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Lookup NU author(s): Remco Benthem De GraveORCiD, Dr Christopher BullORCiD, Dr Diogo Monjardino De Souza Monteiro, Dr Lenia MargaritiORCiD, Gareth McMurchy, Joseph Hutchinson, Dr Jan SmeddinckORCiD
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
Background: Smartphone apps can aid consumers in making healthier and more sustainable food purchases. However, there is still a limited understanding of the different app design approaches and their impact on food purchase choices. An overview of existing food purchase choice apps and an understanding of common challenges can help speed up effective future developments.Objective: We examined the academic literature on food purchase choice apps and provided an overview of the design characteristics, opportunities, and challenges for effective implementation. Thus, we contribute to an understanding of how technologies can effectively improve food purchase choice behavior and provide recommendations for future design efforts.Methods: Following the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines, we considered peer-reviewed literature on food purchase choice apps within IEEE Xplore, PubMed, Scopus, and ScienceDirect. We inductively coded and summarized design characteristics. Opportunities and challenges were addressed from both quantitative and qualitative perspectives. From the quantitative perspective, we coded and summarized outcomes of comparative evaluation trials. From the qualitative perspective, we performed a qualitative content analysis of commonly discussed opportunities and challenges.Results: We retrieved 55 articles, identified 46 unique apps, and grouped them into 5 distinct app types. Each app type supports a specific purchase choice stage and shares a common functional design. Most apps support the product selection stage (selection apps; 27/46, 59%), commonly by scanning the barcode and displaying a nutritional rating. In total, 73% (8/11) of the evaluation trials reported significant findings and indicated the potential of food purchase choice apps to support behavior change. However, relatively few evaluations covered the selection app type, and these studies showed mixed results. We found a common opportunity in apps contributing to learning (knowledge gain), whereas infrequent engagement presents a common challenge. The latter was associated with perceived burden of use, trust, and performance as well as with learning. In addition, there were technical challenges in establishing comprehensive product information databases or achieving performance accuracy with advanced identification methods such as image recognition.Conclusions: Our findings suggest that designs of food purchase choice apps do not encourage repeated use or long-term adoption, compromising the effectiveness of behavior change through nudging. However, we found that smartphone apps can enhance learning, which plays an important role in behavior change. Compared with nudging as a mechanism for behavior change, this mechanism is less dependent on continued use. We argue that designs that optimize for learning within each interaction have a better chance of achieving behavior change. This review concludes with design recommendations, suggesting that food purchase choice app designers anticipate the possibility of early abandonment as part of their design process and design apps that optimize the learning experience.
Author(s): Benthem de Grave R, Bull CN, Souza-Monteiro DM, Margariti E, McMurchy G, Hutchinson JW, Smeddinck JD
Publication type: Article
Publication status: Published
Journal: JMIR
Year: 2024
Volume: 26
Print publication date: 06/03/2024
Online publication date: 14/02/2024
Acceptance date: 20/12/2023
Date deposited: 19/03/2024
ISSN (electronic): 1438-8871
Publisher: JMIR Publications, Inc.
URL: https://doi.org/10.2196/45904
DOI: 10.2196/45904
Data Access Statement: All data generated or analyzed during this study are included in this published article and its supplementary information files
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