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A nudge in the right direction: the role of food choice architecture in changing populations' diets

Published online by Cambridge University Press:  15 January 2021

H. Ensaff*
Affiliation:
Nutritional Sciences and Epidemiology, School of Food Science and Nutrition, University of Leeds, LeedsLS2 9JT, UK
*
Corresponding author: H. Ensaff, email [email protected]
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Abstract

Populations' diets typically fall short of recommendations. The implication of this on ill health and quality of life is well established, as are the subsequent health care costs. An area of growing interest within public health nutrition is food choice architecture; how a food choice is framed and its influence on subsequent food selection. In particular, there is an appeal to manipulating the choice architecture in order to nudge individuals' food choice. This review outlines the current understanding of food choice architecture, theoretical background to nudging and the evidence on the effectiveness of nudge strategies, as well as their design and implementation. Interventions emphasising the role of nudge strategies have investigated changes to the accessibility, availability and presentation of food and the use of prompts. Empirical studies have been conducted in laboratories, online and in real-world food settings, and with different populations. Evidence on the effectiveness of nudge strategies in shifting food choice is encouraging. Underpinning mechanisms, not yet fully explicated, are proposed to relate to salience, social norms and the principle of least effort. Emerging evidence points to areas for development including the effectiveness of choice architecture interventions with different and diverse populations, and the combined effect of multiple nudges. This, alongside further examination of theoretical mechanisms and guidance to engage and inspire across the breadth of food provision, is critical. In this way, the potential of choice architecture to effect meaningful change in populations' diets will be realised.

Type
Research Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press on behalf of The Nutrition Society

Diets falling short

Populations' diets typically fall short of recommendations. Inadequate consumption of fruit, vegetables, legumes, wholegrains, nuts and seeds, in parallel with excessive consumption of red meat, processed meat and sugar-sweetened beverages, is evident globally(1). In the UK, for example, only 8 % of 11–18-year-olds and 31 % of adults meet fruit and vegetable guidelines(2); oily fish consumption stands at 56 g/week for adults(2) (below the 140 g/week recommendation(3)) and adults consume 19 g/d dietary fibre(2) (again, below the 30 g/d recommendation(4)). Children's intake of free sugars is excessive, beyond the 5 % recommendation(4), at 13⋅5 % (4–10-year-olds) and 14⋅1 % (11–18-year-olds) of dietary energy intake(2). Further, saturated fat intake in adults (11⋅9 %(2)) exceeds the recommended maximum of 10 % dietary energy intake(5), as does salt (8⋅4 g/d(6) beyond the recommended maximum of 6 g/d(7)).

This mismatch between government guidelines and a population's actual diet remains a fundamental challenge, with substantial implications reflected in the mortality and morbidity tolls associated with diet-related ill health(1,Reference Micha, Peñalvo and Cudhea8) . The impact of diet and dietary patterns on individuals' quality of life(Reference Govindaraju, Sahle and McCaffrey9,Reference Wu, Zhuang and Li10) is clear. Likewise, health care costs are substantial with poor diet-related ill health costs in the UK of the order of £5⋅8 billion (2006/7)(Reference Scarborough, Bhatnagar and Wickramasinghe11), projected to grow to an estimated £9⋅7 billion by 2050 for overweight and obesity-related health costs(12). Globally, the economic impact of obesity has been estimated to be of the order of US$2 trillion(Reference Dobbs, Sawers and Thompson13).

Worldwide obesity prevalence provides the impetus and urgency to act, with more than 650 million adults with obesity, alongside more than 120 million children and adolescents(Reference Abarca-Gómez, Abdeen and Hamid14). In England specifically, one in five 4–5-year-olds is overweight (including obese) rising to one in three 10–11-year-olds being the same(15). Moreover, diet is a modifiable risk factor, also pertinent to health inequalities, with, for example, men and those with manual occupations less likely to adhere to UK dietary recommendations(Reference Yau, Adams and Monsivais16).

A need to improve diets nationally, regionally and globally has been highlighted(1). In addressing populations' diets, much of the emphasis has been on guidance and education, with the principle that advice translates into positive action from citizens. However, behaviour change is notoriously difficult, with translation not always straightforward. The utility of food choice architecture (how a food choice is framed, and the consequences on subsequent food selections) in this endeavour shows promise, and nudging populations to change their diets has clear and distinct potential. Similarly, there is mounting evidence steering a move away from the conventional stance of food choice as a rational and deliberative act. Interest in opportunities to change diets that do not rely on rational decision-making and engagement of citizens is growing. To this end, the development of theory and evidence-based interventions to actively support citizen access to a sustainable and healthy diet is critical.

The present paper (1) overviews current understanding of food choice, choice architecture and nudge strategies; (2) outlines some of the research conducted so far with populations, and considers the effectiveness of nudge strategies in changing food choice; (3) considers the design and implementation of nudge strategies; and (4) looks forward to potential future developments in this area.

Understanding food choice

Central to addressing the mismatch between government recommendations and citizens' diets is a robust understanding of food choice, which determines food intake, with its short- and long-term health consequences(Reference Buttriss17). Promotion and prediction of behaviour change is not obvious, and requires a comprehensive understanding of conditions preceding behaviour(Reference Kelly and Barker18). Likewise, it is important to note the reciprocal relationship between food choice and provision; food provision influences consumer behaviour and food choice, which itself influences new product development and food provision.

Food choice is complex, dynamic and multifaceted. It is constructed individually, according to interrelated concepts which are shifting and not static. Multiple factors interact to culminate in an individual's preferences and food choice parameters which then shape food choice. As well as physiological drivers, the relevance of social, cultural and psychological aspects to food choice has long been recognised(19). An early taxonomy of the determinants of food consumption behaviour categorised person-related factors, as well as properties of the food itself, and those related to the environment(Reference Steenkamp20). Further, food choice reflects and propagates socio-cultural aspects and is a means of representing identity. Prior experiences and associations with food coalesce to influence food choice, and in this way, an individual's food choice history(Reference Devine21) is personalised and dynamic.

Various theoretical models (each with their limitations) conceptualise and examine food choice. The food choice process model posits that, across a life course, individuals' experiences affect food choice and inform personal systems, which incorporate value negotiations and personalised strategies(Reference Sobal and Bisogni22,Reference Furst, Connors and Bisogni23) . Value negotiations assess various aspects (e.g. sensory perceptions, health and nutrition beliefs and concerns, social relationships) in order to make a food choice, and individuals employ strategies which are honed to simplify the process and guide routine food choice(Reference Sobal and Bisogni22,Reference Furst, Connors and Bisogni23) .

Using a life-course perspective, food choice trajectories recognise that foods, individuals and environments are not static, and food choice may undergo minor transitions and major turning points(Reference Devine21,Reference Devine, Connors and Bisogni24) . These deviations are triggered by an individual's change in circumstances; the nature of which, together with the individual themselves, dictate whether a turning point or less severe transition prevails.

Numerous models, notably the theory of planned behaviour(Reference Ajzen, Kuhl and Beckmann25) and its predecessor, the theory of reasoned action(Reference Ajzen and Fishbein26), highlight the central role of intention in behaviour change. Research confirms the importance of intentions in predicting behaviour(Reference Sheeran27,Reference McEachan, Conner and Taylor28) , and importantly evidence also indicates that the intention–behaviour gap is large(Reference Sheeran and Webb29), with individuals encountering difficulties in translating intentions. Moreover, automaticity and habits may be more relevant, with the intentional control of behaviour seemingly more limited than previously considered(Reference Sheeran27).

Past behaviour guides, and is an important predictor of, future behaviour(Reference Ouellette and Wood30,Reference Ajzen31) , including within the context of food(Reference Wong and Mullan32,Reference Dai, Cone and Moher33) . Habits strongly predict eating behaviour, and are more dependent on the environment, less under intentional control, and largely outside conscious awareness(Reference van't Riet, Sijtsema and Dagevos34). Indeed, the automaticity of food choice and the sheer influence of social and environmental cues are gaining authority; this relates to an automatic behaviour being without qualities such as intent, control, effort, awareness(Reference Bargh, Wyer and Srull35). Carefully considered decisions are atypical for everyday food choice, instead these decisions are largely automatic and habitual, using heuristics (rules of thumb) to act efficiently, because they have been made in the same contexts many times before, and therefore practices are honed. To this end, people rely on behavioural cues from others, and are strongly influenced by social context and norms(Reference Robinson, Blissett and Higgs36Reference Higgs38). Modelling of food intake can be powerful and robust(Reference Vartanian, Spanos and Herman39), particularly when individuals perceive themselves similar to the model or desire to affiliate with them(Reference Cruwys, Bevelander and Hermans40). There is also clear evidence for social facilitation, with people selecting and eating more when with friends(Reference Ruddock, Brunstrom and Vartanian41). Similarly, an individual's food order can be influenced by the person ahead in line(Reference Christie and Chen42). The potential of harnessing social context to improve dietary intake has been highlighted(Reference Robinson, Blissett and Higgs36).

Temporal or time discounting(Reference Barlow, Reeves and McKee43) is relevant in considering food choice, and specifically the intention–behaviour gap. This relates to how value decreases with time, how reward now outweighs later greater benefit, and how individuals tend to have more self-control for future, compared to immediate, plans. Indications are that high time discounting is a risk factor for unhealthy diets, as well as overweight and obesity(Reference Barlow, Reeves and McKee43).

In everyday food decisions, there may be several alternatives to choose from, each with their own attributes. Drift-diffusion models(Reference Fisher44,Reference Krajbich, Lu and Camerer45) explain how individuals accumulate evidence for options until this exceeds a threshold. Likewise, choices are biased by where someone looks and if they look for longer at one alternative(Reference Krajbich, Lu and Camerer45). One strategy that individuals use is heuristics(Reference Kahneman46,Reference Tversky and Kahneman47) ; these limit cognitive load thereby conserving capacity for other tasks(Reference Cohen and Babey48), and may relate to features such as the look, shape, logo, price.

Ultimately, when it comes to food choice, individuals are not rational and do not make carefully considered decisions informed by guidance and evidence. Instead, everyday food decisions are largely automatic, habitual and poorly regulated, guided by non-cognitive processing(Reference Cohen and Babey48); consistent with quick, instinctive and emotional (system 1) processes as opposed to deliberative, rational and slow (system 2)(Reference Stanovich and West49,Reference Kahneman50) . Selection is made in the most efficient manner, to minimise mental and physical effort. Therefore, food choice is susceptible to environmental nudge strategies, and this is the opportunity afforded by choice architecture, to propel better food choice.

Choice architecture and nudge theory

With origins in the discipline of behavioural economics, the concept of nudge has developed since the early 1970s, culminating in the term in the late 2000s(Reference Thaler and Sunstein51). Today, nudge theory has become an area of immense interest including within public health nutrition. Pivotal to nudge theory is the concept of choice architecture(Reference Thaler and Sunstein51). This relates to how a choice is presented and its influence on decision-making(Reference Thaler and Sunstein51). Food choice architecture specifically incorporates all aspects of how a food choice is framed, and the consequences on subsequent food selections made(Reference Ensaff, Homer and Sahota52). This relates to, for example, the layout and wording of menu options, order of food in a buffet line, presentation of meals in a canteen, verbal prompts such as ‘Would you like a side with your order?’, and in essence, every aspect counts and signifies.

The prevailing choice architecture (either by design or otherwise) encourages or discourages certain food choice behaviour. Therefore, there is an appeal to manipulating the choice architecture in order to nudge individuals in a particular direction, towards specific choices. The changes to the choice architecture, the nudge strategies (nudges), are small subtle changes to the social and physical environment.

Central to nudge theory is libertarian paternalism(Reference Thaler and Sunstein53); this approach preserves freedom of choice alongside authority to guide people in a particular direction, considered to be beneficial to their welfare, i.e. a positive change for individuals' and wider societal interests. Government interest in nudge theory and libertarian paternalism continues, particularly where it is considered an attractive alternative to the removal of choice from citizens or the imposition of legislation. This is relevant in public health policy and food choice which impact on a nation's health.

Nudge strategies

Nutrition interventions theoretically grounded in nudge theory emphasise the role of nudge strategies to shift food choice. Purposeful choice architecture exploits the premise that most food decisions are automatic, utilising heuristics and biases as shortcuts, and nudge strategies direct food choice towards preferable decisions, promoting or demoting selection of ‘target’ foods.

Nudging entails priming in order to influence individuals' behaviour through cues; typically, it is without individuals' awareness and inherently involves a side-stepping of an individual's reasoning capabilities(Reference Blumenthal-Barby and Burroughs54). Many nudge strategies correspond to minimising the effort required for (or resistance to) selecting the promoted option, i.e. making the target choice the easy choice. Nudge strategies, typically minor and unobtrusive, do not require high cognitive effort and aim to effect change by operating within individuals' automatic processes. This includes reducing physical effort, cognitive load and/or time.

The nudge strategies may relate to changes to the accessibility, availability and presentation of food options and the use of prompts. With a core principle of retaining the freedom to choose(Reference Thaler and Sunstein51,Reference Thaler and Sunstein53) , no food options are eliminated, and likewise, significantly changing economic incentives are not allowed(Reference Thaler and Sunstein51). Thus, changing the price of a food option or removing it would not constitute a nudge strategy, whereas changing its location would. Fig. 1 provides examples of nudge strategies related to food.

Fig. 1. (Colour online) Nudge strategies implemented in choice architecture interventions to change food choice: reducing effort and cognitive load, increasing salience and emphasising tastiness and social norms.

Overview of nudge strategies

Many nudge strategies are placement manipulations, straightforward changes to the location of food options, e.g. closer to the consumer, near the till, at eye level. The order of food options can also be adjusted (e.g. first in buffet/canteen line, first option on a menu) as can the availability (e.g. number available of promoted items). Particular food options can also be highlighted or emphasised in contrast with competing options, e.g. boxing on a menu. Other nudge strategies include changes to the presentation or format of food (e.g. grab-and-go pots, plate size, tongs to serve) and the addition of semiotics (icons or symbols, e.g. healthy heart labels, emoticon stickers). Nudge strategies can also incorporate descriptive names for target foods, e.g. slow-roasted sweet potato, or prompts, either written or verbal, e.g. ‘Make a fresh choice’, ‘Would you like a side with that?’ Finally, defaults (i.e. standard options that remain, unless an individual intervenes) can be utilised in nudge strategies, e.g. changing the standard meal option to a plant-based dish.

A scientific basis is essential to behaviour change interventions(Reference Michie and Johnston55), and sound theory provides a solid foundation to inform our understanding of how and why nudge strategies may work, and propels future developments in the design of interventions and their effectiveness. Research evidence is outlined later, alongside a current understanding of mechanisms to explain the effects observed, which are not yet fully understood.

Empirical evidence and theory

Many placement nudge strategies work on the basis that options further away or less prominent will reduce their selection, and several studies have shown these to be effective in reducing snack selection(Reference Maas, de Ridder and de Vet56Reference Knowles, Brown and Aldrovandi58). Consumption of brownies and M&Ms was significantly higher when these were located 20 cm away from an individual compared to 70 cm(Reference Knowles, Brown and Aldrovandi58). A different study examining proximity demonstrated participants consuming more apple slices even when competing with a preferred higher energy food (buttered popcorn), positioned further away(Reference Privitera and Zuraikat59). Further, a meta-analysis of nudge-based interventions focusing on fruit and vegetables revealed the largest effect size for placement nudge strategies(Reference Broers, De Breucker and Van den Broucke60). The potential of repositioning foods to meaningful behaviour change as part of a wider strategy to improve food consumption(Reference Hollands, Carter and Anwer61) is evident.

Accessibility or convenience can also change food selection; increasing effort required by offering food that needs unwrapping can reduce intake and this has been shown with individual chocolates(Reference Brunner62) and chocolate brownies(Reference Knowles, Brown and Aldrovandi58). Further, increasing physical effort (wrapped v. unwrapped brownie) and also positioning snacks further away can act independently and interactively to decrease snack consumption(Reference Knowles, Brown and Aldrovandi58). Other simple adjustments such as the specific location within a salad bar and also the provision of a pair of tongs v. a spoon can change (8–16 % difference) food choice(Reference Rozin, Scott and Dingley63). Another study demonstrated how participants having to grab food with sugar tongs significantly reduced consumption of unhealthy (chocolate candies) and healthy (dried apricots) snacks(Reference Brunner62).

Several mechanisms have been proposed to explain the effects observed. These include classical energy conservation and the principle of least effort(Reference Tolman64,Reference Zipf65) where shorter routes to goals are prioritised. Thus, required effort is reduced by bringing items closer or removing barriers (e.g. unwrapping food). Notably, previous work has shown distance affecting perceived effort and reducing selection(Reference Maas, de Ridder and de Vet56). A systematic review on positional changes highlighted evidence regarding the influence of proximity or order of food on food choice, with the strength of the effect apparently dependent on the kind of manipulation (order/distance) and its extent (e.g. how far away)(Reference Bucher, Collins and Rollo66).

Research has also shown how changing the component size of food is relevant, e.g. full-size brownies compared to halved(Reference Hansen, Skov and Jespersen67), whole pretzels also halved(Reference Geier, Rozin and Doros68). Such effects have been attributed to a unit bias(Reference Geier, Rozin and Doros68), a heuristic that choosing one item is appropriate. Presenting food in fun formats has also been investigated; one study conducted in primary schools found that consumption almost doubled when whole wheat bread was presented in fun shapes(Reference Van Kleef, Vrijhof and Polet69). Interestingly, researchers found slight increases in children's perceived tastiness and enjoyment with the shape manipulations(Reference Van Kleef, Vrijhof and Polet69).

In examining how nudge strategies might be effective, it is important to consider the salience of an option, its prominence/contrast with its surroundings (e.g. its brightness, colour). Salience can have a strong effect on food choice, and salience bias (perceptual salience) is a cognitive bias where individuals facing multiple options focus attention on those that are particularly prominent. Manipulating salience and increasing the brightness of food images has been shown to promote selection, even when competing with unhealthy but tastier (participant perceived) alternatives(Reference Dai, Cone and Moher33). Further, salience effects remained in conditions of additional cognitive load (when participants were given a cognitive task) or time pressure(Reference Dai, Cone and Moher33). Salience may also underpin the effects observed in changing the order of food options (e.g. in a buffet line) and placement. However, some research has shown no effect of distance on perceived salience(Reference Maas, de Ridder and de Vet56), and further work is needed to understand fully the implication of the distance moved and the potential relevance of the range of distances.

Placement nudge strategies have been explored on menus as well; placing items at the beginning or the end of options increased their selection by approximately 20 % from the middle(Reference Dayan and Bar-Hillel70). Attractive descriptive names for food options have been reported to impact the likelihood of selection(Reference Bacon and Krpan71,Reference Vennard, Park and Attwood72) . Other work has examined ‘sweet spots’ on menus, i.e. points where consumers first gaze or spend most time looking at. Although empirical evidence is inconclusive as to the merit of placing options at these points(Reference Ozdemir and Caliskan73), a study with older adults in assisted living residences indicated that this did significantly affect selection(Reference Feldman, Mahadevan and Su74). Likewise boxing of food options was shown to increase the selection of healthier items(Reference Feldman, Mahadevan and Su74). Salience may be pertinent in the effects observed, as well as those when positioning food options at the top or bottom of a menu. The relevance of position within a menu has also been linked to primacy and recency effects(Reference Bacon and Krpan71,Reference Bowen and Morris75) , cognitive biases whereby items encountered at the start or end are recalled more clearly.

Increasing the availability (e.g. relative share/number available of promoted items) has been reported to improve selection(Reference Hollands, Carter and Anwer61). As well as salience (increased with more items on show), another proposed mechanism relates to social norms, specifically descriptive norms, i.e. perceptions of the prevalence of a behaviour, communicated via the increased availability. Research has also examined the addition of semiotics, i.e. icons or symbols (e.g. heart logos(Reference Stutts, Zank and Smith76,Reference Levin77) , emoticons(Reference Ensaff, Homer and Sahota52,Reference Siegel, Anneken and Duffy78) ) as a nudge strategy. These additions affect salience and promote selection through individuals' heuristic use, particularly where there are multiple options to choose from. Indeed, this points to the relevance of minimising effort expenditure, cognitively as well as physically. Interestingly, there may be a distinct advantage to subtle messaging, i.e. logo v. explicit message. One study revealed a heart logo commonly used to indicate a healthy food item was effective in increasing selection, whereas an explicit message (‘A Healthy Choice’) was ineffective(Reference Wagner, Howland and Mann79). This may be attributable to the different processing that each accesses, i.e. more automatic with the implicit and more deliberative rational with the explicit. Further, it is important to consider the potential of affect (experiencing an emotion or feeling) and, for example, an emotional response to icons or symbols used as nudge strategies, as well as any implicit approval conveyed, e.g. smiley face.

Default-based nudge strategies such as standard food options have been shown to increase their selection(Reference Campbell-Arvai, Arvai and Kalof80). The relevant underpinning mechanisms relate to the principle of least effort, with individuals remaining with the default for convenience and minimising cognitive effort. Likewise, mechanisms may relate to norms communicated through the standard, i.e. defaults provide a strong indication of social norms, which act as a heuristic for an appropriate food choice. Another potential mechanism relates to status quo bias(Reference Samuelson and Zeckhauser81), with individuals tending to maintain the status quo as the disadvantages of leaving loom larger than the potential advantages. Providing information about eating norms can also be effective in changing individuals' food choices(Reference Robinson, Thomas and Aveyard37,Reference Burger, Bell and Harvey82) . Consistent evidence attests to the effect on food choice, as well as food intake norms influencing the quantity of food consumed(Reference Robinson, Thomas and Aveyard37). Further, the perceived norm originating from a socially proximal group has been shown to be relevant, with behaviour affected when the norm is from an ‘in-group’(Reference Cruwys, Platow and Angullia83).

Nudging and the place of taste

Overall, the mechanisms for the effects observed with nudging and choice architecture interventions are yet to be fully explicated. Nudge strategies influence food choice, however the place of taste for individuals must be respected. It is important to appreciate how extraordinarily important hedonic reward is in food decisions, and that highly palatable foods win. Therefore, in the simplest way, people's food choice parameters dominate, and within these, taste rules supreme and typically overrides other considerations.

It is proposed that for a nudge strategy to be effective and a consumer to choose an option, their perception of the tastiness of the food needs to be satisfied, prior to selection. In other words, a consumer may be diverted elsewhere, regardless of the nudge strategy. Indeed, this is supported by an early study which found that making desserts less accessible had an effect when implemented on low-energy desserts (e.g. fruit) but not high-energy desserts (e.g. cakes)(Reference Meyers, Stunkard and Coll84). Other work found that whilst it may be straightforward to induce increased consumption of palatable foods by social influence, this is not the case with unpalatable foods(Reference Pliner and Mann85). Health-focused labels may also deter selection given that consumers may implicitly subscribe to healthiness and tastiness being inversely related(Reference Raghunathan, Naylor and Hoyer86). Further, it is interesting to consider how nudges can work with consumer perceptions in this regard. One review highlighted the potential approaches of enhancing multisensory desirability of salad greens(Reference Spence87), and another study demonstrated higher tastiness ratings for food arranged in an aesthetically pleasing manner(Reference Michel, Velasco and Gatti88). Therefore, the key principles in establishing effective nudges may revolve around reducing effort and cognitive load, increasing salience and emphasising tastiness and social norms.

Nudging towards plant-based diets

As an environmentally sustainable food system becomes more compelling, there is increasing interest in how to nudge populations towards more sustainable diets. Such changes may be towards plant-based diets, including towards less familiar sources (e.g. algae, aquatic plants) as well as an emphasis shift from animal-based protein to plant-based protein, in line with some of the evidence relating to sustainable diets(Reference Searchinger, Waite and Hanson89,90) . Likewise, there is compelling evidence regarding the health benefit of plant-based diets(Reference Satija and Hu91,Reference Katz and Meller92) and the replacement of animal with plant protein(Reference Song, Fung and Hu93).

Manipulating food choice architecture to direct food decisions towards more plant-based sources holds promise, and empirical research in this arena has focused on, e.g. plant-based foods(Reference Ensaff, Homer and Sahota52,Reference Vennard, Park and Attwood72) , vegetarian options(Reference Bacon and Krpan71), meat-free options(Reference Campbell-Arvai, Arvai and Kalof80). Plant-based foods were the focus of a school-based intervention(Reference Ensaff, Homer and Sahota52) which utilised multiple nudge strategies (including descriptive labels, grab-and-go pots, placement) to shift adolescents' food choice. Overall selection was significantly different during the intervention to the rest of the year and previous year, and children were 2⋅5 times as likely to select ‘nudged’ items during the intervention, compared to baseline(Reference Ensaff, Homer and Sahota52).

Research conducted online has demonstrated how factors such as an option being the chef's menu recommendation and more appealing descriptions can increase the likelihood of a vegetarian dish choice(Reference Bacon and Krpan71). Interestingly, effects were shown to differ depending upon past behaviour; infrequent vegetarian eaters were significantly more likely to choose a vegetarian dish (with a descriptive name, or boxed and captioned as ‘chef's recommendation’), whereas those who ate vegetarian food more frequently had a reduced frequency of selection(Reference Bacon and Krpan71).

Research has also shown how utilising a default menu can increase sustainable food choices. The probability of choosing a meat-free option increased with the use of a default menu, and increased further with the use of ‘appealing’ meat-free options(Reference Campbell-Arvai, Arvai and Kalof80). Work examining the language used for plant-based meals has also pointed to more effective wording to ‘meat-free’, as well as the advantage of experiential and indulgent language reflecting flavour, taste, enjoyment, e.g. ‘melt in the mouth’, ‘mild and sweet’(Reference Vennard, Park and Attwood72). Other research has examined the value of descriptive language, with 25 % more people selecting vegetables labelled indulgently compared to neutral descriptions, and up to 41 % more people selecting these when compared to healthy labelling, e.g. ‘rich buttery roasted sweet corn’ (indulgent) v. ‘corn’ (neutral) v. ‘reduced-sodium corn’ (healthy)(Reference Turnwald, Boles and Crum94). Other nudge strategies, such as ‘climate-friendly choice’ labels on meals have been effective in increasing selection, with indications that the longer the intervention, the greater the selection(Reference Visschers and Siegrist95).

Design and implementation of nudge strategies

A developing understanding of nudge strategies proffers a compelling opportunity to specify and reshape existing food choice architecture. A methodology to do so is needed and indeed the lack of instruction on the implementation of nudges for practitioners has been highlighted(Reference Szaszi, Palinkas and Palfi96). This process revolves around two related components: the target food items (promoted/demoted); and the nudge strategies themselves, which should be considered together. Central to this is the scrutiny of the specific choice architecture. The importance of this is apparent in contrasting settings, e.g. a workplace cafeteria, a table service restaurant, pre-order menu system for hospital patients. Even within apparently similar settings, the unique framework of food choice must be analysed. The target food items are dictated to some extent by the desired shift, or specific criteria. Previous work, for example, has centred on fruit and vegetables(Reference Broers, De Breucker and Van den Broucke60), vegetarian food options(Reference Bacon and Krpan71), meat substitutes(Reference Vandenbroele, Slabbinck and Van Kerckhove97), whole wheat bread(Reference Van Kleef, Vrijhof and Polet69), leafy greens(Reference Spence87), plant-based foods(Reference Ensaff, Homer and Sahota52).

Robust characterisation of the food choice architecture is accomplished through multiple means, including observation visits, mapping and photographing the food environment, interviews (e.g. key informant interviews with catering managers, focus group/intercept interviews with consumers), analysis of menu cycles/recipes and interrogation of food choice data. Integrated findings provide a comprehensive account of food choice within the specific setting, in order to then develop and refine candidate nudge strategies. Subsequent consultation with stakeholders provides feedback to distinguish those nudge strategies that are worthy of further refinement, from those impractical or redundant. This stage also fosters ownership of the changes and can support intervention fidelity, and feasibility of wider roll-out.

Choice architecture interventions to nudge populations

There is a growing body of literature on nutrition interventions underpinned by nudge theory. This work is being conducted internationally, including in the UK and Europe, with a preponderance of the evidence from US studies. Research has been conducted in laboratories(Reference Privitera and Zuraikat59,Reference Walsh and Kiviniemi98,Reference Kosīte, König and De-loyde99) as well as online(Reference Dai, Cone and Moher33,Reference Bacon and Krpan71,Reference Vennard, Park and Attwood72) . Critically, there is also a growing body of work conducted in real-world food settings(Reference Cadario and Chandon100) such as schools(Reference Marcano-Olivier, Horne and Viktor101,Reference Metcalfe, Ellison and Hamdi102) , university cafeterias(Reference Buscher, Martin and Crocker103,Reference Peterson, Duncan and Null104) , workplace(Reference Allan, Querstret and Banas105) and healthcare sites(Reference Al-Khudairy, Uthman and Walmsley106). To date, populations have included children and adolescents(Reference Marcano-Olivier, Horne and Viktor101,Reference Metcalfe, Ellison and Hamdi102,Reference Nørnberg, Houlby and Skov107,Reference Lycett, Miller and Knox108) , young adults at university(Reference Roy, Kelly and Rangan109), adults(Reference Arno and Thomas110) and older adults(Reference Feldman, Mahadevan and Su74). Similar effects in adults and children have been reported(Reference Cadario and Chandon100) and a systematic review(Reference Lycett, Miller and Knox108) examining children's dietary behaviour and nudge interventions found positive results in thirty-three of the forty studies. Interestingly, positive effects were less likely in preschool (younger) children and it was proposed that younger children might be less susceptible due to their greater reliance on their own internal regulation as opposed to external food choice architecture(Reference Lycett, Miller and Knox108).

Frameworks and typologies

The importance of typologies and frameworks to propel further development in this area has been recognised, particularly with respect to supporting empirical research and impact on practice and policy. This is an active area and there are commonalities and distinctions between various contributions.

A framework of three degrees of nudges, based on the extent of the intrusion on a consumer's autonomy in decision-making, has been proposed(Reference Baldwin111). First-degree nudges entail straightforward provision of information and are reliant on full autonomy for an informed rational decision; second-degree nudges lend themselves to behavioural or volitional limitations and bias the desired decision; and third-degree nudges involve greater behaviour manipulation and may include framing devices, salience and affect(Reference Baldwin111).

Likewise, ‘pure’ nudges operating within automatic responses can be distinguished from changes that potentially instigate more deliberative decisions(Reference Baldwin111), e.g. providing information. This distinction is not universally accepted and indeed some proponents incorporate information giving within nudges. It is plausible that there is a continuum with, for example, energy labelling, front-of-pack nutrient profiling and emoticons all at different points, such that an emoticon accesses automatic decision-making whereas energy labelling requires more deliberative processes. This argument is supported by findings from a meta-analysis(Reference Sinclair, Cooper and Mansfield112) that interpretive menu labels (e.g. traffic light, healthy heart symbols) but not informative menu labels (i.e. energy labelling) affected selection and consumption.

MINDSPACE (messenger, incentives, norms, defaults, salience, priming, affect, commitments, ego)(Reference Dolan, Hallsworth and Halpern113) was one of the earliest frameworks and sought to collate the most effective behavioural influences. The UK's Behavioural Insights Team developed the EAST framework(114), advocating the principles of easy, attractive, social and timely for a behaviour to be encouraged. Another key development was a provisional typology of choice architecture interventions, based on adjusting placement, properties and both(Reference Hollands, Shemilt and Marteau115). This was later developed to TIPPME (typology of interventions in proximal physical micro-environments), with fewer intervention types and a recognition that it is linked to a more general concept of physical environment, and that whilst interventions within the typology might map onto the concept of nudging to some extent, this is not a required feature(Reference Hollands, Bignardi and Johnston116).

Overlaps, where nudge strategies have features straddling more than one category, are evident, and this was acknowledged for an affect/behaviour/cognition categorisation(Reference Cadario and Chandon100) devised in a meta-analysis restricted to real-world empirical evidence(Reference Cadario and Chandon100). Cognitively oriented interventions aimed to adjust what consumers know, e.g. nutrition labelling; affectively oriented interventions aimed to adjust how consumers feel without adjusting knowledge, e.g. verbal prompts, attractive descriptions; and behaviourally oriented interventions aimed to directly adjust behaviour without adjusting consumer knowledge or feelings, e.g. first in buffet, pre-sliced fruit(Reference Cadario and Chandon100).

Effectiveness of choice architecture interventions

Numerous systematic reviews(Reference Bucher, Collins and Rollo66,Reference Szaszi, Palinkas and Palfi96,Reference Marcano-Olivier, Horne and Viktor101,Reference Metcalfe, Ellison and Hamdi102,Reference Allan, Querstret and Banas105Reference Lycett, Miller and Knox108,Reference Wilson, Buckley and Buckley117,Reference Skov, Lourenço and Hansen118) and several meta-analyses(Reference Broers, De Breucker and Van den Broucke60,Reference Hollands, Carter and Anwer61,Reference Cadario and Chandon100,Reference Arno and Thomas110,Reference Sinclair, Cooper and Mansfield112) have examined the evidence on choice architecture interventions for changing food choice. There are strong indications that nudge strategies hold promise(Reference Broers, De Breucker and Van den Broucke60,Reference Bucher, Collins and Rollo66,Reference Marcano-Olivier, Horne and Viktor101,Reference Lycett, Miller and Knox108,Reference Arno and Thomas110,Reference Blaga, Vasilescu and Chereches119) , and there is a growing consensus on their merits and potential to shift populations' diets. However, inconsistent findings are evident(Reference Nørnberg, Houlby and Skov107,Reference Skov, Lourenço and Hansen118) and the quality of studies has been emphasised as critical in making further progress in the field.

Research to date shows that the effectiveness of nudge strategies ranges from weak to moderate, with variation across nudge strategies, and a growing interest in combined v. individual nudges. Nudge strategies are also considered to be more effective in time-pressured settings and with lots of choices, i.e. where food choice is particularly susceptible to being automatic. Evidence is also emerging that the most effective nudge strategies may be those that are behaviourally oriented(Reference Cadario and Chandon100) (i.e. look to change behaviour most directly).

A meta-analysis(Reference Arno and Thomas110) of forty-two studies restricted to adults found that nudge strategies resulted in a 15⋅3 % increase in healthier consumption (measured by the frequency of healthy choices or overall energy intake). The authors highlighted the potential of nudging as a strategy to support healthy eating and recommended further work in different settings and countries(Reference Arno and Thomas110). Another meta-analysis(Reference Sinclair, Cooper and Mansfield112) of seventeen studies examining menu labelling and the provision of energy information, as well as more interpretive information (e.g. traffic light symbols, heart symbol), found that energy alone did not have an effect, whilst contextual or interpretive detail did. These supported consumers' selection and consumption of less energy, i.e. −280⋅3 kJ (−67 kcal) and −338⋅9 kJ (−81 kcal), respectively(Reference Sinclair, Cooper and Mansfield112). A Cochrane review(Reference Hollands, Carter and Anwer61) reported the effects of changing the proximity or order of foods, or the number (or relative proportion) of options available. Authors concluded that repositioning or changing the availability of options could contribute to behaviour change; however, they pointed to the limited evidence base, and limited confidence in estimated effects(Reference Hollands, Carter and Anwer61). The first meta-analysis to indicate promising medium effect sizes utilised fourteen well-documented studies of interventions to shift fruit and vegetable selection; placement and combined nudges provided significant effects on food choice (effect sizes, d = 0⋅39 and d = 0⋅28, respectively)(Reference Broers, De Breucker and Van den Broucke60). The need for greater reflection on study design and reporting statistical techniques was also highlighted(Reference Broers, De Breucker and Van den Broucke60). Finally, one comprehensive meta-analysis(Reference Cadario and Chandon100) examined ninety-six studies of choice architecture interventions, restricted to real-world settings. An average effect size of 0⋅23 was reported; although considered small, researchers translated this to an equivalent 518⋅8 kJ/d (124 kcal/d), approximately 7⋅2 %) reduction in energy intake(Reference Cadario and Chandon100). Effect size increases were also reported as the focus of the nudge strategy shifted from cognition to affect to behaviour, with the largest effect size being the equivalent of −874⋅5 kJ/d (−209 kcal/d)(Reference Cadario and Chandon100). When considered on a population level, this reveals the potential impact of nudge strategies and choice architecture interventions in addressing shortfalls in populations' food choice behaviour.

In the considered meta-analyses, different types of nudge strategies targeting different foods were considered, and each focused on food choice and/or consumption. In examining studies, the distinction between food choice and consumption should be acknowledged; however, choice is an overriding influence on consumption and evidence suggests that measuring food choice, as opposed to the more challenging food consumption, may be used to test the impact of interventions(Reference Cadario and Chandon100).

Policy and practice

Traditionally, public health interventions have centred on education, regulation and taxation. Indeed, much of the emphasis has been on nutrition guidance and information, on the basis that advice would translate into action. Historically borrowed from doctor–patient models, this is less effective in behaviour change for prevention and has been highlighted as a common mistake(Reference Kelly and Barker18), where advice and guidance may be insufficient to shift habitual behaviour. Interventions based on nutrition education or changing attitudes rely on better food choice on the basis of rational and deliberative decision-making. This overlooks the premise that everyday food choice is automatic and habitual. Indeed, heuristics and food choice parameters provide some explanation as to why such interventions may be limited.

Automaticity of food choice processes is formidable. For success, we need to develop supportive and nurturing food choice architecture that safeguards better choices, in contrast to existing choice architecture which often challenges and, in some cases, undermines favourable diets. Evidence from systematic reviews is increasingly pointing to the utility of choice architecture interventions in this endeavour. Implementing nudge theory to bring about behaviour change is seemingly an approach more aligned to changing everyday food choice. Effecting change by operating within individuals' automatic responses, nudge strategies do not rely on high cognitive effort and work on the principle of reducing the effort required to get to the designated choice. To that end, choice architecture interventions present an effective solution to adjusting some population-level behaviours for improvements in public health(Reference Kelly and Barker18).

The promise of choice architecture can be instigated at multiple points across the breadth of food provision from schools and workplaces, fast food outlets and restaurants, to markets and supermarket retailers. Leadership and guidance are needed for establishments that are interested to manipulate food choice architecture supportive of positive change. Specifically, practical tools and support to select appropriate nudges should be developed in order to engage and inspire stakeholders to take action. The role of government and policy is paramount, e.g. restrictions regarding the location of high in fat, sugar or salt products in retail settings included in the UK government's strategy for tackling obesity(120).

The potential of nudge strategies

Evidence to date points to the substantial and valuable role of nudge strategies and choice architecture interventions in addressing diet shortfalls. This can be attributed to four key reasons. First, nudge strategies can be effective in shifting food choice and therefore it is plausible to orchestrate a difference in diet. The second key reason is the typical low cost associated with implementation and maintenance. This is pertinent when considering under-resourced sectors and the possibility of scaling up interventions. Third, because of its nature, nudging can affect whole populations, and lends itself to propagating small changes, which on a population basis is considerable. Indeed, nudging resonates well with public health policy emphasising minor changes individually, culminating in substantial improvements at a population level. Further, it is compelling that nudging is not reliant on education or income and provides the potential to tackle health inequalities. The fourth reason is that nudge strategies do not interfere with food provision, with no changes or restrictions to what is available to choose. This can promote stakeholder engagement, particularly when considering the catering and retail sectors involved and their business models.

Research priorities and future developments

The evidence surrounding the effectiveness of nudge strategies in shifting food choice is growing, as is the literature base in support of the potential for such strategies to change populations' diets. Given the potential, there is a need to invest in further research. Due to the likely differential with respect to laboratory settings and research conducted in real-world settings, there is a need for further real-world research(Reference Hollands, Carter and Anwer61,Reference Skov, Lourenço and Hansen118,Reference Blaga, Vasilescu and Chereches119) . There is also a need for a greater understanding of the extent to which people mind being nudged or otherwise. This is relevant as acceptability influences implementation at government level. Evidence of public approval of nudging for health reasons(Reference Junghans, Cheung and De Ridder121) and specifically to promote healthy eating(Reference Evers, Marchiori and Junghans122,Reference Reisch, Sunstein and Gwozdz123) may propel a move towards greater transparency. This would address some of the ethical dimensions relating to nudges, previously outlined(Reference Blumenthal-Barby and Burroughs54). Alongside this, further evidence is needed on whether knowing you are being nudged matters in terms of the effect of the nudge; indications to date are that consumers' awareness does not necessarily change the effect of nudges(Reference Kroese, Marchiori and De Ridder124Reference Cheung, Gillebaart and Kroese126).

Another area for future development relates to unintended consequences, where individuals may compensate for nudged food choices with less preferable additions, e.g. side dishes, drinks, thereby undermining positive outcomes. Some evidence on compensatory behaviour has been reported(Reference Wisdom, Downs and Loewenstein127,Reference Vermeer, Steenhuis and Leeuwis128) and it is important to examine this further, in order to appreciate how to mitigate against it. Further, opportunities to test outcomes for choice architecture interventions against established health promotion interventions would be valuable in ascertaining advantage, and these have been called for(Reference Blaga, Vasilescu and Chereches119). This will inform intervention and policy design to support populations.

Among all potential areas for development and based on emerging evidence, two key areas however are worthy of special consideration. First, the effectiveness of choice architecture interventions with different populations is critical, and the need for further work in this area has been recognised(Reference Arno and Thomas110,Reference Wilson, Buckley and Buckley117,Reference Blaga, Vasilescu and Chereches119) . Similarly, there is a need to better characterise populations and further research with diverse populations and also emerging market economies is warranted. The second area relates to a lack of research examining the combined effect of multiple nudges, particularly as effects may be individualised and meaningful impact may require multiple nudges(Reference Lycett, Miller and Knox108). These together will contribute to a better understanding of the dynamics between choice architecture and food choice.

Conclusions

There is an obvious imperative to address populations' diets. It is essential that policy and practice prioritising health and wellbeing embrace the complexity of food choice and look beyond traditional routes. Evidence to date on nudge strategies to change food choice is growing and shows great promise. It is clear that choice architecture has a distinct and vital role to play in improving populations' diets. Investment in further research to establish and exploit the opportunities afforded by food choice architecture is critical. As opposed to the present-day position which can challenge and undermine favourable diets, there is a need to drive supportive choice architecture as the norm. Guidance to engage and inspire decision makers across the breadth of food provision will propel this positive action. Ultimately, choice architecture and nudge strategies offer the potential to realise change in populations' diets.

Acknowledgements

The author acknowledges the Nutrition Society for the invitation to present at the annual conference and the opportunity to prepare this work.

Financial Support

None.

Conflict of Interest

None.

Authorship

The author had sole responsibility for all aspects of preparation of the paper.

References

GBD (2017) Diet Collaborators (2019) Health effects of dietary risks in 195 countries, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet 393, 19581972.CrossRefGoogle Scholar
Public Health England (2018) NDNS results from years 7 and 8 (combined): data tables. https://www.gov.uk/government/statistics/ndns-results-from-years-7-and-8-combined (accessed July 2020).Google Scholar
Scientific Advisory Committee on Nutrition (2004) Advice on Fish Consumption: Benefits & Risks. London, UK: The Stationery Office.Google Scholar
Scientific Advisory Committee on Nutrition (2015) Carbohydrates and Health. London, UK: The Stationery Office.Google Scholar
Scientific Advisory Committee on Nutrition (2019) Saturated Fats and Health. London, UK: The Stationery Office.Google Scholar
Public Health England (2020) Assessment of Salt Intake from Urinary Sodium in Adults (Aged 19 to 64 Years) in England, 2018 to 2019. London, UK: Public Health England.Google Scholar
Scientific Advisory Committee on Nutrition (2003) Salt and Health. London, UK: The Stationery Office.Google Scholar
Micha, R, Peñalvo, JL, Cudhea, F et al. (2017) Association between dietary factors and mortality from heart disease, stroke, and type 2 diabetes in the United States. J Am Med Assoc 317, 912924.CrossRefGoogle ScholarPubMed
Govindaraju, T, Sahle, B, McCaffrey, T et al. (2018) Dietary patterns and quality of life in older adults: a systematic review. Nutrients 10, 971.CrossRefGoogle ScholarPubMed
Wu, XY, Zhuang, LH, Li, W et al. (2019) The influence of diet quality and dietary behavior on health-related quality of life in the general population of children and adolescents: a systematic review and meta-analysis. Qual Life Res 28, 19892015.CrossRefGoogle ScholarPubMed
Scarborough, P, Bhatnagar, P, Wickramasinghe, KK et al. (2011) The economic burden of ill health due to diet, physical inactivity, smoking, alcohol and obesity in the UK: an update to 2006–07 NHS costs. J Public Heal 33, 527535.CrossRefGoogle ScholarPubMed
Dobbs, R, Sawers, C, Thompson, F et al. (2014) Overcoming obesity: an initial economic analysis. A discussion paper by the McKinsey Global Institute. November 2014. McKinsey Global Institute.Google Scholar
Abarca-Gómez, L, Abdeen, ZA, Hamid, ZA et al. (2017) Worldwide trends in body-mass index, underweight, overweight, and obesity from 1975 to 2016. Lancet 390, 26272642.CrossRefGoogle Scholar
NHS Digital (2019) National child measurement programme, England 2018/19 School Year [NS] – NHS Digital. https://digital.nhs.uk/data-and-information/publications/statistical/national-child-measurement-programme/2018-19-school-year (accessed July 2020).Google Scholar
Yau, A, Adams, J & Monsivais, P (2019) Time trends in adherence to UK dietary recommendations and associated sociodemographic inequalities, 1986–2012: a repeated cross-sectional analysis. Eur J Clin Nutr 73, 9971005.CrossRefGoogle Scholar
British Nutrition Foundation & Buttriss, JL (2013) Nutrition and Development: Short- and Long-Term Consequences for Health. West Sussex, UK: John Wiley & Sons, Ltd.Google Scholar
Kelly, MP & Barker, M (2016) Why is changing health-related behaviour so difficult? Public Health 136, 109116.CrossRefGoogle ScholarPubMed
National Research Council (US) Committee on Food Habits (1943) The Problem of Changing Food Habits. Washington, DC: National Academies Press.Google Scholar
Steenkamp, J-BEM (1993) Food consumption behavior. Eur Adv Consum Res 1, 401409.Google Scholar
Devine, CM (2005) A life course perspective: understanding food choices in time, social location, and history. J Nutr Educ Behav 37, 121128.CrossRefGoogle ScholarPubMed
Sobal, J & Bisogni, CA (2009) Constructing food choice decisions. Ann Behav Med 38, 3746.CrossRefGoogle ScholarPubMed
Furst, T, Connors, M, Bisogni, CA et al. (1996) Food choice: a conceptual model of the process. Appetite 26, 247266.CrossRefGoogle Scholar
Devine, CM, Connors, M, Bisogni, CA et al. (1998) Life-course influences on fruit and vegetable trajectories: qualitative analysis of food choices. J Nutr Educ 30, 361370.CrossRefGoogle Scholar
Ajzen, I (1985) From intentions to actions: a theory of planned behavior. In Action Control, pp. 1139 [Kuhl, J and Beckmann, J, editors]. Berlin, Heidelberg: Springer.CrossRefGoogle Scholar
Ajzen, I & Fishbein, M (1980) Understanding Attitudes and Predicting Social Behaviour. New Jersey: Prentice-Hall.Google Scholar
Sheeran, P (2002) Intention–behavior relations: a conceptual and empirical review. Eur Rev Soc Psychol 12, 136.CrossRefGoogle Scholar
McEachan, RRC, Conner, M, Taylor, NJ et al. (2011) Prospective prediction of health-related behaviours with the theory of planned behaviour: a meta-analysis. Health Psychol Rev 5, 97144.CrossRefGoogle Scholar
Sheeran, P & Webb, TL (2016) The intention–behavior gap. Soc Personal Psychol Compass 10, 503518.CrossRefGoogle Scholar
Ouellette, JA & Wood, W (1998) Habit and intention in everyday life: the multiple processes by which past behavior predicts future behavior. Psychol Bull 124, 5474.CrossRefGoogle Scholar
Ajzen, I (2011) The theory of planned behaviour: reactions and reflections. Psychol Health 26, 11131127.CrossRefGoogle ScholarPubMed
Wong, CL & Mullan, BA (2009) Predicting breakfast consumption: an application of the theory of planned behaviour and the investigation of past behaviour and executive function. Br J Health Psychol 14, 489504.CrossRefGoogle ScholarPubMed
Dai, J, Cone, J & Moher, J (2020) Perceptual salience influences food choices independently of health and taste preferences. Cogn Res Princ Implic 5, 2.CrossRefGoogle ScholarPubMed
van't Riet, J, Sijtsema, SJ, Dagevos, H et al. (2011) The importance of habits in eating behaviour. An overview and recommendations for future research. Appetite 57, 585596.CrossRefGoogle ScholarPubMed
Bargh, J (1994) The four horsemen of automaticity: awareness, efficiency, intention, and control in social cognition. In Handbook of Social Cognition, 2nd ed. pp. 140 [Wyer, RS and Srull, TK, editors]. Hillsdale, NJ: Erlbaum Associates, Inc.Google Scholar
Robinson, E, Blissett, J & Higgs, S (2013) Social influences on eating: implications for nutritional interventions. Nutr Res Rev 26, 166176.CrossRefGoogle ScholarPubMed
Robinson, E, Thomas, J, Aveyard, P et al. (2014) What everyone else is eating: a systematic review and meta-analysis of the effect of informational eating norms on eating behavior. J Acad Nutr Diet 114, 414429.CrossRefGoogle ScholarPubMed
Higgs, S (2015) Social norms and their influence on eating behaviours. Appetite 86, 3844, Academic Press.CrossRefGoogle ScholarPubMed
Vartanian, LR, Spanos, S, Herman, CP et al. (2015) Modeling of food intake: a meta-analytic review. Soc Influ 10, 119136.CrossRefGoogle Scholar
Cruwys, T, Bevelander, KE & Hermans, RCJ (2015) Social modeling of eating: a review of when and why social influence affects food intake and choice. Appetite 86, 318.CrossRefGoogle Scholar
Ruddock, HK, Brunstrom, JM, Vartanian, LR et al. (2019) A systematic review and meta-analysis of the social facilitation of eating. Am J Clin Nutr 110, 842861.CrossRefGoogle ScholarPubMed
Christie, CD & Chen, FS (2018) Vegetarian or meat? Food choice modeling of main dishes occurs outside of awareness. Appetite 121, 5054.CrossRefGoogle ScholarPubMed
Barlow, P, Reeves, A, McKee, M et al. (2016) Unhealthy diets, obesity and time discounting: a systematic literature review and network analysis. Obes Rev 17, 810819.CrossRefGoogle ScholarPubMed
Fisher, G (2017) An attentional drift diffusion model over binary-attribute choice. Cognition 168, 3445.CrossRefGoogle ScholarPubMed
Krajbich, I, Lu, D, Camerer, C et al. (2012) The attentional drift-diffusion model extends to simple purchasing decisions. Front Psychol 3, 193.CrossRefGoogle ScholarPubMed
Kahneman, D (2003) Maps of bounded rationality: psychology for behavioral economics. Am Econ Rev 93, 14491475.CrossRefGoogle Scholar
Tversky, A & Kahneman, D (1974) Judgment under uncertainty: heuristics and biases. Science 185, 11241131.CrossRefGoogle ScholarPubMed
Cohen, DA & Babey, SH (2012) Contextual influences on eating behaviours: heuristic processing and dietary choices. Obes Rev 13, 766779.CrossRefGoogle ScholarPubMed
Stanovich, KE & West, RF (2000) Individual differences in reasoning: implications for the rationality debate? Behav Brain Sci 23, 645726.CrossRefGoogle ScholarPubMed
Kahneman, D (2011) Thinking, Fast and Slow. London, UK: Penguin.Google Scholar
Thaler, RH & Sunstein, CR (2008) Nudge: Improving Decisions about Health, Wealth, and Happiness. New Haven, CT, USA: Yale University Press.Google Scholar
Ensaff, H, Homer, M, Sahota, P et al. (2015) Food choice architecture: an intervention in a secondary school and its impact on students’ plant-based food choices. Nutrients 7, 44264437.CrossRefGoogle Scholar
Thaler, RH & Sunstein, CR (2003) Libertarian paternalism. Am Econ Rev 93, 175179.CrossRefGoogle Scholar
Blumenthal-Barby, JS & Burroughs, H (2012) Seeking better health care outcomes: the ethics of using the ‘nudge’. Am J Bioeth 12, 110.CrossRefGoogle Scholar
Michie, S & Johnston, M (2012) Theories and techniques of behaviour change: developing a cumulative science of behaviour change. Health Psychol Rev 6, 16.CrossRefGoogle Scholar
Maas, J, de Ridder, DTD, de Vet, E et al. (2012) Do distant foods decrease intake? The effect of food accessibility on consumption. Psychol Health 27, 5973.CrossRefGoogle ScholarPubMed
Hunter, JA, Hollands, GJ, Couturier, DL et al. (2018) Effect of snack-food proximity on intake in general population samples with higher and lower cognitive resource. Appetite 121, 337347.CrossRefGoogle ScholarPubMed
Knowles, D, Brown, K & Aldrovandi, S (2020) Exploring the roles of physical effort and visual salience within the proximity effect. Appetite 145, 104489.CrossRefGoogle ScholarPubMed
Privitera, GJ & Zuraikat, FM (2014) Proximity of foods in a competitive food environment influences consumption of a low calorie and a high calorie food. Appetite 76, 175179.CrossRefGoogle Scholar
Broers, VJV, De Breucker, C, Van den Broucke, S et al. (2017) A systematic review and meta-analysis of the effectiveness of nudging to increase fruit and vegetable choice. Eur J Public Health 27, 912920.CrossRefGoogle ScholarPubMed
Hollands, GJ, Carter, P, Anwer, S et al. . (2019) Altering the availability or proximity of food, alcohol, and tobacco products to change their selection and consumption. Cochrane Database Syst Rev, CD012573.CrossRefGoogle ScholarPubMed
Brunner, TA (2013) It takes some effort. How minimal physical effort reduces consumption volume. Appetite 71, 8994.CrossRefGoogle ScholarPubMed
Rozin, P, Scott, S, Dingley, M et al. (2011) Nudge to nobesity I: minor changes in accessibility decrease food intake. Judgm Decis Mak 6, 323332.Google Scholar
Tolman, EC (1932) Purposive Behavior in Animals and Men. New York: The Century Company.Google Scholar
Zipf, GK (1949) Human Behavior and the Principle of Least Effort: An Introduction to Human Ecology. Cambridge, MA: Addison-Wesley Press.Google Scholar
Bucher, T, Collins, C, Rollo, ME et al. (2016) Nudging consumers towards healthier choices: a systematic review of positional influences on food choice. Br J Nutr 115, 22522263.CrossRefGoogle ScholarPubMed
Hansen, PG, Skov, LR, Jespersen, AM et al. (2016) Apples versus brownies: a field experiment in rearranging conference snacking buffets to reduce short-term energy intake. J Foodserv Bus Res 19, 122130.CrossRefGoogle Scholar
Geier, AB, Rozin, P & Doros, G (2006) Unit bias: a new heuristic that helps explain the effect of portion size on food intake. Psychol Sci 17, 521525.CrossRefGoogle ScholarPubMed
Van Kleef, E, Vrijhof, M, Polet, IA et al. (2014) Nudging children towards whole wheat bread: a field experiment on the influence of fun bread roll shape on breakfast consumption. BMC Public Health 14, 906.CrossRefGoogle ScholarPubMed
Dayan, E & Bar-Hillel, M (2011) Nudge to nobesity II : menu positions influence food orders. Judgm Decis Mak 6, 333342.Google Scholar
Bacon, L & Krpan, D (2018) (Not) eating for the environment: the impact of restaurant menu design on vegetarian food choice. Appetite 125, 190200.CrossRefGoogle ScholarPubMed
Vennard, D, Park, T & Attwood, S (2019) Encouraging Sustainable Food Consumption by Using More-Appetizing Language, Technical Note. Washington, DC: World Resources Institute.Google Scholar
Ozdemir, B & Caliskan, O (2014) A review of literature on restaurant menus: specifying the managerial issues. Int J Gastron Food Sci 2, 313.CrossRefGoogle Scholar
Feldman, C, Mahadevan, M, Su, H et al. (2011) Menu engineering: a strategy for seniors to select healthier meals. Perspect Public Health 131, 267274.CrossRefGoogle Scholar
Bowen, JT & Morris, AJ (1995) Menu design: can menus sell? Int J Contemp Hosp Manag 7, 49.CrossRefGoogle Scholar
Stutts, MA, Zank, GM, Smith, KH et al. (2011) Nutrition information and children's fast food menu choices. J Consum Aff 45, 5286.CrossRefGoogle Scholar
Levin, S (1996) Pilot study of a cafeteria program relying primarily on symbols to promote healthy choices. J Nutr Educ Behav 28, 282285.CrossRefGoogle Scholar
Siegel, RM, Anneken, A, Duffy, C et al. (2015) Emoticon use increases plain milk and vegetable purchase in a school cafeteria without adversely affecting total milk purchase. Clin Ther 37, 19381943.CrossRefGoogle Scholar
Wagner, H, Howland, M & Mann, T (2015) Brief report: effects of subtle and explicit health messages on food choice. Health Psychol 34, 7982.CrossRefGoogle Scholar
Campbell-Arvai, V, Arvai, J & Kalof, L (2014) Motivating sustainable food choices: the role of nudges, value orientation, and information provision. Environ Behav 46, 453475.CrossRefGoogle Scholar
Samuelson, W & Zeckhauser, R (1988) Status quo bias in decision making. J Risk Uncertain 1, 759.CrossRefGoogle Scholar
Burger, JM, Bell, H, Harvey, K et al. (2010) Nutritious or delicious? The effect of descriptive norm information on food choice. J Soc Clin Psychol 29, 228242.CrossRefGoogle Scholar
Cruwys, T, Platow, MJ, Angullia, SA et al. (2012) Modeling of food intake is moderated by salient psychological group membership. Appetite 58, 754757.CrossRefGoogle ScholarPubMed
Meyers, AW, Stunkard, AJ & Coll, M (1980) Food accessibility and food choice. Arch Gen Psychiatry 37, 11331135.CrossRefGoogle ScholarPubMed
Pliner, P & Mann, N (2004) Influence of social norms and palatability on amount consumed and food choice. Appetite 42, 227237.CrossRefGoogle ScholarPubMed
Raghunathan, R, Naylor, RW & Hoyer, WD (2006) The unhealthy = tasty intuition and its effects on taste inferences, enjoyment, and choice of food products. J Mark 70, 170184.CrossRefGoogle Scholar
Spence, C (2020) Gastrophysics: nudging consumers toward eating more leafy (salad) greens. Food Qual Prefer 80, 103800.CrossRefGoogle Scholar
Michel, C, Velasco, C, Gatti, E et al. (2014) A taste of Kandinsky: assessing the influence of the artistic visual presentation of food on the dining experience. Flavour 3, 111.CrossRefGoogle Scholar
Searchinger, T, Waite, R, Hanson, C et al. (2019) Creating a Sustainable Food Future, A Menu of Solutions to Feed Nearly 10 Billion People by 2050. Washington, DC: World Resources Institute.Google Scholar
EAT-Lancet Commission (2019) Healthy Diets from Sustainable Food Systems – Summary Report. Stockholm, Sweden: EAT-Lancet Commission.Google Scholar
Satija, A & Hu, FB (2018) Plant-based diets and cardiovascular health. Trends Cardiovasc Med 28, 437441.CrossRefGoogle ScholarPubMed
Katz, DL & Meller, S (2014) Can we say what diet is best for health? Annu Rev Public Health 35, 83103, Annual Reviews.CrossRefGoogle ScholarPubMed
Song, M, Fung, TT, Hu, FB et al. (2016) Association of animal and plant protein intake with all-cause and cause-specific mortality. JAMA Intern Med 176, 14531463.CrossRefGoogle ScholarPubMed
Turnwald, BP, Boles, DZ & Crum, AJ (2017) Association between indulgent descriptions and vegetable consumption: twisted carrots and dynamite beets. JAMA Intern Med 177, 12161218.CrossRefGoogle ScholarPubMed
Visschers, VHM & Siegrist, M (2015) Does better for the environment mean less tasty? Offering more climate-friendly meals is good for the environment and customer satisfaction. Appetite 95, 475483.CrossRefGoogle ScholarPubMed
Szaszi, B, Palinkas, A, Palfi, B et al. (2018) A systematic scoping review of the choice architecture movement: toward understanding when and why nudges work. J Behav Decis Mak 31, 355366.CrossRefGoogle Scholar
Vandenbroele, J, Slabbinck, H, Van Kerckhove, A et al. (2019) Mock meat in the butchery: nudging consumers toward meat substitutes. Organ Behav Hum Decis Process [Epublication 24 September 2019].Google Scholar
Walsh, EM & Kiviniemi, MT (2014) Changing how I feel about the food: experimentally manipulated affective associations with fruits change fruit choice behaviors. J Behav Med 37, 322331.CrossRefGoogle Scholar
Kosīte, D, König, LM, De-loyde, K et al. (2019) Plate size and food consumption: a pre-registered experimental study in a general population sample. Int J Behav Nutr Phys Act 16, 75.CrossRefGoogle Scholar
Cadario, R & Chandon, P (2020) Which healthy eating nudges work best? A meta-analysis of field experiments. Mark Sci 39, 465486.CrossRefGoogle Scholar
Marcano-Olivier, MI, Horne, PJ, Viktor, S et al. (2020) Using nudges to promote healthy food choices in the school dining room: a systematic review of previous investigations. J Sch Health 90, 143157, Blackwell Publishing Ltd.CrossRefGoogle ScholarPubMed
Metcalfe, JJ, Ellison, B, Hamdi, N et al. (2020) A systematic review of school meal nudge interventions to improve youth food behaviors. Int J Behav Nutr Phys Act 17, 77. BioMed Central Ltd.CrossRefGoogle ScholarPubMed
Buscher, LA, Martin, KA & Crocker, S (2001) Point-of-purchase messages framed in terms of cost, convenience, taste, and energy improve healthful snack selection in a college foodservice setting. J Am Diet Assoc 101, 909913.CrossRefGoogle Scholar
Peterson, S, Duncan, DP, Null, DB et al. (2010) Positive changes in perceptions and selections of healthful foods by college students after a short-term point-of-selection intervention at a dining hall. J Am Coll Health 58, 425431.CrossRefGoogle Scholar
Allan, JL, Querstret, D, Banas, K et al. (2017) Environmental interventions for altering eating behaviours of employees in the workplace: a systematic review. Obes Rev 18, 214226.CrossRefGoogle ScholarPubMed
Al-Khudairy, L, Uthman, OA, Walmsley, R et al. (2019) Choice architecture interventions to improve diet and/or dietary behaviour by healthcare staff in high-income countries: a systematic review. BMJ Open 9, e023687.CrossRefGoogle ScholarPubMed
Nørnberg, TR, Houlby, L, Skov, LR et al. (2016) Choice architecture interventions for increased vegetable intake and behaviour change in a school setting: a systematic review. Perspect Public Health 136, 132142.CrossRefGoogle Scholar
Lycett, K, Miller, A, Knox, A et al. (2017) ‘Nudge’ interventions for improving children's dietary behaviors in the home: a systematic review. Obes Med 7, 2133.CrossRefGoogle Scholar
Roy, R, Kelly, B, Rangan, A et al. (2015) Food environment interventions to improve the dietary behavior of young adults in tertiary education settings: a systematic literature review. J Acad Nutr Diet 115, 16471681.CrossRefGoogle ScholarPubMed
Arno, A & Thomas, S (2016) The efficacy of nudge theory strategies in influencing adult dietary behaviour: a systematic review and meta-analysis. BMC Public Health 16, 676.CrossRefGoogle ScholarPubMed
Baldwin, R (2014) From regulation to behaviour change: giving nudge the third degree. Mod Law Rev 77, 831857.CrossRefGoogle Scholar
Sinclair, SE, Cooper, M & Mansfield, ED (2014) The influence of menu labeling on calories selected or consumed: a systematic review and meta-analysis. J Acad Nutr Diet 114, 13751388.CrossRefGoogle ScholarPubMed
Dolan, P, Hallsworth, M, Halpern, D et al. (2012) Influencing behaviour: the mindspace way. J Econ Psychol 33, 264277.CrossRefGoogle Scholar
The Behavioural Insights Team (2014) EAST: Four Simple Ways to Apply Behavioural Insights. London, UK: The Behavioural Insights Team.Google Scholar
Hollands, GJ, Shemilt, I, Marteau, TM et al. (2013) Altering micro-environments to change population health behaviour: towards an evidence base for choice architecture interventions. BMC Public Health 13, 1218.CrossRefGoogle ScholarPubMed
Hollands, GJ, Bignardi, G, Johnston, M et al. (2017) The TIPPME intervention typology for changing environments to change behaviour. Nat Hum Behav 1, 0140.CrossRefGoogle Scholar
Wilson, AL, Buckley, E, Buckley, JD et al. (2016) Nudging healthier food and beverage choices through salience and priming. Evidence from a systematic review. Food Qual Prefer 51, 4764.CrossRefGoogle Scholar
Skov, LR, Lourenço, S, Hansen, GL et al. (2013) Choice architecture as a means to change eating behaviour in self-service settings: a systematic review. Obes Rev 14, 187196.CrossRefGoogle ScholarPubMed
Blaga, OM, Vasilescu, L & Chereches, RM (2018) Use and effectiveness of behavioural economics in interventions for lifestyle risk factors of non-communicable diseases: a systematic review with policy implications. Perspect Public Health 138, 100110.CrossRefGoogle ScholarPubMed
Department of Health & Social Care (2020) Tackling obesity: empowering adults and children to live healthier lives. https://www.gov.uk/government/publications/tackling-obesity-government-strategy/tackling-obesity-empowering-adults-and-children-to-live-healthier-lives#what-next (accessed August 2020).Google Scholar
Junghans, AF, Cheung, TT & De Ridder, DD (2015) Under consumers’ scrutiny – an investigation into consumers’ attitudes and concerns about nudging in the realm of health behavior. Health policies, systems and management. BMC Public Health 15, 113.CrossRefGoogle Scholar
Evers, C, Marchiori, DR, Junghans, AF et al. (2018) Citizen approval of nudging interventions promoting healthy eating: the role of intrusiveness and trustworthiness. BMC Public Health 18, 1182.CrossRefGoogle ScholarPubMed
Reisch, LA, Sunstein, CR & Gwozdz, W (2017) Beyond carrots and sticks: Europeans support health nudges. Food Policy 69, 110.CrossRefGoogle Scholar
Kroese, FM, Marchiori, DR & De Ridder, DTD (2016) Nudging healthy food choices: a field experiment at the train station. J Public Health 38, e133e137.CrossRefGoogle ScholarPubMed
Bruns, H, Kantorowicz-Reznichenko, E, Klement, K et al. (2018) Can nudges be transparent and yet effective? J Econ Psychol 65, 4159.CrossRefGoogle Scholar
Cheung, TTL, Gillebaart, M, Kroese, FM et al. (2019) Cueing healthier alternatives for take-away: a field experiment on the effects of (disclosing) three nudges on food choices. BMC Public Health 19, 974.CrossRefGoogle ScholarPubMed
Wisdom, J, Downs, JS & Loewenstein, G (2010) Promoting healthy choices: information versus convenience. Am Econ J Appl Econ 2, 164178.CrossRefGoogle Scholar
Vermeer, WM, Steenhuis, IHM, Leeuwis, FH, et al. (2011) Small portion sizes in worksite cafeterias: do they help consumers to reduce their food intake. Int J Obes 35, 12001207.CrossRefGoogle ScholarPubMed
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Fig. 1. (Colour online) Nudge strategies implemented in choice architecture interventions to change food choice: reducing effort and cognitive load, increasing salience and emphasising tastiness and social norms.