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Association Between Indulgent Descriptions and Vegetable Consumption: Twisted Carrots and Dynamite Beets
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This observational study examines the association of labeling vegetables with indulgent descriptions and overall vegetable consumption compared with labeling vegetables with basic or health-focused labels.
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“Initial evidence suggests that taste-focused labeling leads more people to choose vegetables than health-focused and basic (nondescriptive) labels do (Turnwald, Boles, & Crum, 2017; Turnwald & Crum, 2019)”
From Increasing Vegetable Intake by Emphasizing Tasty and Enjoyable Attributes: A Randomized Controlled Multisite Intervention for Taste-Focused Labeling (2019) · cites this paper as Turnwald, Boles, & Crum, 2017
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Metadata
- Authors
- Turnwald, B. P., Boles, D. Z., & Crum, A. J.
- Affiliations
- Stanford University (US)
- Corresponding author
- Turnwald, Bradley P.
- Venue
- JAMA Internal Medicine
- Publisher
- American Medical Association (AMA)
- Published
- 2017-08-01
- Volume
- 177
- Issue
- 8
- Pages
- 1216
- ISSN
- 2168-6106 (ISSN-L)
- PMC
- PMC5818791
- OpenAlex
- W2622599536
- Cited by
- 128
- References
- 6
- Citations by year
- 2026: 4 · 2025: 11 · 2024: 13 · 2023: 11 · 2022: 26 · 2021: 12 · 2020: 17 · 2019: 11 · 2018: 17 · 2017: 6
- FWCI
- 13.10
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- JAMA Internal Medicine (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- 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 › Communication › Media Influence and Health
- Keywords
- vegetable consumption, food labeling, food marketing
- MeSH terms
- Vegetable Products, Diet, Healthy, Choice Behavior, Feeding Behavior, Food Labeling, Health Promotion, Humans
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.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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