The landscape of knowledge graph and large language model-augmented knowledge graph applications in dementia caregiving support: a scoping review.
Background and Objectives Dementia's rising prevalence places an immense burden on caregivers. Knowledge graphs (KGs) and large language model (LLM)-augmented KGs are emerging Artificial Intelligence (AI) approaches that organize complex dementia care knowledge and enable personalized, context-aware...
| Publicado en: | Gerontologist Vol. 66; no. 7; pp. 1 - 17 |
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| Autores principales: | , , , , , , , , |
| Formato: | Artículo |
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Oxford University Press / USA
Jul2026
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=195281452&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 195281452 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 00169013 GET jtl: Gerontologist issn: 00169013 maglogo: N pubinfo: dt: Jul2026 vid: 66 iid: 7 pid: 622 pub: Oxford University Press / USA artinfo: ui: 195281452 10.1093/geront/gnag125 ppf: 1 ppct: 16 formats: tig: atl: The landscape of knowledge graph and large language model-augmented knowledge graph applications in dementia caregiving support: a scoping review. aug: au: Qi, Xiang Ruan, Jia Yin Zhong, Jie Wan, Yiran Wei, Duo (Helen) Ko, Eunjung Yang, Shu Shen, Li Wu, Bei affil: Rory Meyers College of Nursing, New York University, New York, New York, United States School of Nursing, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong, China Graduate School of Arts and Science, New York University, New York, New York, United States School of Business, Stockton University, Galloway, New Jersey, United States Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, Pennsylvania, United States NYU Shanghai, Shanghai, China su: Psychology of caregivers Social support Medical ethics Treatment of dementia Research funding CINAHL database Clinical decision support systems Natural language processing Services for caregivers Descriptive statistics MEDLINE Systematic reviews Knowledge base Information retrieval Online information services Psychology information storage & retrieval systems sug: subj: Psychology of caregivers Social support Medical ethics Other Individual and Family Services Treatment of dementia Research funding CINAHL database Clinical decision support systems Natural language processing Services for caregivers Descriptive statistics MEDLINE Systematic reviews Knowledge base Information retrieval Online information services Psychology information storage & retrieval systems keyword: Alzheimer's disease artificial intelligence caregivers copyrightHolder:The Gerontological Society of America copyrightYear:2026 Decision support dementia ethics graphical displays https://dx.doi.org/10.1093/geront/gnag125 inLanguage:en languages large language models Personalized care publisher:Oxford University Press sameAs:https://pubmed.ncbi.nlm.nih.gov/42286794/ Scoping review Alzheimer's disease artificial intelligence caregivers copyrightHolder:The Gerontological Society of America copyrightYear:2026 Decision support dementia ethics graphical displays https://dx.doi.org/10.1093/geront/gnag125 inLanguage:en languages large language models Personalized care publisher:Oxford University Press sameAs:https://pubmed.ncbi.nlm.nih.gov/42286794/ Scoping review ab: Background and Objectives Dementia's rising prevalence places an immense burden on caregivers. Knowledge graphs (KGs) and large language model (LLM)-augmented KGs are emerging Artificial Intelligence (AI) approaches that organize complex dementia care knowledge and enable personalized, context-aware support, yet this field remains nascent. We aimed to map and synthesize research on KGs and LLM-augmented KGs in dementia caregiving, identifying system types, applications, outcomes, challenges, and ethical considerations. Research Design and Methods Following the Joanna Briggs Institute (JBI) framework, a comprehensive search was conducted across 6 academic databases (PubMed, Scopus, Web of Science, IEEE Xplore, PsycINFO, CINAHL) and gray literature. Eligibility criteria included studies detailing the design, development, or evaluation of KGs or LLM-augmented KGs for dementia caregiving. Results 12 articles representing 11 unique studies met the inclusion criteria. All 11 studies used KG or ontology components; 8 were KG-only systems, often supporting personalized meal planning, care plan recommendations, knowledge management, robotic assistance, or virtual assistants. 3 studies described LLM-augmented KGs (3/11), primarily using retrieval-augmented generation to enhance conversational AI for caregivers or persons with dementia. Reported benefits included improved usability, personalized support, more accurate or relevant recommendations, and potential improvements in quality of life and independence. Key challenges involved technical complexity, KG maintenance, data quality, limited real-world evaluation, and underdeveloped ethical analysis. Discussion and Implications Integrating KGs with LLMs for dementia caregiving is a promising yet nascent interdisciplinary field. While early systems demonstrate potential, significant gaps remain in clinical validation, comprehensive ethical guidelines development, and responses to caregivers' diverse and evolving needs. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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