![]() ![]() Baseline characteristics, satisfaction, system usability, and diabetes-related and general health indicators were assessed before and after using the platform for 8 weeks. The intervention consists of a web-based platform that incorporates AI to personalize recipes, meal planning, and shopping list experiences and was made available for 8 weeks. Web-based semistructured interviews were conducted with platform users (7/23, 30%) who agreed to be followed up and diabetes experts (n=3) who had nutrition and platform knowledge. Of these 73 participants, 23 (32%) completed a web-based survey after 8 weeks of platform use. A total of 73 adult participants with prediabetes or diabetes or their carers completed the baseline web-based survey. Methods: Diabetes UK signposted people with diabetes and their carers to the platform’s study-specific portal through its website, social media, and newsletters. ![]() ![]() Objective: This study aimed to examine the usability and preliminary efficacy of a web-based AI-driven nutrition platform to support people with diabetes and their carers in identifying healthy recipes, meal planning, and web-based shopping. Web-based diabetes care, driven by artificial intelligence (AI), enables more personalized care. Research Institute for Health and Wellbeingīackground: Nutrition plays an important role in diabetes self-management. Online Journal of Public Health Informatics.Asian/Pacific Island Nursing Journal 13 articles.JMIR Bioinformatics and Biotechnology 38 articles.JMIR Biomedical Engineering 74 articles.Journal of Participatory Medicine 82 articles.JMIR Perioperative Medicine 98 articles.JMIR Rehabilitation and Assistive Technologies 223 articles.JMIR Pediatrics and Parenting 303 articles.Interactive Journal of Medical Research 340 articles.JMIR Public Health and Surveillance 1245 articles.Journal of Medical Internet Research 7976 articles. ![]()
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