Evidence map›Paper›PMID 40709043›Full record

ArticleFrontiers in public health2025

The impact of social security systems on public health outcomes: an economic perspective on machine translation applications.

Shuhua Niu, Weihua Li, Li-Li

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. 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

3 authors.

Shuhua NiuNantong University, Nantong, China.
Weihua LiNantong University, Nantong, China.
Li-LiTaizhou Vocation College of Science Technology, School of Accounting Finance, Taizhou, Zhejiang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: The relationship between social security systems and public health outcomes has garnered significant attention due to its impact on improving health welfare and promoting economic stability. Social security systems, including pension schemes, healthcare benefits, and unemployment support, are essential for shaping societal wellbeing by influencing healthcare access, labor market participation, and overall economic resilience. However, traditional methods for evaluating these systems often fail to capture the complex dynamics of policy interventions over time. Methods: To address this, we propose an advanced economic policy modeling framework that integrates dynamic optimization techniques with machine translation applications. Machine translation applications refer to the use of automated translation tools to facilitate communication in multilingual contexts, ensuring equal access to healthcare and social services. Results: These applications contribute to the evaluation of social security systems by improving the accessibility and efficiency of service delivery, particularly in linguistically diverse populations. Discussion: By incorporating both economic policy modeling and machine translation technology, our framework offers a comprehensive analysis of social security interventions, demonstrating how well-optimized policies can enhance public health outcomes while ensuring fiscal sustainability.

Indexed as

Models, EconomicPublic HealthSocial SecurityHumansdynamic optimizationeconomic policy modelingpublic healthsocial security systemsstatistical learning

Identifiers

PMID40709043
PMCPMC12287062

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.