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Using Artificial Intelligence–Based Technologies for the Early Detection of Behavioral and Psychological Symptoms of Dementia: Scoping Review
S Fernandes, Joëlle Rosselet Amoussou, Carla Gomes da Rocha, Élodie Perruchoud, Armin von Gunten, Cédric Mabire, Henk Verloo. JMIR Aging, 2025-10-21
Topic: Risk, prevention and care in population studies
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. 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.
Key findings
- 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.
Why it matters
This review of 12 studies found that artificial intelligence-based technologies are an emerging way to detect behavioral and psychological symptoms of dementia such as agitation and aggression. It tests no treatment, cure, or prevention, and the authors call for more research on effectiveness and quality of life.
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Study details
- Evidence strengthLow
How this study scored 39/100
Published in a peer-reviewed journal. Scored zero for study design, sample size, effect reported, studied in people and randomised / blinded because the record does not state it.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (JMIR Aging) |
| Journal's citation record | 0 / 4 | JMIR Aging: journal h-index 49 (OpenAlex, 2026-10-29) |
| Study design | 0 / 12 | No study design recorded — scores zero, not guessed (not stated in the record — scored 0) |
| Strength of evidence | 1 / 5 | Rated “low” in our summary |
| Peer-review validation | 10 / 10 | Peer-reviewed. Published as an article in a named peer-reviewed journal. |
| How recent | 4 / 5 | 2025 — within 3 year(s) of the newest study here |
| Sample size | 0 / 4 | Participant count not stated — scores zero (not stated in the record — scored 0) |
| Effect reported | 0 / 3 | No effect size reported — scores zero (not stated in the record — scored 0) |
| Studied in people | 0 / 3 | Not stated whether this was studied in people — scores zero (not stated in the record — scored 0) |
| Randomised / blinded | 0 / 2 | No randomisation or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | 2 / 7 | Cited 8 times (OpenAlex, 2026-10-10) |
| Citations per year | 1 / 5 | 2.7 citations a year over 3 year(s) since 2025 |
| Impact for its field and year | 3 / 6 | Cited 5.1× the average for papers of its field and year (OpenAlex FWCI) |
| Cited by studies here | 1 / 6 | Cited by 2 other studies in this library |
| Still being cited | 1 / 4 | Cited 8 times in 2024–2026 (2026 still in progress; OpenAlex) |
| Senior author's track record | 2 / 4 | Last-listed author Henk Verloo: h-index 20 (OpenAlex, whole career) |
| Institution's track record | 1 / 3 | University of Lausanne: institution h-index 994 (OpenAlex) |
| Multi-centre collaboration | 2 / 3 | OpenAlex lists 6 institution(s) in 1 country |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 41118658) |
| Free to read | 2 / 2 | Free to read |
| Total | 39 / 100 | — |
What each of these 20 components measures, and what this score is not →
Read the original
Full text: free to read — OpenAlex lists this copy as free to read: the link above (checked 6 Feb 1020).
Cite this study APA, Vancouver, BibTeX · download .bib or .ris
Built from the record alzhub holds for this paper, not looked up. Volume, issue and page numbers are not held in the record. The record names 7 authors; APA and Vancouver show the first six, BibTeX and the downloads carry all of them. Check the citation against the original before you use it.
APA 7th
Fernandes, S., Amoussou, J. R., da Rocha, C. G., Perruchoud, É., von Gunten, A., Mabire, C., et al. (2025). Using Artificial Intelligence–Based Technologies for the Early Detection of Behavioral and Psychological Symptoms of Dementia: Scoping Review. JMIR Aging. https://doi.org/10.2196/76074
Vancouver
Fernandes S, Amoussou JR, da Rocha CG, Perruchoud É, von Gunten A, Mabire C, et al. Using Artificial Intelligence–Based Technologies for the Early Detection of Behavioral and Psychological Symptoms of Dementia: Scoping Review. JMIR Aging. 2025. doi:10.2196/76074. PMID: 41118658.
BibTeX
@article{fernandes2025-41118658,
author = {Fernandes, S and Amoussou, Joëlle Rosselet and da Rocha, Carla Gomes and Perruchoud, Élodie and von Gunten, Armin and Mabire, Cédric and Verloo, Henk},
title = {{Using Artificial Intelligence–Based Technologies for the Early Detection of Behavioral and Psychological Symptoms of Dementia: Scoping Review}},
journal = {JMIR Aging},
year = {2025},
doi = {10.2196/76074},
pmid = {41118658},
url = {https://doi.org/10.2196/76074}
}
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