ReviewInternational journal of environmental research and public health2023
The Progress of Smart Elderly Care Research: A Scientometric Analysis Based on CNKI and WOS.
Review in International journal of environmental research and public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed, 30 citations in OpenAlex.
- Gamification and Cognitive Factors: Research Hotspots, Knowledge Structure, and Future Directions Based on Bibliometric Analysis.Journal of Intelligence · 2026Article
- Tracing the Evolution of Sleep-Related Behavioural Outcomes Research in Autistic Children: A Scientometric Review.Journal of autism and developmental disorders · 2026Article
- Understanding smart health and elderly care implementation in China: a qualitative TOE-C framework analysis of 24 cases.BMC geriatrics · 2026Article
- A policy instrument-based textual analysis of elderly care policies in the context of low fertility in China.BMC health services research · 2026Article
- Advancements and Innovation Trends of Information Technology Empowering Elderly Care Community Services Based on CiteSpace and VOSViewer.Healthcare (Basel, Switzerland) · 2025Article
- Construction and quantitative evaluation of China's smart older adults care policy: a PMC-index model approach.Frontiers in public health · 2025Article
- Understanding older people's intentions to use smart elderly care applications in China: an extension of the UTAUT2 model.Frontiers in public health · 2025Article
- Coupling coordination evaluation and influencing factors analysis of older adult care service resource supply and demand in China.Frontiers in public health · 2025Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
To reduce the burden caused by an increased elderly population and to provide efficient service resources, scholars worldwide have proposed and applied smart elderly care. This paper summarizes the hotspots of the existing literature and explores the research frontiers to ignite future research. CiteSpace software was used to conduct a scientometric analysis of high-quality literature collected from both the China National Knowledge Infrastructure (CNKI) and the Web of Science (WOS). Based on the results of the basic situation description, this article highlights six research hotspots in CNKI and 11 research themes in WOS. In addition, it offers three major evolution stages and three future research directions for smart elderly care research. This paper provides a holistic overview of the smart elderly care literature from two major global databases. The results will contribute to healthcare policy designers, practitioners, and developers by giving them comprehensive knowledge and generating strategies to enhance elderly people's quality of life.
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.