Remote Evaluation of Sleep and Circadian Rhythms in Older Adults With Mild Cognitive Impairment and Dementia: Protocol for a Feasibility and Acceptability Mixed Methods Study.

Alzheimer Alzheimer disease Lewy body disease Parkinson accelerometery acceptability app application cognitive cognitive impairment dementia electroencephalography feasibility mild cognitive impairment mobile applications mobile phone research risk factor sleep sleep disturbance sleeping smart device wearable wearable devices wearables

Journal

JMIR research protocols
ISSN: 1929-0748
Titre abrégé: JMIR Res Protoc
Pays: Canada
ID NLM: 101599504

Informations de publication

Date de publication:
22 Mar 2024
Historique:
received: 19 09 2023
accepted: 13 02 2024
revised: 12 02 2024
medline: 22 3 2024
pubmed: 22 3 2024
entrez: 22 3 2024
Statut: epublish

Résumé

Sleep disturbances are a potentially modifiable risk factor for neurodegenerative dementia secondary to Alzheimer disease (AD) and Lewy body disease (LBD). Therefore, we need to identify the best methods to study sleep in this population. This study will assess the feasibility and acceptability of various wearable devices, smart devices, and remote study tasks in sleep and cognition research for people with AD and LBD. We will deliver a feasibility and acceptability study alongside a prospective observational cohort study assessing sleep and cognition longitudinally in the home environment. Adults aged older than 50 years who were diagnosed with mild to moderate dementia or mild cognitive impairment (MCI) due to probable AD or LBD and age-matched controls will be eligible. Exclusion criteria include lack of capacity to consent to research, other causes of MCI or dementia, and clinically significant sleep disorders. Participants will complete a cognitive assessment and questionnaires with a researcher and receive training and instructions for at-home study tasks across 8 weeks. At-home study tasks include remote sleep assessments using wearable devices (electroencephalography headband and actigraphy watch), app-based sleep diaries, online cognitive assessments, and saliva samples for melatonin- and cortisol-derived circadian markers. Feasibility outcomes will be assessed relating to recruitment and retention, data completeness, data quality, and support required. Feedback on acceptability and usability will be collected throughout the study period and end-of-study interviews will be analyzed using thematic analysis. Recruitment started in February 2022. Data collection is ongoing, with final data expected in February 2024 and data analysis and publication of findings scheduled for the summer of 2024. This study will allow us to assess if remote testing using smart devices and wearable technology is a viable alternative to traditional sleep measurements, such as polysomnography and questionnaires, in older adults with and without MCI or dementia due to AD or LBD. Understanding participant experience and the barriers and facilitators to technology use for research purposes and remote research in this population will assist with the development of, recruitment to, and retention within future research projects studying sleep and cognition outside of the clinic or laboratory. DERR1-10.2196/52652.

Sections du résumé

BACKGROUND BACKGROUND
Sleep disturbances are a potentially modifiable risk factor for neurodegenerative dementia secondary to Alzheimer disease (AD) and Lewy body disease (LBD). Therefore, we need to identify the best methods to study sleep in this population.
OBJECTIVE OBJECTIVE
This study will assess the feasibility and acceptability of various wearable devices, smart devices, and remote study tasks in sleep and cognition research for people with AD and LBD.
METHODS METHODS
We will deliver a feasibility and acceptability study alongside a prospective observational cohort study assessing sleep and cognition longitudinally in the home environment. Adults aged older than 50 years who were diagnosed with mild to moderate dementia or mild cognitive impairment (MCI) due to probable AD or LBD and age-matched controls will be eligible. Exclusion criteria include lack of capacity to consent to research, other causes of MCI or dementia, and clinically significant sleep disorders. Participants will complete a cognitive assessment and questionnaires with a researcher and receive training and instructions for at-home study tasks across 8 weeks. At-home study tasks include remote sleep assessments using wearable devices (electroencephalography headband and actigraphy watch), app-based sleep diaries, online cognitive assessments, and saliva samples for melatonin- and cortisol-derived circadian markers. Feasibility outcomes will be assessed relating to recruitment and retention, data completeness, data quality, and support required. Feedback on acceptability and usability will be collected throughout the study period and end-of-study interviews will be analyzed using thematic analysis.
RESULTS RESULTS
Recruitment started in February 2022. Data collection is ongoing, with final data expected in February 2024 and data analysis and publication of findings scheduled for the summer of 2024.
CONCLUSIONS CONCLUSIONS
This study will allow us to assess if remote testing using smart devices and wearable technology is a viable alternative to traditional sleep measurements, such as polysomnography and questionnaires, in older adults with and without MCI or dementia due to AD or LBD. Understanding participant experience and the barriers and facilitators to technology use for research purposes and remote research in this population will assist with the development of, recruitment to, and retention within future research projects studying sleep and cognition outside of the clinic or laboratory.
INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID) UNASSIGNED
DERR1-10.2196/52652.

Identifiants

pubmed: 38517469
pii: v13i1e52652
doi: 10.2196/52652
doi:

Types de publication

Journal Article

Langues

eng

Pagination

e52652

Informations de copyright

©Victoria Grace Gabb, Jonathan Blackman, Hamish Duncan Morrison, Bijetri Biswas, Haoxuan Li, Nicholas Turner, Georgina M Russell, Rosemary Greenwood, Amy Jolly, William Trender, Adam Hampshire, Alan Whone, Elizabeth Coulthard. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 22.03.2024.

Auteurs

Victoria Grace Gabb (VG)

Bristol Medical School, University of Bristol, Bristol, United Kingdom.
Neurology Department, Bristol Brain Centre, North Bristol NHS Trust, Bristol, United Kingdom.

Jonathan Blackman (J)

Bristol Medical School, University of Bristol, Bristol, United Kingdom.
Neurology Department, Bristol Brain Centre, North Bristol NHS Trust, Bristol, United Kingdom.

Hamish Duncan Morrison (HD)

Bristol Medical School, University of Bristol, Bristol, United Kingdom.
Neurology Department, Bristol Brain Centre, North Bristol NHS Trust, Bristol, United Kingdom.

Bijetri Biswas (B)

Bristol Medical School, University of Bristol, Bristol, United Kingdom.

Haoxuan Li (H)

Bristol Medical School, University of Bristol, Bristol, United Kingdom.
Neurology Department, Bristol Brain Centre, North Bristol NHS Trust, Bristol, United Kingdom.
King's College Hospital, King's College Hospital NHS Foundation Trust, London, United Kingdom.
Bristol Royal Infirmary, University Hospitals Bristol and Weston NHS Foundation Trust, Bristol, United Kingdom.

Nicholas Turner (N)

Bristol Medical School, University of Bristol, Bristol, United Kingdom.

Georgina M Russell (GM)

Bristol Medical School, University of Bristol, Bristol, United Kingdom.

Rosemary Greenwood (R)

Bristol Medical School, University of Bristol, Bristol, United Kingdom.
Research & Innovation, University Hospitals Bristol and Weston NHS Foundation Trust, Bristol, United Kingdom.

Amy Jolly (A)

Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, United Kingdom.
UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom.

William Trender (W)

Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, United Kingdom.

Adam Hampshire (A)

Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, United Kingdom.

Alan Whone (A)

Bristol Medical School, University of Bristol, Bristol, United Kingdom.
Neurology Department, Bristol Brain Centre, North Bristol NHS Trust, Bristol, United Kingdom.

Elizabeth Coulthard (E)

Bristol Medical School, University of Bristol, Bristol, United Kingdom.
Neurology Department, Bristol Brain Centre, North Bristol NHS Trust, Bristol, United Kingdom.

Classifications MeSH