A manifesto for applying behavioural science

Hallsworth, Michael

doi:10.1038/s41562-023-01555-3

Cited by 84 publications

(43 citation statements)

References 160 publications

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“…This is in line with the finding in Dai et al (2021) 20 that text reminders with the "claim your dose" language more effectively increased initial COVID-19 vaccinations than basic reminders without this language. 2 Notably, the ownership effect seems to be driven by text messages containing just the link to a specific pharmacy, which is consistent with the aforementioned observation in the third RCT where reminders with the narrow link outperformed reminders with the broad link.…”

Section: Second Rct and Companion Online Studiessupporting

confidence: 78%

“…Despite this progress, critiques have emerged regarding its ability to have a meaningful impact and reach scale, leading prominent figures in academia and policymaking to argue that further development is necessary for behavioral science to effectively influence policy and address the significant challenges facing our world today 3,4 . To identify behavioral interventions that can change consequential behaviors and be scaled up to a variety of settings, scientists, practitioners, and funders need concerted efforts to develop a nuanced understanding of whether and when the evidence they rely on is sound and transferrable across contexts 2 .…”

Section: Discussion and Implications For Policymentioning

confidence: 99%

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mentioning

confidence: 99%

“…Filling in this knowledge gap is valuable because numerous policy challenges, such as promoting annual preventive screenings or tax filing, require individuals to regularly adopt the encouraged behavior. When tackling these challenges with individual-level interventions, policymakers may benefit from knowing whether an intervention that works under some circumstances remains effective if deployed again when the context evolves 2 .…”

mentioning

confidence: 99%

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Field Tested: Assessing the Transferability of Behavioral Interventions

Saccardo

Dai

Han

et al. 2023

Preprint

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Applied behavioral science has grown rapidly in the past few decades as organizations and governments seek to incorporate research on human behavior into policy decisions1. At the same time, there is a growing recognition of the need to examine the robustness of empirical findings and their transferability to consequential behaviors2,3,4. Here, focusing on an important policy domain—COVID-19 booster uptake—we investigate the transferability of findings a) from prediction surveys and hypothetical experiments to field settings; and b) from one field context at one point in time to another after evolving circumstances. Across three preregistered randomized controlled trials (RCTs, total N=317,175), we tested text-based interventions that either were expected to work by behavioral scientists and laypeople (RCT1), successfully elevated vaccination intentions in online studies (RCT1 and RCT2), or effectively increased vaccination rates in prior field work (RCT3). Our research highlights the importance of field-testing interventions, as findings based on predictions and intentions fail to transfer to our real-world setting. We also find that despite repeated exposure to COVID-19 messaging in our population, reminders and psychological ownership framing still increased booster uptake. These findings have theoretical and practical implications, as they can contribute to refining both theories of behavior change and experts’ predictions about what interventions are likely to have an impact in the field.

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Section: Second Rct and Companion Online Studiessupporting

confidence: 78%

Section: Discussion and Implications For Policymentioning

confidence: 99%

“…

…”

mentioning

confidence: 99%

mentioning

confidence: 99%

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Field Tested: Assessing the Transferability of Behavioral Interventions

Saccardo

Dai

Han

et al. 2023

Preprint

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“…In the same way that urging someone to save more for retirement can lead them to have less money to spend on gifts for their children, urging someone to pivot from sunk costs might lead them to be trusted less by their peers. While the primary goal of such efforts will likely remain behavior change, choice architects must consider how shifting behavior might also inadvertently shift interpersonal variables, as well (c.f., Hallsworth, 2023).…”

Section: A Canonical Puzzles In Judgment and Decision Makingmentioning

confidence: 99%

Reputational Rationality Theory

Dorison¹

2023

Preprint

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Traditionally, research on human judgment and decision making draws on cognitive psychology to identify deviations from normative standards of how decisions ought to be made. These deviations are commonly considered irrational errors and biases. However, this approach has serious limitations. Critically, even though most decisions are embedded within complex social networks of observers, this approach typically ignores how decisions are perceived by valued audiences. To address this limitation, this article proposes reputational rationality theory: a theoretical model of how observers evaluate targets who do (vs. do not) strictly adhere to normative standards of judgment and choice. Drawing on the dual pathways of homophily and social signaling, the theory generates testable predictions regarding when and why observers positively evaluate error-prone decision makers, termed the benefit of bias hypothesis. Given that individuals hold deep impression management goals, reputational rationality theory challenges the unqualified classification of response tendencies that deviate from normative standards as irrational. That is, apparent errors and biases can, under certain conditions, be reputationally rational. The reputational rewards associated with cognitive biases may in turn contribute to their persistence. Acknowledging the (sometimes beneficial) reputational consequences of cognitive biases can address long-standing puzzles in judgment and decision making as well as generate fruitful avenues for future research.

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