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A comparative assessment of two different front-of-package nutrition label designs: A randomized experiment in Brazil
This study compares the effectiveness of different front-of-package label designs in a Brazilian sample (n = 1384). Eligible adults were randomized to one of two study arms and viewed images of snacks with either a triangular warning label (TL) or a rectangular ‘high in’ label with a magnifying glas...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8985949/ https://www.ncbi.nlm.nih.gov/pubmed/35385504 http://dx.doi.org/10.1371/journal.pone.0265990 |
Sumario: | This study compares the effectiveness of different front-of-package label designs in a Brazilian sample (n = 1384). Eligible adults were randomized to one of two study arms and viewed images of snacks with either a triangular warning label (TL) or a rectangular ‘high in’ label with a magnifying glass (ML). They responded to a series of questions that captured label usefulness, understanding, and purchase intentions. Compared to participants in the ML arm, those in the TL arm agreed that the TL communicated important information [Mean (SD) - 5.47 (0.07) vs 4.49 (0.08), p-value <0.001], was a useful tool [Mean (SD) - 6.12 (0.06) vs 5.75 (0.07), p-value <0.001], and was easier to understand as measured subjectively [Mean (SD) - 4.96 (0.07) vs 4.44 (0.08), p-value <0.001]. However, both the TL and the ML performed similarly in communicating nutrient information as measured by the objective understanding of nutrient content [57.09% vs 54.65%, p-value 0.259]. The ML performed marginally better at improving purchase intentions [Mean (SD) - 2.57 (0.07) vs 2.79 (0.08), p-value <0.049]. The current study adds to the growing evidence base on the pathways through which FoP labels, particularly ‘high in’ labels, might influence consumer perceptions and behavior. It is also one of the first studies to provide evidence on the utility of the ML design for Brazil. |
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