Behavioural science is unlikely to change the world without a heterogeneity revolution

Bryan, Christopher J.; Tipton, Elizabeth; Yeager, David S.

doi:10.1038/s41562-021-01143-3

Cited by 335 publications

(311 citation statements)

References 94 publications

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“…Research has recently started to reveal some of those potential moderators of choice architecture interventions, including sociodemographic factors such as income and socioeconomic status as well as psychological factors such as domain knowledge, numerical ability, and attitudes ( 65 – 67 ). Investigating these moderators systematically cannot only provide a more nuanced understanding of the conditions under which choice architecture facilitates behavior change but may also help to inform the design and implementation of targeted interventions that take into account individual differences in the susceptibility to choice architecture interventions ( 68 ). Ethical considerations should play a prominent role in this process to ensure that potentially more susceptible populations, such as children or low-income households, retain their ability to make decisions that are in their personal best interest ( 66 , 69 , 70 ).…”

Section: Discussionmentioning

confidence: 99%

The effectiveness of nudging: A meta-analysis of choice architecture interventions across behavioral domains

Mertens

Herberz

Hahnel

et al. 2021

Proc. Natl. Acad. Sci. U.S.A.

358

191

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Over the past decade, choice architecture interventions or so-called nudges have received widespread attention from both researchers and policy makers. Built on insights from the behavioral sciences, this class of behavioral interventions focuses on the design of choice environments that facilitate personally and socially desirable decisions without restricting people in their freedom of choice. Drawing on more than 200 studies reporting over 450 effect sizes (n = 2,149,683), we present a comprehensive analysis of the effectiveness of choice architecture interventions across techniques, behavioral domains, and contextual study characteristics. Our results show that choice architecture interventions overall promote behavior change with a small to medium effect size of Cohen’s d = 0.45 (95% CI [0.39, 0.52]). In addition, we find that the effectiveness of choice architecture interventions varies significantly as a function of technique and domain. Across behavioral domains, interventions that target the organization and structure of choice alternatives (decision structure) consistently outperform interventions that focus on the description of alternatives (decision information) or the reinforcement of behavioral intentions (decision assistance). Food choices are particularly responsive to choice architecture interventions, with effect sizes up to 2.5 times larger than those in other behavioral domains. Overall, choice architecture interventions affect behavior relatively independently of contextual study characteristics such as the geographical location or the target population of the intervention. Our analysis further reveals a moderate publication bias toward positive results in the literature. We end with a discussion of the implications of our findings for theory and behaviorally informed policy making.

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Section: Discussionmentioning

confidence: 99%

The effectiveness of nudging: A meta-analysis of choice architecture interventions across behavioral domains

Mertens

Herberz

Hahnel

et al. 2021

Proc. Natl. Acad. Sci. U.S.A.

358

191

View full text Add to dashboard Cite

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“…In many countries, people with different socio‐economic backgrounds have different experiences with government, which may inform their stereotypes. A next step would be to replicate this study in other countries (Bryan, Tipton, and Yeager 2021, see also Haque, Van der Wal, and Van den Berg 2021). This will help us understand when, why, and how stereotype differences come about, by allowing us to compare country‐level factors such as bureaucratic and media culture, corruption levels, political and welfare systems, or socioeconomic inequalities.…”

Section: Discussionmentioning

confidence: 98%

Socioeconomic Status and Public Sector Worker Stereotypes: Results from a Representative Survey

Bertram

Bouwman

Tummers

2022

Public Administration Review

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What views do people have of public sector workers? Public sector workers are often portrayed negatively. It is unclear, however, to what extent such negative perceptions are shared among different groups in society. Using a large representative survey in the Netherlands, we study whether people's socioeconomic status is related to having more negative stereotypes about public sector workers. Contrary to expectations, education and income are unrelated to stereotypes. We do find a relation with subjective income: People with low subjective income have more negative stereotypes. Moreover, the sector people work in is highly relevant. People working in core governmental sectors such as central and local government have positive stereotypes. Other groups—such as private sector and non‐profit workers—have a far more negative image of public sector workers. These findings help us to understand people's perceptions of public sector workers and the problems various groups have with the state.

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“…In terms of the validity of a test-result, therefore, any parameter that is induced from old data is conceptually non-equivalent to a theoretical parameter that is tested against new data. (Bryan, Tipton & Yeager, 2021).…”

Section: Pure Induction and The True Population Effectmentioning

confidence: 99%

The case for default point-H1-hypotheses in behavioral science: a theory-construction perspective

Zenker¹,

Witte²

2021

Preprint

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The development of an empirically adequate theoretical construct for a given phenomenon of interest requires an estimate of the population effect size, aka the true effect. Arriving at this estimate in evidence-based ways presupposes access to robust experimental or observational findings, defined as statistically significant test-results with high statistical power. In the behavioral sciences, however, even the best journals typically publish statistically significant test-results with insufficient statistical power, entailing that such findings have insufficient replication probability. Whereas a robust finding formally requires that an empirical study engage with point-specific H0- and H1-hypotheses, behavioral scientists today typically point-specify only the H0, and instead engage a composite (directional) H1. This mismatch renders the prospects for theory-construction poor, because the population effect size—the very parameter that is to be modelled—regularly remains unknown. This can only keep from developing empirically adequate theoretical constructs. Based on the research program strategy (RPS), a sophisticated integration of Frequentist and Bayesian statistical inference elements, here we claim that theoretical progress requires engaging with point-H1-hypotheses by default.

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Behavioural science is unlikely to change the world without a heterogeneity revolution

Cited by 335 publications

References 94 publications

The effectiveness of nudging: A meta-analysis of choice architecture interventions across behavioral domains

The effectiveness of nudging: A meta-analysis of choice architecture interventions across behavioral domains

Socioeconomic Status and Public Sector Worker Stereotypes: Results from a Representative Survey

The case for default point-H1-hypotheses in behavioral science: a theory-construction perspective

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