Sofia Fernandes, Joëlle Rosselet Amoussou, Carla Gomes da Rocha, Elodie Perruchoud, Armin von Gunten, Cédric Mabire, Henk Verloo
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We also examined which health care professionals were involved, nursing involvement and experience, the care settings in which these technologies are used, and the characteristics of the BPSD that were assessed.</p><p><strong>Methods: </strong>Our scoping review was conducted in accordance with the Joanna Briggs Institute manual for scoping reviews. Searches were conducted in March 2025 in the following bibliographic databases: MEDLINE ALL Ovid, Embase, APA PsycINFO Ovid, CINAHL EBSCO, Web of Science Core Collection, the Cochrane Library Wiley, and ProQuest Dissertations and Theses A&I. Additional searches were performed using citation tracking strategies and by consulting the Association for Computing Machinery Digital Library. Eligible studies included primary research involving people with dementia and examining the use of AITs for the detection of BPSD in real-world care settings.</p><p><strong>Results: </strong>After screening 3670 articles for eligibility, the review includes 12 studies. The studies retained were conducted between 2012 and 2025 in 5 countries and encompassed a range of care settings. The AITs used were predominantly based on classic machine learning approaches and used information from environmental sensors, wearable devices, and data recording systems. These studies primarily assessed behavioral and physiological parameters and focused specifically on symptoms, such as agitation and aggression. None of the retained studies explored nurses' roles or their specific skills in using these technologies.</p><p><strong>Conclusions: </strong>The use of AITs for managing BPSD represents an emerging field of research offering novel opportunities to enhance their detection in various health care contexts. We recommended that nurses be actively engaged in developing and assessing these technologies. Future research should prioritize investigations into how effective AITs are across diverse populations, whether they can have a long-term impact on managing BPSD, and whether they can improve the quality of life of patients and caregivers.</p>","PeriodicalId":36245,"journal":{"name":"JMIR Aging","volume":"8 ","pages":"e76074"},"PeriodicalIF":4.8000,"publicationDate":"2025-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12539798/pdf/","citationCount":"0","resultStr":"{\"title\":\"Using Artificial Intelligence-Based Technologies for the Early Detection of Behavioral and Psychological Symptoms of Dementia: Scoping Review.\",\"authors\":\"Sofia Fernandes, Joëlle Rosselet Amoussou, Carla Gomes da Rocha, Elodie Perruchoud, Armin von Gunten, Cédric Mabire, Henk Verloo\",\"doi\":\"10.2196/76074\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>People with dementia commonly display behavioral and psychological symptoms, which have multiple negative consequences. 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引用次数: 0
摘要
背景:痴呆症患者通常表现出行为和心理症状,这些症状会产生多种负面后果。基于人工智能的技术(AITs)有可能支持早期检测痴呆症(BPSD)的行为和心理症状。最近对这一主题的兴趣激增,强调了全面审查现有证据的必要性。目的:本综述旨在确定和总结目前在诊断为BPSD的人群中用于早期检测的ait的类型和用途。我们还检查了哪些医疗保健专业人员参与,护理参与和经验,使用这些技术的护理环境,以及被评估的BPSD的特征。方法:我们的范围审查按照乔安娜布里格斯研究所的范围审查手册进行。检索于2025年3月在以下书目数据库中进行:MEDLINE ALL Ovid、Embase、APA PsycINFO Ovid、CINAHL EBSCO、Web of Science Core Collection、Cochrane Library Wiley和ProQuest disserds and Theses A&I。使用引文跟踪策略和咨询计算机协会数字图书馆进行其他搜索。符合条件的研究包括涉及痴呆症患者的初步研究,以及在现实护理环境中检查使用ait检测BPSD的情况。结果:在筛选了3670篇文章后,纳入了12项研究。所保留的研究是在2012年至2025年期间在5个国家进行的,涵盖了一系列护理环境。使用的人工智能主要基于经典的机器学习方法,并使用来自环境传感器、可穿戴设备和数据记录系统的信息。这些研究主要评估行为和生理参数,并特别关注症状,如躁动和攻击。没有一项保留的研究探讨护士的角色或他们使用这些技术的具体技能。结论:使用ait来管理BPSD代表了一个新兴的研究领域,为在各种卫生保健环境中加强BPSD的检测提供了新的机会。我们建议护士积极参与开发和评估这些技术。未来的研究应该优先调查ait在不同人群中的有效性,它们是否能对BPSD的管理产生长期影响,以及它们是否能改善患者和护理人员的生活质量。
Using Artificial Intelligence-Based Technologies for the Early Detection of Behavioral and Psychological Symptoms of Dementia: Scoping Review.
Background: People with dementia commonly display behavioral and psychological symptoms, which have multiple negative consequences. Artificial intelligence-based technologies (AITs) have the potential to support earlier detection of the behavioral and psychological symptoms of dementia (BPSD). The recent surge of interest in this topic underscores the need to comprehensively examine the existing evidence.
Objective: This scoping review aimed to identify and summarize the types and uses of AITs currently used for the early detection of BPSD among people diagnosed with the disease. We also examined which health care professionals were involved, nursing involvement and experience, the care settings in which these technologies are used, and the characteristics of the BPSD that were assessed.
Methods: Our scoping review was conducted in accordance with the Joanna Briggs Institute manual for scoping reviews. Searches were conducted in March 2025 in the following bibliographic databases: MEDLINE ALL Ovid, Embase, APA PsycINFO Ovid, CINAHL EBSCO, Web of Science Core Collection, the Cochrane Library Wiley, and ProQuest Dissertations and Theses A&I. Additional searches were performed using citation tracking strategies and by consulting the Association for Computing Machinery Digital Library. Eligible studies included primary research involving people with dementia and examining the use of AITs for the detection of BPSD in real-world care settings.
Results: After screening 3670 articles for eligibility, the review includes 12 studies. The studies retained were conducted between 2012 and 2025 in 5 countries and encompassed a range of care settings. The AITs used were predominantly based on classic machine learning approaches and used information from environmental sensors, wearable devices, and data recording systems. These studies primarily assessed behavioral and physiological parameters and focused specifically on symptoms, such as agitation and aggression. None of the retained studies explored nurses' roles or their specific skills in using these technologies.
Conclusions: The use of AITs for managing BPSD represents an emerging field of research offering novel opportunities to enhance their detection in various health care contexts. We recommended that nurses be actively engaged in developing and assessing these technologies. Future research should prioritize investigations into how effective AITs are across diverse populations, whether they can have a long-term impact on managing BPSD, and whether they can improve the quality of life of patients and caregivers.