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Effect of default menus on food selection and consumption in a college dining hall simulation study

  • Cynthia Radnitz (a1), Katharine L Loeb (a1), Kathleen L Keller (a2), Kerri Boutelle (a3), Marlene B Schwartz (a4), Lauren Todd (a1) and Sue Marcus (a5)...

To test an obesity prevention strategy derived from behavioural economics (optimal defaults plus delay), focused on changing the college dining hall service method.


After a uniform pre-load, participants attended an experimental lunch in groups randomized to one of three conditions: a nutrient-dense, lower-fat/energy lunch as an optimal default (OD); a less-nutrient-dense, higher-fat/energy lunch as a suboptimal default (SD); or a free array (FA) lunch. In the OD condition, students were presented a menu depicting healthier vegetarian and omnivore foods as default, with opt-out alternatives (SD menu) available on request with a 15 min wait. In the SD condition, the same menu format was used with the positioning of food items switched. In the FA condition, all choices were presented in uniform fonts and were available immediately.


Private rooms designed to provide a small version of a college dining hall, on two campuses of a Northeastern US university.


First-year college students (n 129).


There was a significant main effect for condition on percentage of optimal choices selected, with 94 % of food choices in the OD condition optimal, 47 % in the FA condition optimal and none in the SD condition optimal. Similarly, energy intake for those in the SD condition significantly exceeded that in the FA condition, which exceeded that in the OD condition.


Presenting menu items as optimal defaults with a delay had a significant impact on choice and consumption, suggesting that further research into its long-term applicability is warranted.

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1. Deforche, B, Van Dyck, D & Deliens, T (2015) Changes in weight, physical activity, sedentary behaviour and dietary intake during the transition to higher education: a prospective study. Int J Behav Nutr Phys Act 12, 16.
2. Finlayson, G, Cecil, J, Higgs, S et al. (2012) Susceptibility to weight gain. Eating behaviour traits and physical activity as predictors of weight gain during the first year of university. Appetite 58, 10911098.
3. Serlachius, A, Hamer, M & Wardle, J (2007) Stress and weight change in university students in the United Kingdom. Physiol Behav 92, 548553.
4. Vadeboncoeur, C, Townsend, N & Foster, C (2015) A meta-analysis of weight gain in first year university students: is freshman 15 a myth? BMC Obes 2, 22.
5. Gropper, SS, Newton, A, Harrington, P et al. (2011) Body composition changes during the first two years of university. Prev Med 52, 2022.
6. Hivert, M-F, Langlois, M-F, Bérard, P et al. (2007) Prevention of weight gain in young adults through a seminar-based intervention program. Int J Obes (Lond) 31, 12621269.
7. Matvienko, O, Lewis, DS & Schafer, E (2001) A college nutrition science course as an intervention to prevent weight gain in female college freshmen. J Nutr Educ 33, 95101.
8. Stice, E, Rohde, P, Shaw, H et al. (2012) Efficacy trial of a selective prevention program targeting both eating disorder symptoms and unhealthy weight gain among female college students. J Consult Clin Psychol 80, 164170.
9. Cioffi, CE, Levitsky, DA, Pacanowski, CR et al. (2015) A nudge in a healthy direction. The effects of nutrition labels on food purchasing behaviors in university dining facilities. Appetite 92, 714.
10. Stroebele, N, Ogden, LG & Hill, JO (2009) Do calorie-controlled portion sizes of snacks reduce energy intake? Appetite 52, 793796.
11. Wansink, B, Ittersum, KV & Painter, J (2006) Ice cream illusions: bowls, spoons, and self-served portion sizes. Am J Prev Med 31, 240243.
12. Radnitz, C, Loeb, KL, DiMatteo, J et al. (2013) Optimal defaults in the prevention of pediatric obesity: from platform to practice. J Food Nutr Disord 2, 1.
13. Thiagarajah, K & Getty, VM (2013) Impact on plate waste of switching from a tray to a trayless delivery system in a university dining hall and employee response to the switch. J Acad Nutr Diet 113, 141145.
14. Just, D & Wansink, B (2009) Smarter lunchrooms: using behavioral economics to improve meal selection. Choices 24, issue 3, 17.
15. Thaler, RH, Sunstein, CR & Balz, JP (2010) Choice architecture. Soc Sci Res Netw Electron J, 117; available at
16. 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.
17. Carroll, GD, Choi, JJ, Laibson, D et al. (2009) Optimal defaults and active decisions. Q J Econ 124, 16391674.
18. Dhingra, N, Gorn, Z, Kener, A et al. (2012) The default pull: an experimental demonstration of subtle default effects on preferences. Judgm Decis Mak 7, 6976.
19. Camerer, C (2004) Prospect theory in the wild: evidence from the field. In Advances in Behavioral Economics, pp. 148161 [C Camerer, G Loewenstein and M Rabin, editors]. New York: Princeton University Press.
20. Kahneman, D, Knetsch, JL & Thaler, RH (1991) Anomalies: the endowment effect, loss aversion, and status quo bias. J Econ Perspect 5, 193206.
21. McKenzie, CRM, Liersch, MJ & Finkelstein, SR (2006) Recommendations implicit in policy defaults. Psychol Sci 17, 414420.
22. Sher, S & McKenzie, CRM (2006) Information leakage from logically equivalent frames. Cognition 101, 467494.
23. Madrian, B & Shea, D (2000) The power of suggestion: inertia in 401(k) participation and savings behavior. Q J Econ 116, 11491187.
24. Johnson, EJ & Goldstein, D (2003) Do defaults save lives? Science 302, 13381339.
25. Chandisarewa, W, Stranix-Chibanda, L, Chirapa, E et al. (2007) Routine offer of antenatal HIV testing (‘opt-out’ approach) to prevent mother-to-child transmission of HIV in urban Zimbabwe. Bull World Health Organ 85, 843850.
26. Chapman, GB, Li, M, Colby, H et al. (2010) Opting in vs opting out of influenza vaccination. JAMA 304, 4344.
27. Patel, MS, Day, S, Small, DS et al. (2014) Using default options within the electronic health record to increase the prescribing of generic-equivalent medications: a quasi-experimental study. Ann Intern Med 161, 10 Suppl., S44S52.
28. Walmsley, S (2003) Opt in or opt out: What is optimal qfor prenatal screening for HIV infection? CMAJ 168, 707708.
29. Anzman-Frasca, S, Mueller, MP, Sliwa, S et al. (2015) Changes in children’s meal orders following healthy menu modifications at a regional US restaurant chain. Obesity (Silver Spring) 23, 10551062.
30. Peters, J, Beck, J, Lande, J et al. (2016) Using healthy defaults in Walt Disney World restaurants to improve nutritional choices. J Assoc Consum Res 1, 92103.
31. Wansink, B & Hanks, A (2014) Calorie reductions and within‐meal calorie compensation in children’s meal combos. Obesity (Silver Spring) 22, 630632.
32. Dalrymple, J, Radnitz, C, Loeb, KL et al. (2016) Optimal defaults as a strategy to improve children’s menu selections in a full-service restaurant. Paper presented at the 50th Annual Convention of the Association for Behavioral and Cognitive Therapies, New York, NY, USA, 27–30 October 2016.
33. Downs, JS, Loewenstein, G & Wisdom, J (2009) Strategies for promoting healthier food choices on JSTOR. Am Econ Rev 99, 159164.
34. Wisdom, J, Downs, JS & Loewenstein, G (2010) Promoting healthy choices: information versus convenience. Am Econ J Appl Econ 2, 164178.
35. Loeb, KL, Radnitz, C, Keller, K et al. (2017) The application of defaults to optimize parents’ health-based choices for children. Appetite 113, 368375.
36. Loeb, KL, Radnitz, C, Keller, KL et al. (2018) The application of optimal defaults to improve elementary school lunch selections: proof-of-concept. J Sch Health (In the Press).
37. DiMatteo, J, Radnitz, CL & Loeb, KL (2016) The application of optimal defaults to physical education in college students. Paper presented at the 50th Annual Convention of the Association for Behavioral and Cognitive Therapies, New York, NY, USA, 27–30 October 2016.
38. Hollands, G, Shemilt, I, Marteau, TM J et al. (2013) Altering micro-environments to change population health behaviour: towards an evidence base for choice architecture interventions. BMC Public Health 13, 1218.
39. Epstein, LH, Salvy, SJ, Carr, KA et al. (2010) Food reinforcement, delay discounting and obesity. Physiol Behav 100, 438445.
40. Mischel, W, Shoda, Y & Rodriguez, ML (1989) Delay of gratification in children. Science 244, 933937.
41. Davis, C, Patte, K, Curtis, C et al. (2010) Immediate pleasures and future consequences. A neuropsychological study of binge eating and obesity. Appetite 54, 208213.
42. Weller, RE, Cook, EW, Avsar, KB et al. (2008) Obese women show greater delay discounting than healthy-weight women. Appetite 51, 563569.
43. Appelhans, BM, Woolf, K, Pagoto, SL et al. (2011) Inhibiting food reward: delay discounting, food reward sensitivity, and palatable food intake in overweight and obese women. Obesity (Silver Spring) 19, 21752182.
44. Rollins, BY, Dearing, KK & Epstein, LH (2010) Delay discounting moderates the effect of food reinforcement on energy intake among non-obese women. Appetite 55, 420425.
45. American Health Association (2017) The American Heart Association’s diet and lifestyle recommendations. (accessed August 2017).
46. Centers for Disease Control & Prevention (2016) BMI Percentile Calculator for Child and Teen English Version. (accessed November 2015).
47. Simmen, B, Pasquet, P & Hladik, CM (2004) Methods for assessing taste abilities and hedonic responses in human and non-human primates. In Researching Food Habits: Methods and Problems, pp. 8799 [H Macbeth and J MacClancy, editors]. Oxford: Berghahn Books.
48. Smiciklas-Wright, H, Mitchell, DC, Mickle, SJ et al. (2003) Foods commonly eaten in the United States, 1989–1991 and 1994–1996: are portion sizes changing? J Am Diet Assoc 103, 4147.
49. McCluskey, JJ, Mittelhammer, RC & Asiseh, F (2012) From default to choice: adding healthy options to kids’ menus. Am J Agric Econ 94, 338343.
50. Rolls, B (2009) The relationship between dietary energy density and energy intake. Physiol Behav 97, 609615.
51. Glanz, K, Basil, M, Maibach, E et al. (1998) Why Americans eat what they do: taste, nutrition, cost, convenience, and weight control concerns as influences on food consumption. J Am Diet Assoc 98, 11181126.
52. Marquis, M (2005) Exploring convenience orientation as a food motivation for college students living in residence halls. Int J Consum Stud 29, 5563.
53. Riddell, LJ, Ang, B, Keast, RSJ et al. (2011) Impact of living arrangements and nationality on food habits and nutrient intakes in young adults. Appetite 56, 726731.
54. Institute of Medicine (2002) Dietary Reference Intakes for Energy, Carbohydrate, Fiber, Fat, Fatty Acids, Cholesterol, Protein and Amino Acids. Washington, DC: The National Academies Press.
55. Rasmussen, M, Krølner, R, Klepp, KI et al. (2006) Determinants of fruit and vegetable consumption among children and adolescents: a review of the literature. Part I: quantitative studies. Int J Behav Nutr Phys Act 3, 22.
56. de Graaf, C, Kramer, FM, Meiselman, HL et al. (2005) Food acceptability in field studies with US army men and women: relationship with food intake and food choice after repeated exposures. Appetite 44, 2331.
57. MRC Cognition and Brain Sciences Unit (2017) Rules of Thumb on Magnitudes of Effect Sizes. (accessed August 2017).
58. Almy, J & Wootan, MG (2015) Temptation at Checkout: The Food Industry’s Sneaky Strategy for Selling More. Washington, DC: Center for Science in the Public Interest; available at
59. Van Kleef, E, Otten, K & van Trijp, HCM (2012) Healthy snacks at the checkout counter: a lab and field study on the impact of shelf arrangement and assortment structure on consumer choices. BMC Public Health 12, 1072.
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