Katrin Lehner, Vera Gallistl, Rebekka Steinlechner, Sophie Kellerberger, Gerhard Paulinger, Franz Kolland
{"title":"[老年人如何通过人工智能辅助健康技术学习：可爱的海豹和神经跌倒传感器]。","authors":"Katrin Lehner, Vera Gallistl, Rebekka Steinlechner, Sophie Kellerberger, Gerhard Paulinger, Franz Kolland","doi":"10.1007/s00391-025-02425-5","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>With the growing use of artificial intelligence (AI) in various areas of life, AI technologies are increasingly being developed for the nursing and care of older people and are intended to contribute to greater safety for older people in need of care and to relieve the burden on caregivers; however, research into the attitudes and practices of older people in need of care towards AI is only just beginning.</p><p><strong>Objective: </strong>The aim of the article is to ask which learning processes emerge as older nursing home residents interact with AI technologies and how these can be supported with concepts from geragogy.</p><p><strong>Material and methods: </strong>The data consist of 10 guideline-assisted interviews with older nursing home residents aged 83-96 years and records of participant observations (75 h). Data collection took place in summer 2022 and fall 2023 in two nursing homes that use AI-based fall sensors and social robots. The material was analyzed using situation analysis.</p><p><strong>Results: </strong>Nursing home residents showed an active interest in engaging with AI technologies, for example, by trying to relate experiences with AI technologies with experiences from their life course (biography-oriented learning practices) and engaging with AI technologies in everyday life (everyday-oriented learning practices). Residents are therefore interested actors in processes of technology implementation but rarely perceive themselves as competent in the context of AI.</p><p><strong>Conclusion: </strong>The article shows the learning practices and potentials of residents and discusses possibilities of a geragogical approach for a differentiated understanding of AI technologies in nursing.</p>","PeriodicalId":49345,"journal":{"name":"Zeitschrift Fur Gerontologie Und Geriatrie","volume":" ","pages":""},"PeriodicalIF":1.1000,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"[How older people are learning through artificial intelligence-assisted health technologies : Cute seals and nervous fall sensors].\",\"authors\":\"Katrin Lehner, Vera Gallistl, Rebekka Steinlechner, Sophie Kellerberger, Gerhard Paulinger, Franz Kolland\",\"doi\":\"10.1007/s00391-025-02425-5\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>With the growing use of artificial intelligence (AI) in various areas of life, AI technologies are increasingly being developed for the nursing and care of older people and are intended to contribute to greater safety for older people in need of care and to relieve the burden on caregivers; however, research into the attitudes and practices of older people in need of care towards AI is only just beginning.</p><p><strong>Objective: </strong>The aim of the article is to ask which learning processes emerge as older nursing home residents interact with AI technologies and how these can be supported with concepts from geragogy.</p><p><strong>Material and methods: </strong>The data consist of 10 guideline-assisted interviews with older nursing home residents aged 83-96 years and records of participant observations (75 h). Data collection took place in summer 2022 and fall 2023 in two nursing homes that use AI-based fall sensors and social robots. The material was analyzed using situation analysis.</p><p><strong>Results: </strong>Nursing home residents showed an active interest in engaging with AI technologies, for example, by trying to relate experiences with AI technologies with experiences from their life course (biography-oriented learning practices) and engaging with AI technologies in everyday life (everyday-oriented learning practices). Residents are therefore interested actors in processes of technology implementation but rarely perceive themselves as competent in the context of AI.</p><p><strong>Conclusion: </strong>The article shows the learning practices and potentials of residents and discusses possibilities of a geragogical approach for a differentiated understanding of AI technologies in nursing.</p>\",\"PeriodicalId\":49345,\"journal\":{\"name\":\"Zeitschrift Fur Gerontologie Und Geriatrie\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":1.1000,\"publicationDate\":\"2025-03-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Zeitschrift Fur Gerontologie Und Geriatrie\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1007/s00391-025-02425-5\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"GERIATRICS & GERONTOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Zeitschrift Fur Gerontologie Und Geriatrie","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s00391-025-02425-5","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"GERIATRICS & GERONTOLOGY","Score":null,"Total":0}
[How older people are learning through artificial intelligence-assisted health technologies : Cute seals and nervous fall sensors].
Background: With the growing use of artificial intelligence (AI) in various areas of life, AI technologies are increasingly being developed for the nursing and care of older people and are intended to contribute to greater safety for older people in need of care and to relieve the burden on caregivers; however, research into the attitudes and practices of older people in need of care towards AI is only just beginning.
Objective: The aim of the article is to ask which learning processes emerge as older nursing home residents interact with AI technologies and how these can be supported with concepts from geragogy.
Material and methods: The data consist of 10 guideline-assisted interviews with older nursing home residents aged 83-96 years and records of participant observations (75 h). Data collection took place in summer 2022 and fall 2023 in two nursing homes that use AI-based fall sensors and social robots. The material was analyzed using situation analysis.
Results: Nursing home residents showed an active interest in engaging with AI technologies, for example, by trying to relate experiences with AI technologies with experiences from their life course (biography-oriented learning practices) and engaging with AI technologies in everyday life (everyday-oriented learning practices). Residents are therefore interested actors in processes of technology implementation but rarely perceive themselves as competent in the context of AI.
Conclusion: The article shows the learning practices and potentials of residents and discusses possibilities of a geragogical approach for a differentiated understanding of AI technologies in nursing.
期刊介绍：
The fact that more and more people are becoming older and are having a significant influence on our society is due to intensive geriatric research and geriatric medicine in the past and present. The Zeitschrift für Gerontologie und Geriatrie has contributed to this area for many years by informing a broad spectrum of interested readers about various developments in gerontology research. Special issues focus on all questions concerning gerontology, biology and basic research of aging, geriatric research, psychology and sociology as well as practical aspects of geriatric care.
Target group: Geriatricians, social gerontologists, geriatric psychologists, geriatric psychiatrists, nurses/caregivers, nurse researchers, biogerontologists in geriatric wards/clinics, gerontological institutes, and institutions of teaching and further or continuing education.
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