Developing a music-based digital therapeutic to help manage the neuropsychiatric symptoms of dementia.

agitation anxiety artificial intelligence dementia digital therapeutics music neuropsychiatric symptoms

Journal

Frontiers in digital health
ISSN: 2673-253X
Titre abrégé: Front Digit Health
Pays: Switzerland
ID NLM: 101771889

Informations de publication

Date de publication:
2023
Historique:
received: 10 10 2022
accepted: 02 01 2023
entrez: 6 2 2023
pubmed: 7 2 2023
medline: 7 2 2023
Statut: epublish

Résumé

The greying of the world is leading to a rapid acceleration in both the healthcare costs and caregiver burden that are associated with dementia. There is an urgent need to develop new, easily scalable modalities of support. This perspective paper presents the theoretical background, rationale, and development plans for a music-based digital therapeutic to manage the neuropsychiatric symptoms of dementia, particularly agitation and anxiety. We begin by presenting the findings of a survey we conducted with key opinion leaders. The findings highlight the value of a music-based digital therapeutic for treating neuropsychiatric symptoms, particularly agitation and anxiety. We then consider the neural substrates of these neuropsychiatric symptoms before going on to evaluate randomized control trials on the efficacy of music-based interventions in their treatment. Finally, we present our development plans for the adaptation of an existing music-based digital therapeutic that was previously shown to be efficacious in the treatment of adult anxiety symptoms.

Identifiants

pubmed: 36744277
doi: 10.3389/fdgth.2023.1064115
pmc: PMC9895844
doi:

Types de publication

Journal Article

Langues

eng

Pagination

1064115

Informations de copyright

© 2023 Russo, Mallik, Thomson, de Raadt St. James, Dupuis and Cohen.

Déclaration de conflit d'intérêts

FR has served as an advisor for LUCID since 2018 and as Chief Science Officer since 2021. He has been granted stock options, which may qualify him to financially benefit from commercial applications of the technology considered here. AM, ZT and AR are full-time employees of LUCID and have also been granted stock options, which may qualify them to financially benefit from commercial applications of the technology considered here. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Auteurs

Frank A Russo (FA)

Department of Psychology, Toronto Metropolitan University, Toronto, ON, Canada.
KITE, Toronto Rehabilitation Institute, University Health Network, Toronto, ON, Canada.
LUCID Inc., Toronto, ON, Canada.

Adiel Mallik (A)

LUCID Inc., Toronto, ON, Canada.

Zoe Thomson (Z)

LUCID Inc., Toronto, ON, Canada.

Alexander de Raadt St James (A)

LUCID Inc., Toronto, ON, Canada.

Kate Dupuis (K)

Center for Elder Research, Sheridan College, Oakville, ON, Canada.

Dan Cohen (D)

Right to Music, New York, NY, United States.

Classifications MeSH