Effects of Different Exercise‐Led Strategies on Mental, Nutritional, Physical and Cognitive Health in Community‐Dwelling Older Adults: A Quasi‐Experimental Study.

Introduction: Exercise interventions are widely used to promote physical and psychosocial health in community‐dwelling older adults; however, the comparative effects of human‐guided and artificial intelligence (AI)‐based exercise delivery on sleep and cognitive outcomes remain insufficiently underst...

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Publicado en:International Journal of Older People Nursing Vol. 21; no. 3; pp. 1 - 12
Autores principales: Liao, Hui‐Chuan, Chou, Chia‐Ni, Chao, Wen‐Yi
Formato: clinical trial research tables/charts Journal Article
Publicado: Wiley-Blackwell May2026
Acceso en línea:Ver este registro en EBSCOhost
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      dt: May2026
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      pub: Wiley-Blackwell
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        10.1111/opn.70071
        194047418
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        atl: Effects of Different Exercise‐Led Strategies on Mental, Nutritional, Physical and Cognitive Health in Community‐Dwelling Older Adults: A Quasi‐Experimental Study.
      aug:
        au:
          Liao, Hui‐Chuan
          Chou, Chia‐Ni
          Chao, Wen‐Yi
        affil: Department of Nursing, China Medical University Beigang Hospital, Yunlin, Taiwan
      sug:
        subj:
          Community Living In Old Age
          Therapeutic Exercise Methods
          Training Effect (Physiology)
          Mental Health In Old Age
          Cognition In Old Age
          Nutritional Status In Old Age
          Human
          Aged
          Descriptive Statistics
          Confidence Intervals
          Quasi-Experimental Studies
          Pretest-Posttest Design
          Funding Source
          Sleep Quality
          Artificial Intelligence Utilization
          Psychological Well-Being
          Convenience Sample
          Chi Square Test
          T-Tests
          Data Analysis Software
          Clinical Trials
          Scales
          Questionnaires
          Aged: 65+ years
      ab: Introduction: Exercise interventions are widely used to promote physical and psychosocial health in community‐dwelling older adults; however, the comparative effects of human‐guided and artificial intelligence (AI)‐based exercise delivery on sleep and cognitive outcomes remain insufficiently understood. This study compared the effects of human‐guided versus AI‐based exercise programmes on multiple health domains in older adults. Methods: A 12‐week quasi‐experimental study was conducted with two groups: a human‐guided exercise programme (HGEP) and an AI‐based exercise programme (AIEP). Outcomes included depression, sleep quality, well‐being, nutritional status, sarcopenia risk and cognitive function, assessed using validated instruments. Generalised estimating equation models were applied to examine time effects and group‐by‐time interactions. Results: Significant main effects of time were observed for depression, well‐being, sarcopenia risk, sleep quality and cognitive function, indicating overall post‐intervention improvement. Notably, significant group‐by‐time interactions favoured the AIEP for sleep quality and cognitive function. Improvements in sleep quality should be interpreted cautiously due to a floor effect in the human‐guided group, whereas the cognitive benefit observed in the AI‐based group may reflect additional attentional and executive demands associated with real‐time feedback and performance monitoring. Conclusion: Both exercise delivery strategies yielded beneficial effects across multiple health domains. AIEPs may provide added advantages for sleep and cognitive outcomes, highlighting their potential role as a complementary approach in community‐based exercise interventions for older adults. Implications for Practice: These findings support integrating AI‐assisted exercise into community and nursing practice as a scalable, accessible alternative to instructor‐led programs, enhancing reach and providing flexible, personalized support for older adults' health. Summary: What does this research add to existing knowledge in gerontology?: This study contributes to gerontology by providing empirical evidence on the comparative effectiveness of AI‐supported versus human‐guided exercise interventions among community‐dwelling older adults. It demonstrates that both intervention strategies significantly improve mental health, nutritional status, sarcopenia risk and early cognitive screening outcomes, with AI‐based programmes showing particular promise for enhancing sleep quality. What are the implications of this new knowledge for nursing care for and with older adults?: The findings support the integration of tailored exercise interventions into routine nursing care for older adults. Nurses can utilise AI‐based systems to complement in‐person guidance, especially in resource‐limited settings, thereby expanding access to physical and cognitive health‐promoting programmes. This enables more scalable, cost‐effective and individualised care approaches. How could the findings be used to influence practice, education, research, and policy?: The results can inform the development of ageing‐related health policies that advocate for technology‐assisted interventions. In practice, they support community‐based implementation of hybrid exercise programmes. For education and research, these findings underscore the importance of interdisciplinary training in gerontechnology and call for longitudinal studies to assess sustainability and broader health outcomes.
      pubtype: Academic Journal
      doctype:
        clinical trial
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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