Use of digital tools in nutritional management in pediatrics and adolescent medicine
DOI:
https://doi.org/10.15343/0104-7809.202549e17602025IKeywords:
Technological Systems, Nutrition, Child Feeding, Adolescent NutritionAbstract
The advancement of digital technologies has transformed the healthcare field, offering new possibilities for behavioral interventions and health promotion. In nutrition, these tools have been applied to support dietary management among children and adolescents, with the potential to personalize care and enhance engagement. The aim of this study was to analyze the use of digital tools as part of nutritional care for children and adolescents. A narrative literature review was conducted through searches in the MEDLINE/PubMed, Scielo, and Bireme databases, including studies published in the past ten years in Portuguese, English, and Spanish. Systematic reviews, meta-analyses, and full studies on child and adolescent nutrition associated with digital technologies were included. Of the 170 articles retrieved, 17 were selected. The use of mobile applications, digital games, telehealth platforms, and exergames was identified in the prevention and treatment of childhood obesity, promotion of breastfeeding, diet therapy for specific clinical conditions, and nutrition education. Evidence indicates that these tools have the potential to personalize interventions, monitor dietary intake and physical activity, and support clinical decision-making. Despite their promise, challenges remain, including digital access inequality, the need for scientific validation, child and family adherence, data privacy and security, and ethical limitations in the use of Artificial Intelligence in pediatric populations. Digital technologies show promising potential for nutritional support in children and adolescents, with the ability to enhance intervention effectiveness. However, further studies are needed to assess long-term impacts, ensure ethical safety, and strengthen the integration of these solutions into clinical practice.
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This article is a translation in English of the article:
Uso de ferramentas digitais no manejo nutricional em pediatria e hebiatria
References
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Danziato-Neto MA, Caldas PSS, Rêgo JMC, Carioca AAF, Câmara CRS. Relationship between ultrasound measurement of quadriceps muscle and nutritional status in ICU patients in a high-complexity trauma care hospital. Rev Nutr. 2024;37:e240005. doi:10.1590/1678-9865202437e240005
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Estecha-Querol S, Fleming CAK, Samnani AA, Cameseria MJ, Chowdhury D, Kehoe S, et al. Identifying key components of a global conceptual framework for adolescent nutrition: Review, nominal group technique and youth co-design. BMJ Glob Health. 2025;10(6):e016167. doi:10.1136/ bmjgh-2024-016167
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Henriques I. Inteligência Artificial e publicidade dirigida a crianças e adolescentes. Internet & Sociedade. 2021;2(2):5-25.
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Zeigler VL. Ethical considerations in pediatric critical care research. Crit Care Nurs Clin North Am. 2011;23(2):377-84. doi:10.1016/j.ccell.2011.04.005
Parvez SM, Azad R, Rahman M, Unicomb L, Ram PK, Naser AM, et al. Achieving optimal technology and behavioral uptake of single and combined interventions of water, sanitation hygiene and nutrition, in an efficacy trial (WASH benefits) in rural Bangladesh. Trials. 2018;19(1):358. doi:10.1186/ s13063-018-2710-8
Alcântara CM, Silva ANS, Pinheiro PNC, Queiroz MVO. Digital technologies for promotion of healthy eating habits in teenagers. Rev Bras Enferm. 2019;72(2):513-20. doi:10.1590/0034-7167-2018-0352
World Health Organization. Global strategy on digital health 2020–2025. Geneva: WHO; 2021. Licence: CC BY-NC-SA 3.0 IGO.
Chai LK, Collins CE, May C, Brown LJ, Ashman A, Burrows TL. Fidelity and acceptability of a family-focused technology-based telehealth nutrition intervention for child weight management. J Telemed Telecare. 2021;27(2):98-109. doi:10.1177/1357633X19864819
Till S, Mkhize M, Farao J, Shandu LD, Muthelo L, Coleman TL, et al; CoMaCH Network. Digital health technologies for maternal and child health in Africa and other low- and middle-income countries: Cross-disciplinary scoping review with stakeholder consultation. J Med Internet Res. 2023;25:e42161. doi:10.2196/42161
Meneses AB, Melo GRA, Lima SC, Toral N. Memorization of messages, satisfaction, and feasibility of a nutritional intervention using a mobile text messaging app among adolescents. Rev Nutr. 2022;35:e210186. doi:10.1590/1678-9865202235e210186
Pervanidou P, Chatzidaki E, Nicolaides NC, Voutetakis A, Polychronaki N, Chioti V, et al. The impact of the ENDORSE digital weight management program on the metabolic profile of children and adolescents with overweight and obesity and on food parenting practices. Nutrients. 2023;15(7):1777. doi:10.3390/nu15071777
Sudré GA, da Silva Vergilio HA, de Jesus L, Sudré MRS. Estudo da Implantação das Tecnologias de Informação na área da Saúde em Enfermagem: uma revisão integrativa de literatura. J Health Inform [Internet]. [cited 2024 Dec 10]. Available from: https://jhi.sbis.org.br/index.php/jhi-sbis/article/view/588
Reis LA. SANEP-Sistema Especialista Probabilístico de Apoio a Nutrição Enteral Pediátrica [Internet]. Florianópolis: Universidade Federal de Santa Catarina; 2001 [cited 2024 Dec 10]. Available from: https://core.ac.uk/download/pdf/30360597.pdf
Vasconcelos Filho JE, Lamboglia CMGF, Carvalho LM. Missão kid: um exergame de apoio ao combate a obesidade infantil. J Health Inform [Internet]. 2016 [cited 2024 Dec 10];8:809-18. Available from: https://pesquisa.bvsalud.org/gim/resource/ru/biblio-906621
Wu J, Dong L, Sun Y, Zhao X, Gan J, Wang Z. The effectiveness of artificial intelligence in assisting mothers with assessing infant stool consistency in a breastfeeding cohort study in China. Nutrients. 2024;16(6):855. doi:10.3390/nu16060855
Elias MA, Faversani LA, Moreira JAV, Masiero AV, Cunha NV. Inteligência artificial em saúde e implicações bioéticas: uma revisão sistemática. Rev Bioét. 2023;31. doi:10.1590/1983-803420233542ES
Henriques I. Inteligência Artificial e publicidade dirigida a crianças e adolescentes. Internet & Sociedade. 2021;2(2):5-25.
Dourado DA. Regulação da inteligência artificial na saúde. São Paulo: Universidade de São Paulo; 2024.
Zahid M, Ume Sughra. Development of a protocol for conducting a randomized control trial on effects of artificial intelligence on nutritional status of children post cardiac surgery. J Pak Med Assoc. 2022;72(5):908-11.
Lara-Mejía V, Franco-Lares B, Lozada-Tequeanes AL, Villanueva-Vázquez C, Hernández-Cordero S. Methodologies for monitoring the digital marketing of foods and beverages aimed at infants, children, and adolescents (ICA): A scoping review. Int J Environ Res Public Health. 2022;19(15):8951. doi:10.3390/ijerph19158951
Naves ÉA. Bioética e inteligência artificial: panorama atual da literatura. Rev Bioét. 2024;32. doi:10.1590/1983-803420243552PT
Al-Jawaldeh A, Bekele H, de Silva A, Gomes F, Untoro J, Wickramasinghe K, et al. A new global policy framework for adolescent nutrition? Lancet. 2022;399(10320):125-7. doi:10.1016/S0140-6736(21)02694-5
Fuemmeler BF, Holzwarth E, Sheng Y, Do EK, Miller CA, Blatt J, et al. Mila Blooms: A mobile phone application and behavioral intervention for promoting physical activity and a healthy diet among adolescent survivors of childhood cancer. Games Health J. 2020;9(4):279-89. doi:10.1089/g4h.2019.0060
Oliver-Roig A, Rico-Juan JR, Richart-Martínez M, Cabrero-García J. Predicting exclusive breastfeeding in maternity wards using machine learning techniques. Comput Methods Programs Biomed. 2022;221:106837. doi:10.1016/j.cmpb.2022.106837
Danziato-Neto MA, Caldas PSS, Rêgo JMC, Carioca AAF, Câmara CRS. Relationship between ultrasound measurement of quadriceps muscle and nutritional status in ICU patients in a high-complexity trauma care hospital. Rev Nutr. 2024;37:e240005. doi:10.1590/1678-9865202437e240005
Woods N, Gilliland J, McEachern LW, O’Connor C, Stranges S, Doherty S, et al. How accurate is multiple imputation for nutrient intake estimation? Insights from ASA24 data. Nutrients. 2025;17(15):2510. doi:10.3390/nu17152510
Estecha-Querol S, Fleming CAK, Samnani AA, Cameseria MJ, Chowdhury D, Kehoe S, et al. Identifying key components of a global conceptual framework for adolescent nutrition: Review, nominal group technique and youth co-design. BMJ Glob Health. 2025;10(6):e016167. doi:10.1136/ bmjgh-2024-016167
Mehrjoyan N, Zarei F, Ghofranipour F, Ahmadi F. A participatory framework for identifying and ranking multidimensional solutions to nutritional behavior issues in female school students: A stakeholder-based mixed-methods study. BMC Public Health. 2025;25(1):2344. doi:10.1186/s12889-025- 23575-6
Gozukara Bag H, Yagin F, Gormez Y, González P, Colak C, Gülü M, et al. Estimation of obesity levels through the proposed predictive approach based on physical activity and nutritional habits. Diagnostics. 2023;13(18):2949. doi:10.3390/diagnostics13182949
Cruz RC. Como ferramentas digitais podem ajudar no combate da obesidade infantil? Portal Afya [Internet]. 2024 [cited 2024 Dec 10]. Available from: https://portal.afya.com.br/pediatria/como-ferramentas-digitais-podem-ajudar-no-combate-da-obesidade-infantil
Brazil Health. Obesidade infantil: entenda o tratamento e a importância de prevenir desde cedo. 2024 Oct 31.
Dias CG, Radonsky V. Desenvolvimento de um sistema de auxílio ao diagnóstico em pediatria com o uso de redes neurais artificiais. Exacta [Internet]. 2003;(1):89-95. Available from: https://www.redalyc.org/articulo.oa?id=81000108
Takáo MMV. Inteligência artificial em alergologia e imunologia: desenvolvimento de modelos de predição de risco para erros inatos da imunidade [thesis]. Campinas (SP): Universidade Estadual de Campinas; 2023.
Henriques I. Inteligência Artificial e publicidade dirigida a crianças e adolescentes. Internet & Sociedade. 2021;2(2):5-25.
Maniglia M, Seike AC, Castelete ALT, Catunda BV, Santos JG, Bringhente LM, et al. Aplicação de Tecnologias de Inteligência Artificial na Educação Infantil. In Revista. 2023;15(1).
Santos A. Inteligência artificial traz avanços para a nutrição, mas enfrenta desafios e questões éticas. Jornal da USP – Campus Ribeirão Preto [Internet]. 2024 [cited 2024 Dec 10]. Available from: https://jornal.usp.br/campus-ribeirao-preto/inteligencia-artificial-traz-avancos-para-a-nutricao-mas enfrenta-desafios-e-questoes-eticas/
Lima JC. Desafios para a adoção de Inteligência Artificial pelo Sistema Único de Saúde (SUS): ética, transparência e interpretabilidade [thesis]. Rio de Janeiro (RJ): Fundação Oswaldo Cruz; 2022. Available from: https://ppgics.icict.fiocruz.br/teses-ou-disserta%C3%A7%C3%B5es/desafios-para-a ado%C3%A7%C3%A3o-de-intelig%C3%AAncia-artificial-pelo-sistema-%C3%BAnico-de-sa%C3%BAde
Sánchez López JD, Cambil Martín J, Villegas Calvo M, Luque Martínez F. Inteligencia artificial y robótica. Reflexiones sobre la necesidad de implementar un nuevo marco bioético. J Healthc Qual Res. 2021;36(2):113-4.
Zeigler VL. Ethical considerations in pediatric critical care research. Crit Care Nurs Clin North Am. 2011;23(2):377-84. doi:10.1016/j.ccell.2011.04.005
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2025-11-18
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Corrêa, F. F., Silva, N. C. da, Barbosa, P. D. dos S., Paula, D. de S., Faustino, D. F., & Mello, A. P. de Q. (2025). Use of digital tools in nutritional management in pediatrics and adolescent medicine. O Mundo Da Saúde, 49. https://doi.org/10.15343/0104-7809.202549e17602025I
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