{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,14]],"date-time":"2026-08-14T09:29:14Z","timestamp":1786699754941,"version":"build-2736575974"},"reference-count":57,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2026,8,14]],"date-time":"2026-08-14T00:00:00Z","timestamp":1786665600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Diseases"],"abstract":"<jats:p>Background: Obesity is a chronic, multifactorial disease that demands personalized and sustainable management approaches. Digital health technologies, such as artificial intelligence, wearable devices, mobile health apps, and virtual reality (VR), may support obesity care by providing enhanced behavioral monitoring, personalized feedback, and patient engagement. Objective: This critical narrative review discusses the current evidence on artificial intelligence, wearable technologies, and VR in the context of precision nutrition and obesity management and their possible clinical applications and limitations. Method: A critical narrative review was conducted using peer-reviewed literature published between 2019 and 2026 and identified through PubMed and Google Scholar. Search terms included combinations of \u201cprecision nutrition,\u201d \u201cpersonalized nutrition,\u201d \u201cobesity,\u201d \u201cweight management,\u201d \u201cmetabolic health,\u201d \u201cdigital health,\u201d \u201cartificial intelligence,\u201d \u201cmachine learning,\u201d \u201cmobile health,\u201d \u201cwearable devices,\u201d and \u201comics\u201d using Boolean operators. Evidence from randomized controlled trials, systematic reviews, meta-analyses, and key conceptual studies was critically synthesized due to substantial heterogeneity in interventions and outcomes. Result: Wearables and mobile applications can enable continuous self-monitoring of physical activity, dietary intake, sleep, and physiological measures. Artificial intelligence may improve dietary personalization, risk prediction, glycemic control, and adaptive feedback. VR offers an immersive way to tackle behavioral and cognitive mechanisms related to overeating such as cravings, food cue reactivity, and inhibitory control. However, the evidence is heterogeneous, with many studies limited by short follow-up periods, small samples, variable adherence, and insufficient clinical validation. Conclusions: Artificial intelligence, wearable technologies, and VR are promising tools for precision obesity management, but their long-term clinical effectiveness remains uncertain. Future research should prioritize adequately powered trials, longer follow-up, standardized outcomes, transparent algorithms, ethical data governance, and integration with multidisciplinary nutrition and obesity care.<\/jats:p>","DOI":"10.3390\/diseases14080295","type":"journal-article","created":{"date-parts":[[2026,8,14]],"date-time":"2026-08-14T08:08:29Z","timestamp":1786694909000},"page":"295","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Artificial Intelligence, Wearable Technologies, and Virtual Reality in Precision Nutrition and Obesity Management: A Critical Narrative Review"],"prefix":"10.3390","volume":"14","author":[{"given":"Yin Yin","family":"Bashir","sequence":"first","affiliation":[{"name":"Department of Clinical Nutrition and Dietetics, Faculty of Allied Medical Sciences, Applied Science Private University, Amman 11937, Jordan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rahaf","family":"AL-Huneiti","sequence":"additional","affiliation":[{"name":"Department of Clinical Nutrition and Dietetics, Faculty of Allied Medical Sciences, Applied Science Private University, Amman 11937, Jordan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2685-7294","authenticated-orcid":false,"given":"Anfal","family":"AL-Dalaeen","sequence":"additional","affiliation":[{"name":"Department of Clinical Nutrition and Dietetics, Faculty of Allied Medical Sciences, Applied Science Private University, Amman 11937, Jordan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Firas S.","family":"Azzeh","sequence":"additional","affiliation":[{"name":"Preparatory Year Program, Department of Biology, Batterjee Medical College, Jeddah 21442, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,8,14]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"e70040","DOI":"10.1111\/cob.70040","article-title":"A Review of the Management of Obesity in Primary Care","volume":"16","author":"Parretti","year":"2026","journal-title":"Clin. 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