Author
Listed:
- Justin Chew
(Department of Geriatric Medicine, Tan Tock Seng Hospital, Singapore 308433, Singapore
Institute of Geriatrics and Active Aging, Tan Tock Seng Hospital, Singapore 308433, Singapore)
- Zhiwei Zeng
(Joint NTU-UBC Research Centre of Excellence in Active Living for the Elderly (LILY), Nanyang Technological University, Singapore 639798, Singapore)
- Toh Hsiang Benny Tan
(Joint NTU-UBC Research Centre of Excellence in Active Living for the Elderly (LILY), Nanyang Technological University, Singapore 639798, Singapore)
- Pamela Chew
(Department of Psychology, Tan Tock Seng Hospital, Singapore 308433, Singapore)
- Noorhazlina Ali
(Department of Geriatric Medicine, Tan Tock Seng Hospital, Singapore 308433, Singapore
Institute of Geriatrics and Active Aging, Tan Tock Seng Hospital, Singapore 308433, Singapore)
- Hao Wang
(Joint NTU-UBC Research Centre of Excellence in Active Living for the Elderly (LILY), Nanyang Technological University, Singapore 639798, Singapore)
- Melissa Ong
(Institute of Geriatrics and Active Aging, Tan Tock Seng Hospital, Singapore 308433, Singapore)
- Roslyn Raymond
(Institute of Geriatrics and Active Aging, Tan Tock Seng Hospital, Singapore 308433, Singapore)
- Kalene Pek
(Institute of Geriatrics and Active Aging, Tan Tock Seng Hospital, Singapore 308433, Singapore)
- Di Wang
(Joint NTU-UBC Research Centre of Excellence in Active Living for the Elderly (LILY), Nanyang Technological University, Singapore 639798, Singapore)
- Liang Zhang
(Joint NTU-UBC Research Centre of Excellence in Active Living for the Elderly (LILY), Nanyang Technological University, Singapore 639798, Singapore)
- Zhiqi Shen
(Joint NTU-UBC Research Centre of Excellence in Active Living for the Elderly (LILY), Nanyang Technological University, Singapore 639798, Singapore
College of Computing and Data Science, Nanyang Technological University, Singapore 639798, Singapore)
- Cyril Leung
(Joint NTU-UBC Research Centre of Excellence in Active Living for the Elderly (LILY), Nanyang Technological University, Singapore 639798, Singapore)
- Jing Jih Chin
(Department of Geriatric Medicine, Tan Tock Seng Hospital, Singapore 308433, Singapore
Institute of Geriatrics and Active Aging, Tan Tock Seng Hospital, Singapore 308433, Singapore)
- Wee Shiong Lim
(Department of Geriatric Medicine, Tan Tock Seng Hospital, Singapore 308433, Singapore
Institute of Geriatrics and Active Aging, Tan Tock Seng Hospital, Singapore 308433, Singapore
Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore 308232, Singapore)
- Chunyan Miao
(Joint NTU-UBC Research Centre of Excellence in Active Living for the Elderly (LILY), Nanyang Technological University, Singapore 639798, Singapore
College of Computing and Data Science, Nanyang Technological University, Singapore 639798, Singapore)
Abstract
Background: Current research highlights the importance of addressing multiple risk factors concurrently to tackle the complex etiology of dementia. However, limited evidence exists on the efficacy of technology-driven, multidomain community-based interventions for preventing cognitive decline. Objectives: To evaluate the efficacy of ADL+, an artificial intelligence (AI)-enabled digital toolkit integrating cognitive assessments and multidomain interventions, on outcomes of cognitive function, activity levels, and quality of life in older adults at risk of cognitive decline. Adherence and usability were also evaluated. Methods: We conducted a quasi-experimental study including community-dwelling older adults aged 60 years and above without dementia, but with subjective memory complaints (AD8 score ≥ 2). Participants received a six-month intervention (app-based cognitive training, personalized nutritional, physical, and social activities recommendations) or a control group treatment (cognitive health educational package). The primary outcome was a change in neuropsychological test battery (NTB) Z-scores (NTB composite and its individual domains: attention, processing speed, memory, and executive function). Secondary outcomes were activity levels (Frenchay Activities Index, FAI), and quality of life (EQ-5D). Outcomes were assessed at the end of the intervention and three months post-intervention using linear mixed-effects models. Results: 96% of participants in the intervention and 89% in the control group completed the study. At six months, the intervention group showed a significant NTB composite score improvement (mean change: 0.086 (95% CI 0.020 to 0.15)), with a between-group difference of 0.17 (95% CI 0.071 to 0.27). Significant differences in attention, processing speed, and memory domains were observed, with benefits sustained in the processing speed domain at nine months. The control group’s FAI scores declined at six months (mean change: −1.04 (95% CI −1.83 to −0.26)), while the intervention group’s scores remained stable. The intervention group’s EQ-5D visual analogue scale (VAS) scores improved at both six and nine months, with between-group differences of 4.06 (95% CI 0.23 to 7.90) at six months and 5.12 (95% CI 0.81 to 9.43) at nine months. Adherence was high, while average usability scores were obtained. Conclusions: The ADL+ toolkit shows potential beneficial effects on cognitive function, activity levels, and quality of life for older adults at risk of cognitive decline. Findings will guide future randomized controlled trials and implementation efforts.
Suggested Citation
Justin Chew & Zhiwei Zeng & Toh Hsiang Benny Tan & Pamela Chew & Noorhazlina Ali & Hao Wang & Melissa Ong & Roslyn Raymond & Kalene Pek & Di Wang & Liang Zhang & Zhiqi Shen & Cyril Leung & Jing Jih Ch, 2024.
"ADL+: A Digital Toolkit for Multidomain Cognitive, Physical, and Nutritional Interventions to Prevent Cognitive Decline in Community-Dwelling Older Adults,"
IJERPH, MDPI, vol. 22(1), pages 1-17, December.
Handle:
RePEc:gam:jijerp:v:22:y:2024:i:1:p:42-:d:1557517
Download full text from publisher
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:22:y:2024:i:1:p:42-:d:1557517. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.