ArticleClinical nutrition research2026
Personalized nutrition interventions using digital technologies for older adults: a scoping review.
Article in Clinical nutrition research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveAs global populations age, nutrition management is important for healthy aging. Digital technologies, including mobile applications, web-based platforms, messaging tools, and artificial intelligence (AI)-enabled systems, are used in personalized nutrition interventions. However, evidence on their characteristics, effectiveness, and user experiences remains limited. This scoping review examined technology-based personalized nutrition interventions for older adults.
methodsThis review followed the Joanna Briggs Institute methodology and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews guidelines. PubMed, Embase, and Web of Science were searched for studies published from January 1, 2010, to June 30, 2026. Among 2,727 records, 2,044 were screened after duplicate removal, 28 full-text articles were assessed, and 13 articles representing 12 studies were included.
resultsTechnologies included mobile, messaging, web-based, information and communications technology, tablet-based, and AI-supported systems. Interventions involved dietary recording, personalized feedback, remote counseling, coaching, and self-monitoring. Outcomes included dietary intake and quality, nutritional status, physical function, frailty, cognition, cardiometabolic indicators, engagement, usability, and acceptability. Findings were more consistent for dietary behaviors and individualized nutrition management. Evidence for physical function, frailty, cognition, cardiometabolic health, and quality of life was limited and often based on small or multidomain studies. Familiar interfaces and professional support were accepted, whereas low digital literacy, complex navigation, and limited food databases were barriers.
conclusionDigital personalized nutrition interventions may support dietary behavior change and individualized nutrition management in older adults. Larger studies and user-centered systems addressing digital literacy, usability, cultural context, and AI-feedback validation are needed.
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