Using Artificial Intelligence–Based Technologies for the Early Detection of Behavioral and Psychological Symptoms of Dementia: Scoping Review
Background: People with dementia commonly display behavioural and psychological symptoms, which have multiple negative consequences. Artificial-intelligence-based technologies have the potential to support earlier detection of the behavioural and psychological symptoms of dementia. 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 summarise the types and uses of artificial-intelligence-based technologies currently used for the early detection of behavioural and psychological symptoms of dementia among people diagnosed with the disease. We also examined which healthcare professionals were involved, nursing involvement and experience, the care settings in which these technologies are employed, and the characteristics of the behavioural and psychological symptoms of dementia 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.com, APA PsycINFO Ovid, CINAHL EBSCO, Web of Science Core Collection, the Cochrane Library Wiley and ProQuest Dissertations & Theses A&I. Additional searches were performed using citation tracking strategies and by consulting the ACM Digital Library. Eligible studies included primary research involving people with dementia and examining the use of artificial-intelligence-based technologies for the detection of the behavioural and psychological symptoms of dementia in real-world care settings. Results: After screening 3670 articles for eligibility, the review includes twelve studies. The studies retained were conducted between 2012 and 2025 in five countries and encompassed a range of care settings. The artificial-intelligence-based technologies 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 behavioural and physiological parameters and focussed specifically on symptoms such as agitation and aggression. None of the studies retained explored nurses’ roles or their specific skills in using these technologies. Conclusions: The use of artificial-intelligence-based technologies for managing behavioural and psychological symptoms of dementia represents an emerging field of research offering novel opportunities to enhance their detection in various healthcare contexts. We recommended that nurses be actively engaged in developing and assessing these technologies. Future research should prioritise investigations into how effective artificial-intelligence-based technologies are across diverse populations, whether they can have a long-term impact on managing behavioural and psychological symptoms of dementia, and whether they can improve the quality of life of patients and caregivers.
