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The future of behavioral insights: on the importance of socially situated nudges

Published online by Cambridge University Press:  14 August 2018

SANDER VAN DER LINDEN*
Affiliation:
Department of Psychology, School of Biological Sciences, University of Cambridge, Downing Site, Cambridge, CB2 3EB, UK
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Abstract

Socially minded nudges are the more sociable cousin of regular nudges: they reveal important information about other people's behavior, raise normative expectations about what is desirable, can be shared and transmitted online or offline and leverage social incentives and sanctions that regulate individual and group behavior. In this article, I argue that many of the most successful nudges – that is, nudges that have been well replicated, offer positive spill-over and whose effects last over time – have in fact been social nudges. Moreover, the efficacy of other nudges can be enhanced by considering the social dimension of the problem that they are trying to address. In asking where behavioral science should go next, I argue that although the Behavioural Insights Team has traditionally shied away from addressing more complex and sticky societal issues, socially situated nudges are particularly well suited to address many of the important challenges raised by Sanders et al. (2018).

Type
Articles
Copyright
Copyright © Cambridge University Press 2018 

Introduction

It was in the spring of 2017 that David Halpern and I were on a panel together here in Cambridge talking about behavioral insights. He asked me what was keeping me busy these days and I had an immediate answer: fake news. I asked what the Behavioural Insights Team is currently doing about the spread of fake news, especially in light of the fact that the UK parliament recently opened up an investigation into the various ways in which fake news is undermining democracy (Harriss & Raymer, Reference Harriss and Raymer2017). Halpern asked me what I suggest they do – what was my big idea? I told him that my co-authors and I have been working on developing a fake news ‘vaccine’ (van der Linden et al., Reference van der Linden, Leiserowitz, Rosenthal and Maibach2017a). My memory is a bit foggy, but when asked to elaborate, I recall rambling on about what a complex social issue fake news is and I think we both agreed that I failed to deliver a succinct and actionable policy pitch! I am writing about this event because it was during my talk that I recalled another conversation, some years ago, with Maya Shankar (then head of the US Social and Behavioral Sciences Team) about what it is exactly that they are doing about climate change, another clear complex global issue. To her own dismay, the short answer was, “Not much.”

These are just two examples, but in much of my experience, ‘nudge’ is often seen as almost purposefully steering clear of trying to solve some of the world's biggest and most complex social dilemmas. I was therefore pleased to see clear acknowledgment of this in Sanders, Snijders and Hallsworth's (Reference Sanders, Snijders and Hallsworth2018) article about where we are in behavioral science and where we are going next. In fact, Sanders and Halpern readily admit that they have been advocating for the ‘low-hanging’ fruit, at least in the early life of the Behavioural Insights Team, and perhaps that made good sense in order to establish the viability of using behavioral science effectively in policy. I was also pleased to see a collective desire to tackle bigger problems. Indeed, as the authors state, “it would be disappointing if tax compliance were the only application of behavioral science active in policy ten years from now.” As a social psychologist, I spend much of my time thinking about complex societal affairs, so I completely agree with the observation that although these issues often seem daunting at first, that is not a good reason to avoid tackling them. Of course, when it comes to thorny problems, we need to lower our expectations, as success is often less immediate and more difficult to achieve. However, it is exactly for that reason that insights from behavioral science are desperately needed in this area. While Sanders et al. claim to have made dedicated attempts to start tackling bigger problems, such as poverty and recidivism, their section on thorny problems reads more like a side note rather than an agenda-defining item.

I understand the difficulties. When we published a policy memo distilling key insights from psychological science to help improve behavioral decision-making about climate change (van der Linden et al., Reference van der Linden, Maibach and Leiserowitz2015), Cass Sunstein (Reference Sunstein2015) wondered how much we can achieve in policy with better communications. This remark is ironic, of course, given that some of the most successful nudges have relied on exactly such insights: a simple tweak in wording can be a powerful lever for behavior change, from mobilizing people to vote to saving household energy consumption (Cialdini et al., Reference Cialdini, Martin and Goldstein2015; Panagopolous & van der Linden, Reference Panagopoulos and van der Linden2016). Nonetheless, I can understand the pessimism, and Sunstein is correct, of course, in that some of these problems are going to need much more than a simple nudge. Moving from encouraging people to use double-sided printing to countering violent extremism is quite the behavioral stretch. In fact, polarized issues like climate change are not low-hanging fruit; they often require so-called ‘heavy lifting’ (i.e., the type of controversial policies whose adoption is likely to face serious obstacles) (Sunstein, Reference Sunstein2015). So where does that leave us? Although Sanders et al.’s (Reference Sanders, Snijders and Hallsworth2018) review covers an impressive range of issues, from the replication crisis and small effects to spillover and thorny problems, its breadth necessarily restricts its depth. Little advice is offered on how behavioral science can tackle some of the world's most pressing social issues, including fake news, extremism, inequality and climate change. When I was first invited to write a response, I wondered what else I could say about nudge that Sanders et al. had not already addressed in their article. Yet, the more I thought about how to effectively address thorny problems using insights from behavioral science, the more it dawned on me that (1) the theory of nudge is socially impoverished in some ways, which is important, because (2) many of the most ‘successful’ behavioral insights have in fact been socially minded nudges. They have been successful in the sense that they satisfy many of the problems discussed and reviewed by Sanders et al. (i.e., nudges that are replicable, scalable, have positive spillover and have shown some promise of long-term effects, especially in the context of major societal issues). Accordingly, in the remainder of my response, I will argue that in order to tackle thorny, complex and deeply embedded social problems, we need more socially minded nudges.

The power of socially situated nudges

Not all nudges are social. In fact, let me summarize the spirit of social nudges: they inform us about the behavior of relevant others, raise normative behavioral expectations in some way, leverage social incentives and sanctions or are socially networked and transmissible from one individual to another. The social nature of the nudge could be implicit or explicit, online or offline. Interestingly, when you think about the definition of the ‘NUDGE’ acronym (Thaler & Sunstein, Reference Thaler and Sunstein2009), it becomes clear that there are few explicit social elements present (‘iNcentives’, ‘Understand mappings’, ‘Defaults’, ‘Give feedback’, ‘Expect error’ and ‘Structure complex choices’). To illustrate, the idea of altering the order in which healthy food options appear in school cafeterias involves nothing inherently ‘social’. The choice environment here seems to mean ‘physical’ environment. Clearly, the environment is also social (people queuing), but the nudge itself is not socially situated in that it is does not inform people about the behavior of others, there are no pronounced social expectations, the nudge is not designed to be socially shared or transmitted and there are no social incentives or sanctions regulating an individual's behavior. This is not to say that regular nudges are not successful (on the contrary). It is just evident that in much nudge thinking, the focus seems to be geared toward reducing cognitive load and effort, rather than thinking about the social dimensions of the nudge. Perhaps the greatest testament of this is one of Thaler's personal favorites: the urinal fly nudge. Clearly, aiming at a photorealistic image of a fly is more of a private matter than a socially shared activity. It also illustrates the banality of nudge that many people seem to associate with it: reducing urinal spillage solves one kind of problem, but it is not tackling some of society's greatest challenges. However, in general, ‘standard’ nudges may benefit a great deal from upping their social IQ. For example, in light of hyperbolic discounting, the ‘Save More Tomorrow’ plan focuses on having people commit in advance to allocating a portion of their salary to retirement savings (Thaler & Benartzi, Reference Thaler and Benartzi2004). Although effective, there is nothing particularly social about this nudge. Yet, ‘Save More Tomorrow’ commitments could be increased further by informing people how many referent others are participating (making it a social, group-based initiative) – similar social norm strategies have proven highly effective in other areas (Cialdini et al., Reference Cialdini, Martin and Goldstein2015). There are many more examples. Take the case in point of trying to reduce cognitive load when it comes to filling out complicated forms to receive free school meals. Such forms are problematic, as low-income individuals often already have limited cognitive bandwidth (Mullainathan & Shafir, Reference Mullainathan and Shafir2013). Automatic enrollment has greatly benefitted underprivileged communities in this regard, but the nudge fails to account for the fact that free school lunches are heavily stigmatized (Oostindjer et al., Reference Oostindjer, Aschemann-Witzel, Wang, Skuland, Egelandsdal, Amdam, Schjøll, Pachucki, Rozin, Stein and Lengard Almli2016) – further stigmatization of poverty can be an unintended social consequence (one of the key issues raised by Sanders et al., Reference Sanders, Snijders and Hallsworth2018). For example, in the UK, 29% of eligible children do not participate in the UK's Free School Meals program. So why not design an appropriate socially situated nudge instead? Indeed, reframing free school lunches as a program that is available to all children may be effective. For example, a rise in wider peer group participation reduced non-participation among low-income children by between 29% and 35% (Holford, Reference Holford2015). Because much of human behavior is inherently social, it seems difficult to argue against the need for more socially minded nudges. We can ask, however, whether social nudges have indeed delivered on their potential. I will review some key examples of complex societal issues below where social nudges have been shown to be replicable and scalable, with good potential for long-term effects and positive spillovers.

Limiting global climate change

The importance of insights from behavioral science has been increasingly highlighted in climate change policy-making (van der Linden et al., Reference van der Linden, Maibach and Leiserowitz2015). In fact, one of the largest real-world behavioral science experiments has become a posterchild for the success of ‘behavioral insights’ (Cialdini et al., Reference Cialdini, Martin and Goldstein2015). The company OPOWER supplied millions of customers with tailored energy bills revealing social information about the consumption of their neighbors (Schultz et al., Reference Schultz, Nolan, Cialdini, Goldstein and Griskevicius2007; Allcott, Reference Allcott2011). On average, the intervention led to a reduction in household energy consumption of about 2%.

Although this sounds small, when scaled across millions of households, this is a classic example of the argument that ‘small effects can add up to large-scale policy consequences’ (Cialdini et al., Reference Cialdini, Martin and Goldstein2015) – being the equivalent of an 11–20% short-run price increase (Allcott, Reference Allcott2011). This finding has been replicated in many policy-relevant domains, from tax compliance (Hallsworth et al., Reference Hallsworth, Chadborn, Sallis, Sanders, Berry, Greaves, Clements and Davies2016) and antibiotic prescriptions (Hallsworth et al., Reference Hallsworth, Chadborn, Sallis, Sanders, Berry, Greaves, Clements and Davies2016) to water conservation (Ferraro & Price, Reference Ferraro and Price2013), including meta-analytic evidence (van der Linden & Chryst, Reference van der Linden and Chryst2017). Moreover, although social norm interventions decay substantially over time (van der Linden, Reference van der Linden2015, Reference van der Linden2017a), they have been among the few initiatives that do reveal some long-term effects on behavior even when the interventions are discontinued (Schultz et al., Reference Schultz, Nolan, Cialdini, Goldstein and Griskevicius2007; Ferraro & Price, Reference Ferraro and Price2013; Allcott & Roberts, Reference Allcott and Rogers2014). In addition, descriptive norms have been shown to result in positive spillover. For example, in the context of charitable donations, observing generous donating behavior not only increases donations, but also inspires other, unrelated types of prosocial behavior (Nook et al., Reference Nook, Ong, Morelli, Mitchell and Zaki2016).

These nudges are inherently social because they inform (a) people about the behavior of referent others and (b) set normative expectations about what type of behavior is ‘typical’ and ‘desired’ – reinforcing conformity with the desired norm. Importantly, many social processes are recursive, allowing nudges to initiate virtuous feedback cycles. For example, when more people conform to the desired norm, the social signal becomes stronger and more persuasive, encouraging further compliance. Social nudges are important in these types of complex social dilemmas because people's sense of self-efficacy is often contingent on their perception of how many others are contributing (Kerr & Kaufman-Gilliland, Reference Kerr and Kaufman-Gilliland1997).

Another relevant example is the use of so-called ‘green defaults’. Defaults are a classic nudge, and their effectiveness has been demonstrated in a variety of contexts, from encouraging retirements savings (Thaler & Benartzi, Reference Thaler and Benartzi2004) to organ donor registration (Johnson & Goldstein, Reference Johnson and Goldstein2003) to green energy (Pichert & Katsikopoulos, Reference Pichert and Katsikopoulos2008), with some evidence to suggest that defaults can increase green energy uptake by tenfold (Ebeling & Lotz, Reference Ebeling and Lotz2015). The classic explanation for the success of defaults is not social: people stick with them because it takes more cognitive effort to adjust away from the default (Tversky & Kahneman, Reference Tversky and Kahneman1974). However, a number of recent studies have advanced another, social explanation to account for the default effect. Defaults communicate implicit norms (Davidai et al., Reference Davidai, Gilovich and Ross2012); that is, defaults signal what the normatively desired course of action is (McKenzie et al., Reference McKenzie, Liersch and Finkelstein2006). By setting defaults, institutions implicitly engage in norm signaling (Tankard & Paluck, Reference Tankard and Paluck2016); for example, universities that adopt sustainable defaults implicitly signal what the desired prototypical behavioral choice for the group is, which can not only increase behavioral uptake, but also promote public acceptability of related policies (Santos & van der Linden, Reference Santos and van der Linden2016).

Voting: leave or remain?

Mobilizing citizens to vote is a classic example of a difficult social dilemma. Yet, simple implicit social cues, such as mere images of human eyes, have been shown to increase voter turnout in local elections (Panagopolous, Reference Panagopoulos2014; Panagopolous & van der Linden, Reference Panagopoulos and van der Linden2016). Human gaze detection is an evolved cognitive mechanism that largely draws on areas of the brain that are not under voluntary control, so images or shapes that resemble human eyes can be sufficient to trigger the involuntary detection of another's gaze. Panagopoulos (Reference Panagopoulos2014) reports an average effect size of 2%. Although modest, raising turnout by a few percentage points can have large practical consequences in districts with hundreds of thousands of voters. Critical societal issues such as the EU Brexit referendum (with results being 51.9% leave vs. 48.1% remain) can depend on relatively small differences in voter turnout. More generally, there is some evidence that eye cues can elicit cooperation across domains, from reducing theft to increasing charitable donations (Bateson et al., Reference Bateson, Nettle and Roberts2006; Ernest-Jones et al., Reference Ernest-Jones, Nettle and Bateson2011; Nettle et al., Reference Nettle, Nott and Bateson2012).

Larger effects have been observed with more explicit social norm interventions, such as revealing the average voting history in a household or the voting behavior of neighbors, raising voter turnout by as much as 8% (Gerber et al., Reference Gerber, Green and Larimer2008), which is cost effective at a rate of $2–3 per vote. Social networks further illustrate the power of socially situated nudges. Messages delivered to over 60 million Facebook users during a 2010 US election not only influenced information-seeking and voting behavior, but also the behavior of a user's friends and friends of friends. Importantly, the effect of social transmission was greater than the direct effect of the messages themselves (Bond et al., Reference Bond, Fariss, Jones, Kramer, Marlow, Settle and Fowler2012). These effects are not short-lived, either. Davenport et al. (Reference Davenport, Gerber, Green, Larimer, Mann and Panagopoulos2010) tracked over a million voters and found that the effects of social norm communications can last up to two years after the initial treatment.

The fake news nudge

The rise of fake news and misinformation poses a serious threat to people's ability to form evidence-based judgments (Lewandowsky et al., Reference Lewandowsky, Ecker and Cook2017; Schwartz et al., Reference Schwarz, Newman and Leach2016; van der Linden, Reference van der Linden2017b). A large majority of Americans find that fake news leaves them confused over basic facts (Barthel et al., Reference Barthel, Mitchell and Holcomb2016). Although the root causes of increasing societal conflict and political polarization are clearly complex, this in itself does not preclude the implementation of behavioral insights to help protect people from being misled by false information. For example, in a recent Science editorial, we highlight that it is possible to pre-emptively warn and inoculate people against fake news across the political spectrum (van der Linden et al., Reference van der Linden, Maibach, Cook, Leiserowitz and Lewandowsky2017b). Inoculation theory draws on a biological analogy: just as injections with a weakened dose of a virus can offer resistance to future infection by triggering antibodies in the immune system, the same can reasonably be achieved with information, cultivating ‘mental’ antibodies. Research in different domains, from public health to politics to climate change, has shown that through warnings and ‘cognitive rehearsal’ (i.e., pre-emptively debunking a falsehood), attitudinal resistance can be conferred (Banas & Rains, Reference Banas and Rains2010; Niederdeppe et al., Reference Niederdeppe, Heley and Barry2015) and politicization can be counteracted (Bolsen & Druckman, Reference Bolsen and Druckman2015; Cook et al., Reference Cook, Lewandowsky and Ecker2017; van der Linden et al., Reference van der Linden, Leiserowitz, Rosenthal and Maibach2017a).

Warnings about disputed content can help nudge people from relying predominantly on a ‘system 1’ (heuristic) to more of a ‘system 2’ (deliberate) type of information processing. Controlled laboratory evaluations of Facebook's disputed warning label system (tagging articles that have been disputed by independent fact-checkers) have shown some promise in reducing the credibility of disputed articles (Pennycook et al., Reference Pennycook and Rand2017). On the Behavioral Public Policy Blog, Baggio and Motterlini (Reference Baggio and Motterlini2017) suggest other real-world social applications of inoculation, such as in the context of vaccine hesitancy, as after childbirth parents are typically overwhelmed and may be more susceptible to misinformation. Other potential societal applications include building cognitive resistance to extremism and radicalization in conflict areas. Inoculation can also offer crossover protection to related but experimentally untreated beliefs (Parker et al., Reference Parker, Rains and Ivanov2016), and although the effect decays, there is some evidence to suggest that resistance can persist over time (Niederdeppe et al., Reference Niederdeppe, Heley and Barry2015).

Thus far, the fake news nudge itself appears to have no social element, as inoculation is mostly about achieving cognitive resistance to misinformation. However, the most powerful application of inoculation lies in its ability to spread (van der Linden et al., Reference van der Linden, Maibach, Cook, Leiserowitz and Lewandowsky2017b), both online through social networks, as well as interpersonally (Compton & Pfau, Reference Compton and Pfau2009; Ivanov et al., Reference Ivanov, Miller, Compton, Averbeck, Harrison, Sims, Parker and Parker2012). In this sense, the vaccine metaphor can be extended so that potential herd immunity and societal resistance can be achieved against misinformation. This could occur when a sufficient number of people have been inoculated in a network or when the rate of transmission of the ‘vaccine’ outpaces the rate at which misinformation replicates. In short, the most important consequence of inoculation is its ability to be scaled at population level through social transmission. For example, we have developed a ‘fake news’ inoculation game that can be played and shared online.Footnote 1 These are all areas where behavioral insights obtained from large-scale randomized controlled trials would be of great value.

Conclusion

In sum, many of the most successful nudges have been socially oriented. Importantly, these nudges are well replicated, have positive spillover effects and last over time. Conversely, the efficacy of traditional nudges may be enhanced – and unintended negative consequences can be averted – by considering the social dimension of the problem the nudge is trying to solve. In asking where behavioral science is going next, I hope to have illustrated that thorny problems often concern recursive social processes that can be more effectively addressed with socially minded nudges. For many of my psychologist colleagues, I have probably not gone far enough (e.g., see Mols et al., Reference Mols, Haslam, Jetten and Steffens2015), as many of society's most urgent challenges reflect deep commitments to social groups and identities and are going to need more than a simple nudge. But upping the social IQ of every existing and new nudge is a step in the right direction: does this nudge signal what behavior is desired? Is the nudge socially inclusive? Does it inspire more people to comply? Can the nudge be shared and transmitted? Social nudges may be simple, but they have the distinct advantage of making friends and they can turn a drop into a wave and transform an individual into a crowd, and crowds can change the world.

Acknowledgements

I would like to thank the editors and members of the Social Decision-Making Lab for their helpful feedback on earlier versions of this manuscript.

Footnotes

References

Allcott, H. (2011), ‘Social norms and energy conservation’, Journal of Public Economics, 95(9): 10821095.Google Scholar
Allcott, H. and Rogers, T. (2014), ‘The short-run and long-run effects of behavioral interventions: Experimental evidence from energy conservation’, The American Economic Review, 104(10): 30033037.Google Scholar
Baggio, M. and Motterlini, M. (2017), Could we use “cognitive vaccination” against “Anti-vaxx”? Behavioural Public Policy Blog. https://bppblog.com/2017/10/16/could-we-use-cognitive-vaccination-against-anti-vaxx/ [28 November 2017].Google Scholar
Banas, J. A. and Rains, S. A. (2010), ‘A meta-analysis of research on inoculation theory’, Communication Monographs, 77(3): 281311.Google Scholar
Barthel, M., Mitchell, A. and Holcomb, J. (2016), Many Americans believe fake news is sowing confusion. http://www.journalism.org/2016/12/15/many-americans-believe-fake-news-is-sowing-confusion/PewResearchCenter [November 29 2017].Google Scholar
Bateson, M., Nettle, D. and Roberts, G. (2006), ‘Cues of being watched enhance cooperation in a real-world setting’, Biology Letters, 2(3): 412414.Google Scholar
Bolsen, T. and Druckman, J. N. (2015), ‘Counteracting the politicization of science’, Journal of Communication, 65(5): 745769.Google Scholar
Bond, R. M., Fariss, C. J., Jones, J. J., Kramer, A. D., Marlow, C., Settle, J. E. and Fowler, J. H. (2012), ‘A 61-million-person experiment in social influence and political mobilization’, Nature, 489(7415): 295298.Google Scholar
Cialdini, R. B., Martin, S. J. and Goldstein, N. J. (2015), ‘Small behavioral science–informed changes can produce large policy-relevant effects’, Behavioral Science & Policy, 1(1): 2127.Google Scholar
Cook, J., Lewandowsky, S. and Ecker, U. K. (2017), ‘Neutralizing misinformation through inoculation: Exposing misleading argumentation techniques reduces their influence’, PloS One, 12(5): 0175799.Google Scholar
Compton, J. and Pfau, M. (2009), ‘Spreading Inoculation: Inoculation, Resistance to Influence, and Word-of-Mouth Communication’, Communication Theory, 19(1): 928.Google Scholar
Davenport, T. C., Gerber, A. S., Green, D. P., Larimer, C. W., Mann, C. B. and Panagopoulos, C. (2010), ‘The enduring effects of social pressure: Tracking campaign experiments over a series of elections’, Political Behavior, 32(3): 423430.Google Scholar
Davidai, S., Gilovich, T. and Ross, L. D. (2012), ‘The meaning of default options for potential organ donors’, Proceedings of the National Academy of Sciences, 109(38): 1520115205.Google Scholar
Ebeling, F. and Lotz, S. (2015), ‘Domestic uptake of green energy promoted by opt-out tariffs’, Nature Climate Change, 5(9): 868871.Google Scholar
Ernest-Jones, M., Nettle, D. and Bateson, M. (2011), ‘Effects of eye images on everyday cooperative behavior: a field experiment’, Evolution and Human Behavior, 32(3): 172178.Google Scholar
Ferraro, P. J. and Price, M. K. (2013), ‘Using nonpecuniary strategies to influence behavior: evidence from a large-scale field experiment’, Review of Economics and Statistics, 95(1): 6473.Google Scholar
Gerber, A. S., Green, D. P. and Larimer, C. W. (2008), ‘Social pressure and voter turnout: Evidence from a large-scale field experiment’, American Political Science Review, 102(1): 3348.Google Scholar
Hallsworth, M., Chadborn, T., Sallis, A., Sanders, M., Berry, D., Greaves, F., Clements, L. and Davies, S. C. (2016), ‘Provision of social norm feedback to high prescribers of antibiotics in general practice: a pragmatic national randomised controlled trial’, The Lancet, 387(10029): 17431752.Google Scholar
Harriss, L. and Raymer, K. (2017), ‘Online information and fake news’, Parliamentary Office of Science and Technology’, POSTnote 0559. Houses of Parliament, London, UK. http://researchbriefings.parliament.uk/ResearchBriefing/Summary/POST-PN-0559Google Scholar
Holford, A. (2015), ‘Take-up of Free School Meals: Price Effects and Peer Effects’, Economica, 82(328): 976993.Google Scholar
Ivanov, B., Miller, C. H., Compton, J., Averbeck, J. M., Harrison, K. J., Sims, J. D., Parker, K. A. and Parker, J. L. (2012), ‘Effects of postinoculation talk on resistance to influenc’, Journal of Communication, 62(4): 701718.Google Scholar
Johnson, E. J. and Goldstein, D. (2003), ‘Do defaults save lives?’, Science, 302(5649): 13381339.Google Scholar
Kerr, N. L. and Kaufman-Gilliland, C. M. (1997), ‘“… and besides, I probably couldn't have made a difference anyway”: justification of social dilemma defection via perceived self-inefficacy’, Journal of Experimental Social Psychology, 33(3): 211230.Google Scholar
Lewandowsky, S., Ecker, U. K. and Cook, J. (2017), ‘Beyond Misinformation: Understanding and Coping with the “Post-Truth” Era’, Journal of Applied Research in Memory and Cognition, 6(4): 353369.Google Scholar
McKenzie, C. R., Liersch, M. J. and Finkelstein, S. R. (2006), ‘Recommendations implicit in policy defaults’, Psychological Science, 17(5): 414420.Google Scholar
Mols, F., Haslam, S. A., Jetten, J. and Steffens, N. K. (2015). ‘Why a nudge is not enough: A social identity critique of governance by stealth’, European Journal of Political Research, 54(1): 8198.Google Scholar
Mullainathan, S. and Shafir, E. (2013), Scarcity: Why having too little means so much. Times Books. Henry Holt and Company, New York: NY.Google Scholar
Nettle, D., Nott, K. and Bateson, M. (2012), ‘Cycle thieves, we are watching you’: impact of a simple signage intervention against bicycle theft’, PloS One, 7(12): e51738.Google Scholar
Niederdeppe, J., Heley, K. and Barry, C. L. (2015), ‘Inoculation and narrative strategies in competitive framing of three health policy issues’, Journal of Communication, 65(5): 838862.Google Scholar
Nook, E. C., Ong, D. C., Morelli, S. A., Mitchell, J. P. and Zaki, J. (2016), ‘Prosocial conformity: Prosocial norms generalize across behavior and empathy’, Personality and Social Psychology Bulletin, 42(8): 10451062.Google Scholar
Oostindjer, M., Aschemann-Witzel, J., Wang, Q., Skuland, S. E., Egelandsdal, B., Amdam, G. V., Schjøll, A., Pachucki, M. C., Rozin, P., Stein, J. and Lengard Almli, V. (2016), ‘Are school meals a viable and sustainable tool to improve the healthiness and sustainability of children's diet and food consumption? A cross-national comparative perspective’, Critical Reviews in Food Science and Nutrition 57(18): 39423958.Google Scholar
Panagopoulos, C. (2014), ‘I've got my eyes on you: Implicit social-pressure cues and prosocial behavior’, Political Psychology, 35(1): 2333.Google Scholar
Panagopoulos, C. and van der Linden, S. (2016), ‘Conformity to implicit social pressure: the role of political identity’, Social Influence, 11(3): 177184.Google Scholar
Parker, K. A., Rains, S. A. and Ivanov, B. (2016), ‘Examining the “blanket of protection” conferred by inoculation: The effects of inoculation messages on the cross-protection of related attitudes’, Communication Monographs, 83(1): 4968.Google Scholar
Pennycook, G. and Rand, D. G. (2017), ‘Assessing the effect of “disputed” warnings and source salience on perceptions of fake news accuracy’, Social Science Research Network. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3035384Google Scholar
Pichert, D. and Katsikopoulos, K. V. (2008), ‘Green defaults: Information presentation and pro-environmental behaviour’, Journal of Environmental Psychology, 28(1): 6373.Google Scholar
Roozenbeek, J. and van der Linden, S. (2018), ‘The fake news game: actively inoculating against the risk of misinformation’, Journal of Risk Research. doi: 10.1080/13669877.2018.1443491.Google Scholar
Sanders, M., Snijders, V. and Hallsworth, M. (2018). Behavioural science and policy: where are we now and where are we going? Behavioural Public Policy, 2(2): 144167.Google Scholar
Santos, J. M. and van der Linden, S. (2016), ‘Changing norms by changing behavior: The Princeton Drink Local Program’, Environmental Practice, 18(2): 116122.Google Scholar
Schultz, P. W., Nolan, J. M., Cialdini, R. B., Goldstein, N. J. and Griskevicius, V. (2007), ‘The constructive, destructive, and reconstructive power of social norms’, Psychological Science, 18(5): 429434.Google Scholar
Schwarz, N., Newman, E. and Leach, W. (2016), ‘Making the truth stick & the myths fade: Lessons from cognitive psychology’, Behavioral Science & Policy, 2(1): 8595.Google Scholar
Sunstein, C. R. (2015), ‘On interesting policymakers’, Perspectives on Psychological Science, 10(6): 764767.Google Scholar
Tankard, M. E. and Paluck, E. L. (2016), ‘Norm perception as a vehicle for social change’, Social Issues and Policy Review, 10(1): 181211.Google Scholar
Thaler, R. H. and Benartzi, S. (2004), ‘Save more tomorrow™: Using behavioral economics to increase employee saving’, Journal of political Economy, 112(S1): S164S187.Google Scholar
Thaler, R. H. and Sunstein, C. R. (2009), ‘Nudge: Improving Decisions About Health, Wealth, and Happiness’, New Haven, CT: Yale University Press.Google Scholar
Tversky, A. and Kahneman, D. (1974), ‘Judgment under uncertainty: Heuristics and biases’, Science, 185(4157): 11241131.Google Scholar
van der Linden, S. (2015), ‘Intrinsic motivation and pro-environmental behaviour’, Nature Climate Change, 5(7): 612613.Google Scholar
van der Linden, S. (2017a), ‘The nature of viral altruism and how to make it stick’, Nature Human Behaviour, 1: 0041.Google Scholar
van der Linden, S. (2017b), ‘Beating the hell out of fake news’, Ethical Record: The Proceedings of the Conway Hall Ethical Society 122(6), 47.Google Scholar
van der Linden, S. and Chryst, B. (2017), ‘No Need for Bayes Factors: A Fully Bayesian Evidence Synthesis’, Frontiers in Applied Mathematics and Statistics, 3: 12.Google Scholar
van der Linden, S., Maibach, E. and Leiserowitz, A. (2015), ‘Improving public engagement with climate change: Five “best practice” insights from psychological science’, Perspectives on Psychological Science, 10(6): 758763.Google Scholar
van der Linden, S., Leiserowitz, A., Rosenthal, S. and Maibach, E. (2017a), ‘Inoculating the public against misinformation about climate change’, Global Challenges, 1(2): 1600008.Google Scholar
van der Linden, S., Maibach, E., Cook, J., Leiserowitz, A. and Lewandowsky, S. (2017b), ‘Inoculating against misinformation’, Science, 358(6367): 11411142.Google Scholar