ArticleJMIR aging2020
Artificial Intelligence-Powered Digital Health Platform and Wearable Devices Improve Outcomes for Older Adults in Assisted Living Communities: Pilot Intervention Study.
Article in JMIR aging, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 4 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
28 citing papers in PubMed, 4 syntheses or guidelines pooled it, 53 citations in OpenAlex.
- Artificial Intelligence Applications in Medical Devices for Personalized Health Care Solutions: Systematic Review.Journal of medical Internet research · 2026Pooled it
- A systematic review on the efficacy of artificial intelligence in geriatric healthcare: a critical analysis of current literature.BMC geriatrics · 2025Pooled it
- Wearable Artificial Intelligence for Detecting Anxiety: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2023Pooled it
- Artificial intelligence for older people receiving long-term care: a systematic review of acceptability and effectiveness studies.The lancet. Healthy longevity · 2022Pooled it
- A Multidimensional Digital Health Platform to Support Intrinsic Capacity and Healthy Aging: Pilot Feasibility Study.JMIR aging · 2026Article
- Artificial Intelligence Empowers Physical Therapy for Older Adults: A Perspective.Health science reports · 2026Article
- The Role of Artificial Intelligence in Medication Management for Older Adults: A Systematic Review.Aging medicine (Milton (N.S.W)) · 2026Review
- The Role of AI in Improving Digital Wellness Among Older Adults: Comparative Bibliometric Analysis.JMIR AI · 2026Article
- Family caregivers' acceptance of Artificial Intelligence-enabled technologies for providing care to older adults.BMC geriatrics · 2025Article
- Advanced Oral Delivery Systems for Nutraceuticals.Advanced healthcare materials · 2025Review
- Advancements and Innovation Trends of Information Technology Empowering Elderly Care Community Services Based on CiteSpace and VOSViewer.Healthcare (Basel, Switzerland) · 2025Article
- Leveraging Mobile Health and Wearable Technologies for the Prevention and Management of Atherosclerotic Cardiovascular Disease.Current atherosclerosis reports · 2025Review
- Observational
- The PDC30 Chatbot-Development of a Psychoeducational Resource on Dementia Caregiving Among Family Caregivers: Mixed Methods Acceptability Study.JMIR aging · 2025Article
- Enhancement or suppression: a double-edged sword? Differential association of digital literacy with subjective health of older adult-evidence from China.Frontiers in public health · 2024Article
- Article
- Article
- Applications of Artificial Intelligence to Obesity Research: Scoping Review of Methodologies.Journal of medical Internet research · 2022Article
- Nursing Home-Sensitive Hospitalizations and the Relevance of Telemedicine: A Scoping Review.International journal of environmental research and public health · 2022Article
- Wearable Sensors for Healthcare: Fabrication to Application.Sensors (Basel, Switzerland) · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundWearables and artificial intelligence (AI)-powered digital health platforms that utilize machine learning algorithms can autonomously measure a senior's change in activity and behavior and may be useful tools for proactive interventions that target modifiable risk factors.
objectiveThe goal of this study was to analyze how a wearable device and AI-powered digital health platform could provide improved health outcomes for older adults in assisted living communities.
methodsData from 490 residents from six assisted living communities were analyzed retrospectively over 24 months. The intervention group (+CP) consisted of 3 communities that utilized CarePredict (n=256), and the control group (-CP) consisted of 3 communities (n=234) that did not utilize CarePredict. The following outcomes were measured and compared to baseline: hospitalization rate, fall rate, length of stay (LOS), and staff response time.
resultsThe residents of the +CP and -CP communities exhibit no statistical difference in age (P=.64), sex (P=.63), and staff service hours per resident (P=.94). The data show that the +CP communities exhibited a 39% lower hospitalization rate (P=.02), a 69% lower fall rate (P=.01), and a 67% greater length of stay (P=.03) than the -CP communities. The staff alert acknowledgment and reach resident times also improved in the +CP communities by 37% (P=.02) and 40% (P=.02), respectively.
conclusionsThe AI-powered digital health platform provides the community staff with actionable information regarding each resident's activities and behavior, which can be used to identify older adults that are at an increased risk for a health decline. Staff can use this data to intervene much earlier, protecting seniors from conditions that left untreated could result in hospitalization. In summary, the use of wearables and AI-powered digital health platform can contribute to improved health outcomes for seniors in assisted living communities. The accuracy of the system will be further validated in a larger trial.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.