Using AI-Based Technologies to Help Nurses Detect Behavioral Disorders: Narrative Literature Review.

artificial intelligence behavioral and psychological symptoms of dementia early detection management narrative literature review neuropsychiatric symptoms

Journal

JMIR nursing
ISSN: 2562-7600
Titre abrégé: JMIR Nurs
Pays: Canada
ID NLM: 101771299

Informations de publication

Date de publication:
28 May 2024
Historique:
received: 12 11 2023
accepted: 26 04 2024
revised: 15 04 2024
medline: 28 5 2024
pubmed: 28 5 2024
entrez: 28 5 2024
Statut: epublish

Résumé

The behavioral and psychological symptoms of dementia (BPSD) are common among people with dementia and have multiple negative consequences. Artificial intelligence-based technologies (AITs) have the potential to help nurses in the early prodromal detection of BPSD. Despite significant recent interest in the topic and the increasing number of available appropriate devices, little information is available on using AITs to help nurses striving to detect BPSD early. The aim of this study is to identify the number and characteristics of existing publications on introducing AITs to support nursing interventions to detect and manage BPSD early. A literature review of publications in the PubMed database referring to AITs and dementia was conducted in September 2023. A detailed analysis sought to identify the characteristics of these publications. The results were reported using a narrative approach. A total of 25 publications from 14 countries were identified, with most describing prospective observational studies. We identified three categories of publications on using AITs and they are (1) predicting behaviors and the stages and progression of dementia, (2) screening and assessing clinical symptoms, and (3) managing dementia and BPSD. Most of the publications referred to managing dementia and BPSD. Despite growing interest, most AITs currently in use are designed to support psychosocial approaches to treating and caring for existing clinical signs of BPSD. AITs thus remain undertested and underused for the early and real-time detection of BPSD. They could, nevertheless, provide nurses with accurate, reliable systems for assessing, monitoring, planning, and supporting safe therapeutic interventions.

Sections du résumé

BACKGROUND BACKGROUND
The behavioral and psychological symptoms of dementia (BPSD) are common among people with dementia and have multiple negative consequences. Artificial intelligence-based technologies (AITs) have the potential to help nurses in the early prodromal detection of BPSD. Despite significant recent interest in the topic and the increasing number of available appropriate devices, little information is available on using AITs to help nurses striving to detect BPSD early.
OBJECTIVE OBJECTIVE
The aim of this study is to identify the number and characteristics of existing publications on introducing AITs to support nursing interventions to detect and manage BPSD early.
METHODS METHODS
A literature review of publications in the PubMed database referring to AITs and dementia was conducted in September 2023. A detailed analysis sought to identify the characteristics of these publications. The results were reported using a narrative approach.
RESULTS RESULTS
A total of 25 publications from 14 countries were identified, with most describing prospective observational studies. We identified three categories of publications on using AITs and they are (1) predicting behaviors and the stages and progression of dementia, (2) screening and assessing clinical symptoms, and (3) managing dementia and BPSD. Most of the publications referred to managing dementia and BPSD.
CONCLUSIONS CONCLUSIONS
Despite growing interest, most AITs currently in use are designed to support psychosocial approaches to treating and caring for existing clinical signs of BPSD. AITs thus remain undertested and underused for the early and real-time detection of BPSD. They could, nevertheless, provide nurses with accurate, reliable systems for assessing, monitoring, planning, and supporting safe therapeutic interventions.

Identifiants

pubmed: 38805252
pii: v7i1e54496
doi: 10.2196/54496
doi:

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

e54496

Informations de copyright

©Sofia Fernandes, Armin von Gunten, Henk Verloo. Originally published in JMIR Nursing (https://nursing.jmir.org), 28.05.2024.

Auteurs

Sofia Fernandes (S)

School of Health Sciences, University of Applied Sciences and Arts Western Switzerland (HES-SO), Sion, Switzerland.
Les Maisons de la Providence Nursing Home, Le Châble, Switzerland.
Faculty of Biology and Medicine, Institute of Higher Education and Research in Healthcare, University of Lausanne, Lausanne, Switzerland.

Armin von Gunten (A)

Service of Old Age Psychiatry, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.

Henk Verloo (H)

School of Health Sciences, University of Applied Sciences and Arts Western Switzerland (HES-SO), Sion, Switzerland.
Service of Old Age Psychiatry, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.

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