SynthesisBMC geriatrics2025
A systematic review on the efficacy of artificial intelligence in geriatric healthcare: a critical analysis of current literature.
Synthesis in BMC geriatrics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
5 citing papers in PubMed.
- Assessing the Value for Money of AI-Assisted Technologies for Older Adults: Scoping Review of Economic Evaluations.Journal of medical Internet research · 2026Article
- Generational Differences in the Acceptance of Care Robots Among Portuguese Adults: Evidence from the Almere Model, ADL and IADL Frameworks.Healthcare (Basel, Switzerland) · 2026Article
- Mapping research trends and competency domains in nursing-related digital and artificial intelligence technologies: A bibliometric analysis.International journal of nursing sciences · 2026Review
- AI-Assisted Dynamic Postural Control Screening to Improve Functional Mobility in Older Adult Populations: Quasi-Experimental Study.JMIR aging · 2025Article
- Use of Artificial Intelligence, Internet of Things, and Edge Intelligence in Long-Term Care for Older People: Comprehensive Analysis Through Bibliometric, Google Trends, and Content Analysis.Journal of medical Internet research · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo carry out systematic analysis of existing literature on role of Artificial Intelligence in geriatric patient healthcare.
methodsA detailed online search was carried out using search phrases in reliable sources of information like Pubmed database, Embase database, Ovid database, Global Health database, PsycINFO, and Web of Science. Study specific information was gathered, including the organisation, year of publication, nation, setting, design of the research, information about population, size of study sample, group dynamics, eligibility and exclusion requirements, information about intervention, duration of exposure to the intervention , comparators, details of outcome measures, scheduling of evaluations, and consequences. After information gathering, the reviewers gathered to discuss any differences.
resultsThirty-one studies were finally selected for systemic review. Although there was some disagreement on the acceptance of AI-enhanced treatments in LTC settings, this review indicated that there was little consensus about the efficacy of those initiatives for older individuals. Social robots have been shown to increase social interaction and mood, but the data was more conflicting and less definitive for the other innovations and consequences. The majority of research evaluated a variety of results, which made it impossible to synthesise them in a meaningful way and prevented a meta-analysis. In addition, many studies have moderate to severe bias risks due to underpowered design
conclusionIt is challenging to determine whether AI supplemented technologies for geriatric patients are significantly beneficial. Although some encouraging findings were made, more study is required.
Indexed as
Identifiers
What OpenQuestion holds
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.