We share Chater & Loewenstein's (C&L's) disillusionment with the current state of applied behavioral science (see Gal & Rucker, Reference Gal and Rucker2022). We concur a predominant focus on i-frame (nudge) interventions has not helped much and, in some cases, may have harmed the public by diverting attention from s-framed solutions. However, although we generally agree with C&L's overarching observations and sentiment, we have concern that the alternatives they contemplate cast doubt as to the relevance of behavioral science to policy. Namely, it is unclear that a case has been made that behavioral science is poised to offer insight and to inform, in a meaningful way, s-framed interventions.
Consider the five main public policy problems listed in Table 1 of the target article. It is unclear why any of the proposed s-level interventions require, or even benefit from, insight from behavioral science. The idea that structural change that prevents or discourages a behavior (e.g., a tax leveraged against sugar drinks) leads to a reduction in such behavior (e.g., less consumption) is not a special insight of behavioral science. To the degree such interventions are not implemented, it is not because of a lack of understanding nor communication of behavioral science, but because of the lack of political will and lack of public support to bear the costly tradeoffs involved.
Furthermore, most of the examples of policy that the authors explicitly offer as being based on “behavioral insights” (in target article, sect. 3.3) strike us as mundane and lacking any true insight. For example, avoiding “not invented here” syndrome, encouraging debate within groups, reducing bureaucracy, and making forms clear, are run-of-the-mill advice offered in popular management or information design books. To attribute such common wisdom to “behavioral science insights” seems inappropriate. Regarding climate change, their proposed intervention to increase public support for decarbonization could be viewed as akin to manipulating, and misleading, the public to believe they will get something for nothing (i.e., green energy at no net cost). Here, the idea that people like getting something for nothing is neither, in our view, a behavioral insight nor is such an implementation truthful as presented.
Thus, although we see promise and agree with C&L's general observations, we suggest that behavioral science must go further than emphasizing the need for s-frame interventions if we wish to contribute meaningfully to policy conversations. Next, we offer two principles to guide more relevant and more imaginative behavioral science inspired policy.
The relevance of behavioral science must be founded on theoretical understanding and insight, not extrapolation of effects
A key to making behavioral science relevant to application is the development of theoretical insights about behavior. Theory should be at the crux of application because each setting is unique; the effect of an intervention in one setting can never be directly extrapolated to another. Theoretical understanding, regardless of the source, is what allows us to generate valid explanations for the effects of interventions in novel settings.
Theoretical insights come from developing and testing theories of behavior using experimental and other methods with no special status to “gold standard” controlled field trials or quasi-experiments focused on examining the effects of interventions (Gal & Rucker, Reference Gal and Rucker2022). Although documenting effects is a part of science, we believe too many behavioral scientists have focused on identifying effects rather than on explanations of why those effects occur (i.e., theoretical insights). At the same time, many also confound and mistake descriptions of effects for theoretical explanations.
To illustrate, after observing a phenomenon wherein losses appeared to loom larger than gains, behavioral scientists declared loss aversion a key feature of a “descriptive theory” of choice; that is, a description of an effect rather than an explanation (for a review, see Gal & Rucker, Reference Gal and Rucker2018). Yet, despite lacking theoretical insight, researchers subsequently attempted to export loss aversion to new settings beyond those in which it was described. Unsurprisingly, these attempts have failed (e.g., Ferraro & Tracy, Reference Ferraro and Tracy2022; O'Keefe & Jensen, Reference O'Keefe and Jensen2007).
Behavioral science must strive for imagination in application
The dominant nudge approach has, in our view, been characterized by a lack of creativity and mundane solutions (e.g., send text reminders to encourage remembering an appointment). We believe much of this lack of creativity is because of a procedure of extrapolating generic interventions tested in one context to another as opposed to designing a solution specific to a problem (Gal & Rucker, Reference Gal and Rucker2022). To foster a more relevant behavioral science, imagination is needed in application. Imagination in application is important because behavioral insights cannot be applied directly; they must be translated or incorporated into interventions or other approaches to address specific problems. Doing this effectively will often benefit from, if not demand, finding non-obvious solutions – imagination.
To illustrate the value of imagination in application, research suggests that certain behaviors, including environmentally friendly behaviors (Brough et al., Reference Brough, Wilkie, Ma, Isaac and Gal2016) or seeking mental healthcare (Li & Gal, Reference Li and Gal2021), are stereotyped as feminine and this deters men from engaging in them. How to apply this insight, however, cannot be extrapolated from this finding, but requires imagination. One approach might be to attempt to weaken the stereotypes attached to these behaviors through persuasive messaging (i.e., that such behaviors do not reflect on one's masculinity). Alternative approaches might involve accepting that the stereotypes exist and focusing on framing specific green behaviors in more masculine ways (e.g., buying an electric car offers faster takeoff) or reducing the visibility of such behaviors (e.g., allowing men to receive mental health treatments relatively discreetly and anonymously). Regardless of the specific strategy, the point is that imagination in application is important for increasing the relevance of applied behavioral science.
In sum, agreeing with and building on the target article, we see a “behavioral winter” of sorts in terms of policy relevance is upon us. Yet we believe that policy relevance requires more work beyond noticing the value of s-frame interventions. We have offered two principles that we believe are essential for a spring of more relevant behavioral science to emerge.
Kai Ruggeri
[Opens in a new window]Kai Ruggeri
, Olivia Symone Tutuska
, Giampaolo Abate Romero Ladini
, Narjes Al-Zahli
, Natalia Alexander
, Mathias Houe Andersen
, Katherine Bibilouri
, Jennifer Chen
, Barbora Doubravová
, Tatianna Dugué
, Aleena Asfa Durrani
, Nicholas Dutra
, R. A. Farrokhnia
, Tomas Folke
, Suwen Ge
, Christian Gomes
, Aleksandra Gracheva
, Neža Grilc
, Deniz Mısra Gürol
, Zoe Heidenry
, Clara Hu
, Rachel Krasner
, Romy Levin
, Justine Li
, Ashleigh Marie Elizabeth Messenger
, Fredrik Nilsson
, Julia Marie Oberschulte
, Takashi Obi
, Anastasia Pan
, Sun Young Park
, Sofia Pelica
, Maksymilian Pyrkowski
, Katherinne Rabanal
, Pika Ranc
, Žiga Mekiš Recek
, Daria Stefania Pascu
, Alexandra Symeonidou
, Milica Vdovic
, Qihang Yuan
, Eduardo Garcia-Garzon
and 
We share Chater & Loewenstein's (C&L's) disillusionment with the current state of applied behavioral science (see Gal & Rucker, Reference Gal and Rucker2022). We concur a predominant focus on i-frame (nudge) interventions has not helped much and, in some cases, may have harmed the public by diverting attention from s-framed solutions. However, although we generally agree with C&L's overarching observations and sentiment, we have concern that the alternatives they contemplate cast doubt as to the relevance of behavioral science to policy. Namely, it is unclear that a case has been made that behavioral science is poised to offer insight and to inform, in a meaningful way, s-framed interventions.
Consider the five main public policy problems listed in Table 1 of the target article. It is unclear why any of the proposed s-level interventions require, or even benefit from, insight from behavioral science. The idea that structural change that prevents or discourages a behavior (e.g., a tax leveraged against sugar drinks) leads to a reduction in such behavior (e.g., less consumption) is not a special insight of behavioral science. To the degree such interventions are not implemented, it is not because of a lack of understanding nor communication of behavioral science, but because of the lack of political will and lack of public support to bear the costly tradeoffs involved.
Furthermore, most of the examples of policy that the authors explicitly offer as being based on “behavioral insights” (in target article, sect. 3.3) strike us as mundane and lacking any true insight. For example, avoiding “not invented here” syndrome, encouraging debate within groups, reducing bureaucracy, and making forms clear, are run-of-the-mill advice offered in popular management or information design books. To attribute such common wisdom to “behavioral science insights” seems inappropriate. Regarding climate change, their proposed intervention to increase public support for decarbonization could be viewed as akin to manipulating, and misleading, the public to believe they will get something for nothing (i.e., green energy at no net cost). Here, the idea that people like getting something for nothing is neither, in our view, a behavioral insight nor is such an implementation truthful as presented.
Thus, although we see promise and agree with C&L's general observations, we suggest that behavioral science must go further than emphasizing the need for s-frame interventions if we wish to contribute meaningfully to policy conversations. Next, we offer two principles to guide more relevant and more imaginative behavioral science inspired policy.
The relevance of behavioral science must be founded on theoretical understanding and insight, not extrapolation of effects
A key to making behavioral science relevant to application is the development of theoretical insights about behavior. Theory should be at the crux of application because each setting is unique; the effect of an intervention in one setting can never be directly extrapolated to another. Theoretical understanding, regardless of the source, is what allows us to generate valid explanations for the effects of interventions in novel settings.
Theoretical insights come from developing and testing theories of behavior using experimental and other methods with no special status to “gold standard” controlled field trials or quasi-experiments focused on examining the effects of interventions (Gal & Rucker, Reference Gal and Rucker2022). Although documenting effects is a part of science, we believe too many behavioral scientists have focused on identifying effects rather than on explanations of why those effects occur (i.e., theoretical insights). At the same time, many also confound and mistake descriptions of effects for theoretical explanations.
To illustrate, after observing a phenomenon wherein losses appeared to loom larger than gains, behavioral scientists declared loss aversion a key feature of a “descriptive theory” of choice; that is, a description of an effect rather than an explanation (for a review, see Gal & Rucker, Reference Gal and Rucker2018). Yet, despite lacking theoretical insight, researchers subsequently attempted to export loss aversion to new settings beyond those in which it was described. Unsurprisingly, these attempts have failed (e.g., Ferraro & Tracy, Reference Ferraro and Tracy2022; O'Keefe & Jensen, Reference O'Keefe and Jensen2007).
Behavioral science must strive for imagination in application
The dominant nudge approach has, in our view, been characterized by a lack of creativity and mundane solutions (e.g., send text reminders to encourage remembering an appointment). We believe much of this lack of creativity is because of a procedure of extrapolating generic interventions tested in one context to another as opposed to designing a solution specific to a problem (Gal & Rucker, Reference Gal and Rucker2022). To foster a more relevant behavioral science, imagination is needed in application. Imagination in application is important because behavioral insights cannot be applied directly; they must be translated or incorporated into interventions or other approaches to address specific problems. Doing this effectively will often benefit from, if not demand, finding non-obvious solutions – imagination.
To illustrate the value of imagination in application, research suggests that certain behaviors, including environmentally friendly behaviors (Brough et al., Reference Brough, Wilkie, Ma, Isaac and Gal2016) or seeking mental healthcare (Li & Gal, Reference Li and Gal2021), are stereotyped as feminine and this deters men from engaging in them. How to apply this insight, however, cannot be extrapolated from this finding, but requires imagination. One approach might be to attempt to weaken the stereotypes attached to these behaviors through persuasive messaging (i.e., that such behaviors do not reflect on one's masculinity). Alternative approaches might involve accepting that the stereotypes exist and focusing on framing specific green behaviors in more masculine ways (e.g., buying an electric car offers faster takeoff) or reducing the visibility of such behaviors (e.g., allowing men to receive mental health treatments relatively discreetly and anonymously). Regardless of the specific strategy, the point is that imagination in application is important for increasing the relevance of applied behavioral science.
In sum, agreeing with and building on the target article, we see a “behavioral winter” of sorts in terms of policy relevance is upon us. Yet we believe that policy relevance requires more work beyond noticing the value of s-frame interventions. We have offered two principles that we believe are essential for a spring of more relevant behavioral science to emerge.
Competing interest
None.