Evidence map›Paper›PMID 42410846›Full record

ArticleMedicine2026

Research status and trends analysis of long-term care: A bibliometric analysis.

Qingquan Pang, Shihua Xu, Yun Zhao, Yue Li, Yongping Nong, Haidan Qin, Xianlin Bi

Abstract read
In one paragraph

Article in Medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Qingquan PangSchool of Public Health and Management, Youjiang Medical University for Nationalities, Baise, Guangxi, China.
Shihua XuSchool of Public Health and Management, Youjiang Medical University for Nationalities, Baise, Guangxi, China.
Yun ZhaoSchool of Management, Xuzhou Medical University, Xuzhou, Jiangsu, China.
Yue LiThe Affiliated Hospital of Youjiang Medical College for Nationalities, Baise, Guangxi, China.
Yongping NongSchool of Public Health and Management, Youjiang Medical University for Nationalities, Baise, Guangxi, China.
Haidan QinSchool of Public Health and Management, Youjiang Medical University for Nationalities, Baise, Guangxi, China.
Xianlin BiSchool of Public Health and Management, Youjiang Medical University for Nationalities, Baise, Guangxi, China.ORCID 0009-0008-0003-3626

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Long-term care (LTC) is a fundamental system in many countries that provides essential aged care services and promotes the physical and mental well-being of older adults. This study visually maps the progress and trends in LTC research, offering theoretical references for fellow scholars and practitioners. Using the Web of Science Core Collection as the data source, we retrieved publications on LTC from 2010 to 2024. CiteSpace bibliometric software was employed with a time slice of 1 year and a selection threshold of top 50 per slice. Co-occurrence and collaboration networks were analyzed for keywords, authors, and institutions. The United States contributed the highest number of publications (1896). Among journals, The Lancet published the most articles (2568). The University of Toronto exhibited the strongest centrality (0.23). The top 5 most frequent keywords were "long-term care" (1666 occurrences), "dementia" (726), "nursing home" (674), "health" (615), and "older adult" (551). Qualitative synthesis further identified major research themes including long-term mortality among LTC recipients, nursing home residents, LTC insurance, pragmatic trials, and social isolation. Author collaboration networks showed only small clusters with weak overall connectivity; institutional collaborations were also limited, predominantly involving universities. This fragmented cooperation pattern did not improve significantly over time, providing a critical benchmark for evaluating the effectiveness of academic community building within the field. Notably, all high-frequency keywords exhibited extremely low centrality values (0.01-0.02), indicating that while a large volume of research centers on a few core terms, the knowledge linkages between these topics and broader research issues remain weak. Additionally, burst detection revealed strong emergence of terms such as "unit" and "setting," further highlighting an exceptionally high concentration of research attention on micro-level care facility issues. Future research should strengthen international collaboration at the macro-level, expand the target population of LTC to a wider range of older adults at the meso level, and address the chronic disease needs of older individuals at the micro-level, thereby advancing the development of LTC systems.

Indexed as

BibliometricsLong-Term CareAgedHumansNursing HomesCiteSpacelong-term carepension servicespopulation aging

Identifiers

PMID42410846
PMCPMC13337040

What OpenQuestion holds

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LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.