Artificial intelligence for relational reconnection and social support in Alzheimer's disease: a conceptual framework for socially embedded systems.

Alzheimer's disease (AD) has traditionally been approached through a biomedical lens, focusing on neurodegenerative markers such as amyloid-β plaques and tau protein accumulation. However, clinical evidence increasingly demonstrates that social dysfunction, which includes identity confusion, emotion...

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Publicado en:Gerontologist Vol. 66; no. 7; pp. 1 - 11
Autor principal: Zhang, Chengmeng
Formato: Artículo
Publicado: Oxford University Press / USA Jul2026
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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        atl: Artificial intelligence for relational reconnection and social support in Alzheimer's disease: a conceptual framework for socially embedded systems.
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        au: Zhang, Chengmeng
        affil: Institute of Population Research, Peking University, Beijing, ChinaInstitute of Ageing Studies, Peking University, Beijing, China
      su:
        Social capital
        Artificial intelligence
        Cultural competence
        Emotions
        Social perception
        Caregivers
        Social networks
        Quality of life
        Informed consent (Medical law)
        Social support
        Interpersonal relations
        Social isolation
        Alzheimer's disease
        Independent living
        Biometry
        Conceptual structures
        Auditory perception
        User interfaces
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          Social capital
          Artificial intelligence
          Cultural competence
          Emotions
          Social perception
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          Social networks
          Quality of life
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          Interpersonal relations
          Social isolation
          Other Individual and Family Services
          Alzheimer's disease
          Independent living
          Biometry
          Conceptual structures
          Auditory perception
          User interfaces
      keyword:
        artificial intelligence
        cognitive impairment
        copyrightHolder:The Gerontological Society of America
        copyrightYear:2026
        crystalline
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        https://dx.doi.org/10.1093/geront/gnag108
        inLanguage:en
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        nerve degeneration
        personhood
        publisher:Oxford University Press
        sameAs:https://pubmed.ncbi.nlm.nih.gov/42121397/
        social capital
        social cognition
        Social dysfunction
        Social relationship management capacity
        social support
        Socially embedded artificial intelligence
        artificial intelligence
        cognitive impairment
        copyrightHolder:The Gerontological Society of America
        copyrightYear:2026
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        lens
        lens (device)
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        publisher:Oxford University Press
        sameAs:https://pubmed.ncbi.nlm.nih.gov/42121397/
        social capital
        social cognition
        Social dysfunction
        Social relationship management capacity
        social support
        Socially embedded artificial intelligence
      ab: Alzheimer's disease (AD) has traditionally been approached through a biomedical lens, focusing on neurodegenerative markers such as amyloid-β plaques and tau protein accumulation. However, clinical evidence increasingly demonstrates that social dysfunction, which includes identity confusion, emotional withdrawal, and breakdowns in social roles. This article reconceptualizes AD as a disorder in which the primary dimension of decline lies in social relationship management capacity (SRMC), while recognizing that neurobiological and cognitive deterioration remain integral to its manifestation and progression. SRMC refers to a person's ability to identify, interpret, maintain, and regulate social ties embedded in complex networks. This article introduces a conceptual and technical framework for a socially embedded artificial intelligence (AI) framework designed to recognize and compensate for the deterioration of SRMC in AD. Drawing on social capital theory, affective computing, and neural social cognition research, this framework proposes a four-dimensional intervention model: relationship recognition, relationship learning, relationship establishment, and relationship management. By aligning cutting-edge AI techniques with the lived social reality of individuals with AD, this approach not only provides a new path for supportive care but also reorients ethical and technological discourse toward sustaining social personhood in the face of neurodegeneration.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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