Consumer Reactions to Positive and Negative Front-of-Package Food Labels

消费者对食品包装正面标签(正面和负面)的反应

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Abstract

INTRODUCTION: The National Academy of Medicine recommends that the U.S. adopt an interpretative front-of-package food labeling system, but uncertainty remains about how this system should be designed. This study examined reactions to front-of-package food labeling systems that use positive labels to identify healthier foods, negative labels to identify unhealthier foods, or both. METHODS: In August 2021, U.S. adults (N=3,051) completed an online randomized experiment. Participants were randomly assigned to 1 of 4 labeling conditions: control (calorie), positive, negative, or both positive and negative labels. Labels were adapted from designs for a 'healthy' label drafted by the Food and Drug Administration and displayed on the front of product packaging. Participants selected products to purchase, identified healthier products, and reported reactions to the labels. Analyses, conducted in 2022, examined the healthfulness of participants' selections using the Ofcom Nutrient Profiling Model score (0-100, higher scores indicate being healthier). RESULTS: Participants exposed to only positive labels, only negative labels, or both positive and negative labels had healthier selections than participants in the control arm (differences vs control=1.13 [2%], 2.34 [4%] vs 3.19 [5%], respectively; all p<0.01). The both-positive-and-negative-labels arm outperformed the only-negative-labels (p=0.03) and only-positive-labels (p<0.001) arms. The only-negative-labels arm outperformed the only-positive-labels arm (p=0.005). All the 3 interpretative labeling systems also led to improvements in the identification of healthier products and beneficial psychological reactions (e.g., attention, thinking about health effects; all p<0.05). CONCLUSIONS: Front-of-package food labeling systems that use both positive and negative labels could encourage healthier purchases and improve understanding more than systems using only positive or only negative labels.

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