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A 2-Phase Labeling and Choice Architecture Intervention to Improve Healthy Food and Beverage Choices
Open accessAbstract
Objectives. We assessed whether a 2-phase labeling and choice architecture intervention would increase sales of healthy food and beverages in a large hospital cafeteria. Methods. Phase 1 was a 3-month color-coded labeling intervention (red = unhealthy, yellow = less healthy, green = healthy). Phase 2 added a 3-month choice architecture intervention that increased the visibility and convenience of some green items. We compared relative changes in 3-month sales from baseline to phase 1 and from phase 1 to phase 2. Results. At baseline (977 793 items, including 199 513 beverages), 24.9% of sales were red and 42.2% were green. Sales of red items decreased in both phases (P < .001), and green items increased in phase 1 (P < .001). The largest changes occurred among beverages. Red beverages decreased 16.5% during phase 1 (P < .001) and further decreased 11.4% in phase 2 (P < .001). Green beverages increased 9.6% in phase 1 (P < .001) and further increased 4.0% in phase 2 (P < .001). Bottled water increased 25.8% during phase 2 (P < .001) but did not increase at 2 on-site comparison cafeterias (P < .001). Conclusions. A color-coded labeling intervention improved sales of healthy items and was enhanced by a choice architecture intervention.
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“While behavioral economic approaches have been examined for school lunch programs, nutrition assistance programs, and hospital cafeterias (Just, Mancino, and Wansink 2007; Thorndike et al. 2012), few studies have examined healthy defaults as applied to food selection in different types of restaurants.”
From Using Healthy Defaults in Walt Disney World Restaurants to Improve Nutritional Choices (2016) · cites this paper as Thorndike et al. 2012
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Bevet, S., Niles, M. T., & Pope, L. (2018) · PLoS ONE · doi:10.1371/journal.pone.0198162 · Cited by 18
Ruiter, R. A. C., Crutzen, R., de Leeuw, E., & Kok, G. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108677318.018 · Cited by 20
“I’ll have what he’s having”: Group ordering behavior in food choice decisions
Ellison, B. (2014) · Food Quality and Preference · doi:10.1016/j.foodqual.2014.04.012 · Cited by 18
Metadata
- Authors
- Thorndike, A. N., Sonnenberg, L., Riis, J., Barraclough, S., & Levy, D. E.
- Affiliations
- Harvard University (US)
- Venue
- American Journal of Public Health
- Publisher
- American Public Health Association
- Published
- 2012-03
- Volume
- 102
- Issue
- 3
- Pages
- 527-533
- ISSN
- 0090-0036 (ISSN-L)
- 1541-0048
- PMC
- PMC3329221
- OpenAlex
- W2118495149
- Cited by
- 405
- References
- 26
- Citations by year
- 2026: 6 · 2025: 16 · 2024: 18 · 2023: 15 · 2022: 19 · 2021: 28 · 2020: 76 · 2019: 42 · 2018: 22 · 2017: 30 · 2016: 35 · 2015: 40 · 2014: 25 · 2013: 22 · 2012: 9
- FWCI
- 29.67
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- American Journal of Public Health (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- American Heart Association
- Massachusetts General Hospital
- Harvard Catalyst
- National Institutes of Health
- National Heart, Lung, and Blood Institute (K23HL093221, 1 K23HL93221)
- National Center for Research Resources (UL1RR025758)
- Topics
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Consumer Attitudes and Food Labeling
- Health Sciences › Nursing › Nutrition and Dietetics › Nutrition, Health and Food Behavior
- Social Sciences › Psychology › Applied Psychology › Behavioral Health and Interventions
- Keywords
- choice architecture, hospital cafeterias, bottled water consumption, food environment
- MeSH terms
- Beverages, Boston, Choice Behavior, Color, Food, Food Service, Hospital, Hospitals, General, Humans, Male, Product Labeling
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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