker, 
    • Alia Crum, 
    • Kim A. Weeden, 
    • Lucy Napper, 
    • Nassim Tabri, 
    • Jamil Zaki, 
    • Linda Skitka, 
    • Shinobu Kitayama, 
    • Dean Mobbs, 
    • Cass R. Sunstein, 
    • Sarah Ashcroft-Jones, 
    • Anna Louise Todsen, 
    • Ali Hajian, 
    • Sanne Verra, 
    • Vanessa Buehler, 
    • Maja Friedemann, 
    • Marlene Hecht, 
    • Rayyan S. Mobarak, 
    • Ralitsa Karakasheva, 
    • Markus R. Tünte, 
    • Siu Kit Yeung, 
    • R. Shayna Rosenbaum, 
    • Žan Lep, 
    • Yuki Yamada, 
    • Sa-kiera Tiarra Jolynn Hudson, 
    • Lucía Macchia, 
    • Irina Soboleva, 
    • Eugen Dimant, 
    • Sandra J. Geiger, 
    • Hannes Jarke, 
    • Tobias Wingen, 
    • Jana Berkessel, 
    • Silvana Mareva, 
    • Lucy McGill, 
    • Francesca Papa, 
    • Bojana Većkalov, 
    • Zeina Afif, 
    • Eike K. Buabang, 
    • Marna Landman, 
    • Felice Tavera, 
    • Jack L. Andrews, 
    • Aslı Bursalıoğlu, 
    • Zorana Zupan, 
    • Lisa Wagner, 
    • Joaquin Navajas, 
    • Marek Vranka, 
    • David Kasdan, 
    • Patricia Chen, 
    • Kathleen R. Hudson, 
    • Lindsay M. Novak, 
    • Paul Teas, 
    • Nikolay R. Rachev, 
    • Matteo M. Galizzi, 
    • Katherine L. Milkman, 
    • Marija Petrović, 
    • Jay J. Van Bavel
    • Robb Willer

    Nature, 2023

    View Article View abstract

    Scientific evidence regularly guides policy decisions, with behavioural science increasingly part of this process. In April 2020, an influential paper proposed 19 policy recommendations (‘claims’) detailing how evidence from behavioural science could contribute to efforts to reduce impacts and end the COVID-19 pandemic. Here we assess 747 pandemic-related research articles that empirically investigated those claims. We report the scale of evidence and whether evidence supports them to indicate applicability for policymaking. Two independent teams, involving 72 reviewers, found evidence for 18 of 19 claims, with both teams finding evidence supporting 16 (89%) of those 18 claims. The strongest evidence supported claims that anticipated culture, polarization and misinformation would be associated with policy effectiveness. Claims suggesting trusted leaders and positive social norms increased adherence to behavioural interventions also had strong empirical support, as did appealing to social consensus or bipartisan agreement. Targeted language in messaging yielded mixed effects and there were no effects for highlighting individual benefits or protecting others. No available evidence existed to assess any distinct differences in effects between using the terms ‘physical distancing’ and ‘social distancing’. Analysis of 463 papers containing data showed generally large samples; 418 involved human participants with a mean of 16,848 (median of 1,699). That statistical power underscored improved suitability of behavioural science research for informing policy decisions. Furthermore, by implementing a standardized approach to evidence selection and synthesis, we amplify broader implications for advancing scientific evidence in policy formulation and prioritization.

    Date Posted

    Dec 13, 2023

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