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      Children's Perception of Food Marketing Across Digital Media Platforms

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          Highlights

          • Themes include identification, attitudes, and actions about food marketing.

          • Even if children are aware of food ads, children are still receptive to food ads.

          • Most parents reported that their children always or mostly knew what ads were.

          • More research is needed in a more diverse, larger sample with ad examples.

          Abstract

          Introduction

          Exposure to food marketing increases the risk of poor diet. Children's perception and interpretation of food marketing across digital media platforms is understudied. Children aged 9–11 years are uniquely susceptible to food marketing because children may watch content alone, and it is unclear whether embedded ads are decipherable by children (e.g., social media influencers) and if children are receptive to advertisements.

          Methods

          The authors collected data from 21 child–parent dyads in 2022 to fill this gap. Children were interviewed about their food marketing exposure and media use and were asked to share their perspectives on food advertisements. Parents completed a survey for household digital devices, demographics, and perception of their child's food advertising knowledge.

          Results

          This study found that all children generally recognized direct food advertisements, could describe them with varying levels of confidence, and shared examples. Despite self-identifying ads and understanding the intent of advertising, many children are still receptive to advertisements on the basis of engaging content (e.g., liking the ads as entertainment, watching ads even when given the chance to skip the ad) and the food items marketed (e.g., liking the taste of foods).

          Conclusions

          These findings suggest that knowledge of advertisement exposure and intent of advertising are not sufficient to reduce receptiveness of unhealthy food ad exposure. Additional research on the potential impacts of embedded ads, such as through social media influencers, is needed to understand children's interaction with the current digital media landscape.

          Related collections

          Most cited references30

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          Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support.

          Research electronic data capture (REDCap) is a novel workflow methodology and software solution designed for rapid development and deployment of electronic data capture tools to support clinical and translational research. We present: (1) a brief description of the REDCap metadata-driven software toolset; (2) detail concerning the capture and use of study-related metadata from scientific research teams; (3) measures of impact for REDCap; (4) details concerning a consortium network of domestic and international institutions collaborating on the project; and (5) strengths and limitations of the REDCap system. REDCap is currently supporting 286 translational research projects in a growing collaborative network including 27 active partner institutions.
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            The REDCap consortium: Building an international community of software platform partners

            The Research Electronic Data Capture (REDCap) data management platform was developed in 2004 to address an institutional need at Vanderbilt University, then shared with a limited number of adopting sites beginning in 2006. Given bi-directional benefit in early sharing experiments, we created a broader consortium sharing and support model for any academic, non-profit, or government partner wishing to adopt the software. Our sharing framework and consortium-based support model have evolved over time along with the size of the consortium (currently more than 3200 REDCap partners across 128 countries). While the "REDCap Consortium" model represents only one example of how to build and disseminate a software platform, lessons learned from our approach may assist other research institutions seeking to build and disseminate innovative technologies.
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              Ultra-processed foods: what they are and how to identify them

              The present commentary contains a clear and simple guide designed to identify ultra-processed foods. It responds to the growing interest in ultra-processed foods among policy makers, academic researchers, health professionals, journalists and consumers concerned to devise policies, investigate dietary patterns, advise people, prepare media coverage, and when buying food and checking labels in shops or at home. Ultra-processed foods are defined within the NOVA classification system, which groups foods according to the extent and purpose of industrial processing. Processes enabling the manufacture of ultra-processed foods include the fractioning of whole foods into substances, chemical modifications of these substances, assembly of unmodified and modified food substances, frequent use of cosmetic additives and sophisticated packaging. Processes and ingredients used to manufacture ultra-processed foods are designed to create highly profitable (low-cost ingredients, long shelf-life, emphatic branding), convenient (ready-to-consume), hyper-palatable products liable to displace all other NOVA food groups, notably unprocessed or minimally processed foods. A practical way to identify an ultra-processed product is to check to see if its list of ingredients contains at least one item characteristic of the NOVA ultra-processed food group, which is to say, either food substances never or rarely used in kitchens (such as high-fructose corn syrup, hydrogenated or interesterified oils, and hydrolysed proteins), or classes of additives designed to make the final product palatable or more appealing (such as flavours, flavour enhancers, colours, emulsifiers, emulsifying salts, sweeteners, thickeners, and anti-foaming, bulking, carbonating, foaming, gelling and glazing agents).
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                Author and article information

                Contributors
                Journal
                AJPM Focus
                AJPM Focus
                AJPM Focus
                Elsevier
                2773-0654
                11 February 2024
                June 2024
                11 February 2024
                : 3
                : 3
                : 100205
                Affiliations
                [1 ]Department of Biostatistics and Epidemiology, School of Public Health & Health Sciences, University of Massachusetts Amherst, Amherst, Massachusetts
                [2 ]Department of Biomedical Data Sciences, Geisel School of Medicine, Dartmouth College, Hanover, New Hampshire
                [3 ]Department of Pediatrics, Geisel School of Medicine, Dartmouth College, Hanover, New Hamsphire
                [4 ]Department of Student Development, College of Education, University of Massachusetts Amherst, Amherst, Massachusetts
                [5 ]Department of Health Promotion and Policy, School of Public Health & Health Sciences, University of Massachusetts Amherst, Amherst, Massachusetts
                Author notes
                [* ]Address correspondence to: Jennifer E. Carroll, PhD, Department of Epidemiology, School of Public Health & Health Sciences, University of Massachusetts Amherst, Arnold House, 715 North Pleasant Street, 4 th floor, Amherst MA 01003. jecarroll@ 123456umass.edu
                Article
                S2773-0654(24)00024-5 100205
                10.1016/j.focus.2024.100205
                10981009
                38560403
                d70bda6a-def8-4a83-aaf9-f3ae76ad4e57
                © 2024 The Author(s)

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                Categories
                Research Article

                children,media use,food advertising,qualitative
                children, media use, food advertising, qualitative

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