Evidence map›Paper›PMID 40376051›Full record

ArticleFrontiers in public health2025

Text analysis of rehabilitation nursing policy in China from the perspective of policy tools.

Wenjia Li, Yuhan Zhu, Xuehua Zhu

Abstract read
In one paragraph

Article in Frontiers in public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

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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

3 authors.

Wenjia LiSchool of Nursing, Zhejiang Chinese Medical University, Hangzhou, China.
Yuhan ZhuSchool of Nursing, Zhejiang Chinese Medical University, Hangzhou, China.
Xuehua ZhuSchool of Nursing, Zhejiang Chinese Medical University, Hangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: This study aims to analyze the specific content and structural characteristics of rehabilitation nursing-related policies in China from 2007 to 2024, utilizing the perspective of policy tools. The goal is to provide insights for the subsequent optimization and enhancement of the rehabilitation nursing policy system. Methods: According to the classification method of policy instruments proposed by public policy scholars Rothwell and Zegveld, this study identified the X dimension (basic policy instrument) and categorized the included policies into demand-oriented, supply-oriented, and environment-based policies. Simultaneously, in light of multi-level service needs, an analysis of the elements constituting the rehabilitation nursing system was conducted in conjunction with existing research. This led to the summarization of five levels within the rehabilitation nursing system: nursing staff, service objectives, service items, service methods, and safeguard measures. These levels were designated as the Y dimension (service system) for this study. Utilizing this two-dimensional analytical framework, researchers classified and coded relevant policy texts that met established criteria. Subsequently, they analyzed their content and performed a quantitative assessment regarding both quantity and distribution patterns. Results: A total of 41 policy documents were analyzed, resulting in the extraction of 292 policy terms, and in dimension X, environment-based, supply-based, and demand-based policy instruments comprised 46.58, 36.64, and 16.78%, respectively. In dimension Y, nursing staff, service objectives, service items, service methods, and safeguard measures accounted for 22.95, 12.67, 12.67, 20.89, and 25.00%, respectively. Overall, the rehabilitation nursing policy in China is predominantly characterized by environment-based policy tools, while demand-based policy tools are comparatively underrepresented. Conclusion: The government has increasingly prioritized rehabilitation nursing care; consequently, the current policy framework is evolving toward greater specialization, standardization, and systematization. Nevertheless, there remains a need to optimize the structural application of policy tools further, particularly concerning enhancing the utilization of demand-side policy instruments.

Indexed as

Health PolicyRehabilitationChinaHumansnursing policypolicy toolspublic healthrehabilitation caretext analysis

Identifiers

PMID40376051
PMCPMC12078275

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LicenceCC BY
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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.