An Interdisciplinary Approach to Long-Term Care: Artificial Intelligence Applications for Monitoring Nutritional Status and Social Well-Being

Öz

The global rise in the older adult population brings complex, interrelated biopsychosocial challenges, including nutritional inadequacies, sarcopenia, social isolation, and sleep disturbances. Dealing with these interconnected issues in institutional care settings is increasingly difficult given the restrictions of traditional approaches. This descriptive review analyzes, from a multidisciplinary perspective, the role of Artificial Intelligence (AI)-based technologies in monitoring nutritional status, predicting clinical risks such as malnutrition and sarcopenia, and enhancing psychosocial well-being in elder care. Relevant literature was identified through searches in PubMed/MEDLINE, Scopus, and Web of Science (2016–2026), focusing on peer-reviewed studies published in English. Current literature indicates that AI-based image-processing systems can accurately monitor dietary intake, while machine learning algorithms can enable earlier risk stratification for sarcopenia and inflammatory trajectories using biomarker data. Furthermore, social robots and non-contact sensors have been shown to reduce loneliness among older adults, improve sleep quality, and indirectly enhance motivation for eating. From a social work perspective, AI is considered an effective tool that increases organizational efficiency in case management and facilitates a shift from crisis-oriented intervention to predictive and preventive care models. The success of this technical transformation depends on establishing an ethical framework that supports privacy, dignity, and the principles of person-centered care. Overall, AI provides evidence-informed decision support for dietitians and social work professionals, helping to develop a holistic care ecosystem that optimizes the well-being of older adults.

Anahtar Kelimeler

• Artificial intelligence
• elder care
• nutrition
• social isolation
• sarcopenia
• social work

Uzun Süreli Bakımda Disiplinlerarası Bir Yaklaşım: Beslenme Durumu ve Sosyal Refahın İzlenmesinde Yapay Zekâ Uygulamaları

Öz

Yaşlı nüfusun küresel olarak artması, beslenme yetersizlikleri, sarkopeni, sosyal izolasyon ve uyku bozuklukları gibi karmaşık ve birbirleriyle ilişkili biyopsikososyal zorlukları beraberinde getirmektedir. Geleneksel yaklaşımların sınırlılıkları nedeniyle, kurumsal bakım ortamlarında bu birbiriyle bağlantılı sorunların yönetimi giderek daha güç hale gelmiştir. Bu anlatı derlemesi, yaşlı bakımında yapay zekâ (YZ) tabanlı teknolojilerin beslenme durumunun izlenmesindeki, malnütrisyon ve sarkopeni dâhil klinik risklerin öngörülmesindeki ve psikososyal refahın artırılmasındaki rolünü multidisipliner bir bakış açısıyla değerlendirmektedir. Güncel literatür, YZ destekli görüntü işleme sistemlerinin besin alımını yüksek doğrulukla izleyebildiğini; makine öğrenmesi algoritmalarının ise biyobelirteç verilerini kullanarak sarkopeni ve inflamatuvar seyre yönelik erken risk sınıflandırmasına olanak tanıdığını göstermektedir. Ayrıca sosyal robotların ve temassız sensörlerin yaşlılarda yalnızlığı azaltabildiği, uyku kalitesini iyileştirebildiği ve dolaylı olarak yeme motivasyonunu artırabildiği bildirilmektedir. Sosyal hizmet perspektifinden, YZ vaka yönetiminde kurumsal verimliliği artıran ve kriz odaklı müdahaleden öngörülü ve önleyici bakım modellerine geçişi destekleyen stratejik bir araç olarak görülmektedir. Bununla birlikte, bu teknolojik dönüşümün başarısı mahremiyeti, onuru ve kişi merkezli bakım ilkelerini koruyan bir etik çerçevenin oluşturulmasına bağlıdır. Genel olarak YZ, diyetisyenler ve sosyal hizmet uzmanları için kanıta dayalı karar desteği sunmakta ve yaşlı bireylerin iyilik hâlini optimize eden bütüncül bir bakım ekosisteminin geliştirilmesine katkı sağlamaktadır.

Anahtar Kelimeler

• Yapay zeka
• yaşlı bakımı
• beslenme
• sosyal izolasyon
• sarkopeni
• sosyal hizmet

Kaynakça

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