Technology-enabled personalized nutrition interventions for adolescents with type 1 diabetes: a systematic review

Adolescents with type 1 diabetes (T1D) face substantial and distinctive challenges in nutritional self-management. The emergence of digital health technologies offers novel opportunities to personalize nutritional support in this population, yet the evidence base underlying these interventions has not been comprehensively synthesized. This systematic review aimed to comprehensively identify, characterize, and synthesize the available evidence on personalized nutrition interventions for adolescents with T1D. A systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Seven electronic databases were searched from January 2012 to March 2026: PubMed/MEDLINE, Embase, CINAHL, Web of Science, Cochrane Library, PsycINFO, and IEEE Xplore. Eligible studies included any study design examining a personalized nutrition intervention for adolescents (aged 10–25 years) with T1D, reporting at least one glycemic, nutritional, behavioral, or psychosocial outcome. Study quality was assessed using the Cochrane Risk of Bias 2 tool for randomized trials, the Critical Appraisal Skills Programme (CASP) checklist for qualitative studies, and the Mixed Methods Appraisal Tool (MMAT) for mixed-methods and non-randomized designs. Data were synthesized using narrative synthesis for quantitative evidence and thematic analysis for qualitative evidence, following the Synthesis Without Meta-Analysis (SWiM) reporting guidelines. Thirty-five studies published between 2012 and 2026 were included, involving over 1,500 participants across 17 countries. Study designs comprised randomized controlled trials ( n = 8), pilot and pre-post interventional studies ( n = 10), qualitative and mixed-methods studies ( n = 14), survey studies ( n = 2), and a simulation study ( n = 1). Personalized macronutrient-aware bolus calculators (incorporating fat and protein) improved postprandial glucose control and reduced estimation errors compared with standard carbohydrate counting. AI-driven dietary assessment tools (photographic, 3D volumetric, and voice-based) significantly enhanced carbohydrate estimation accuracy over manual methods. Simplified meal announcement strategies within hybrid closed-loop automated insulin delivery systems demonstrated non-inferiority to precise carbohydrate counting for time in range, with reduced cognitive burden, though some increase in prolonged hyperglycemia was observed. Gamified and real-time feedback applications increased self-monitoring frequency and engagement, while qualitative evidence consistently showed reductions in psychosocial burden, diabetes-related stigma, treatment fatigue, and family conflict, alongside gains in empowerment, autonomy, and quality of life. Common barriers included engagement decay, usability issues, and cultural mismatches, whereas personalization, low cognitive load, and social support features facilitated sustained use. Personalized digital nutrition tools and simplified meal management strategies within AID systems hold substantial promise for improving glycemic outcomes and reducing psychosocial burden in adolescents with T1D. Effective interventions share core design principles including dynamic individualization, real-time feedback, low cognitive burden, and integration with the adolescent social and digital ecosystem. Future research should prioritize long-term engagement, cultural equity, and co-designed youth-centered implementation strategies.