Evidence map›Paper›PMID 41945623›Full record

ArticlePloS one2026

Rejection or support? research on labor participation strategy of older adults based on three-party evolutionary game.

Yan Shen, Yingying Zhong, Fei Sun

Abstract read
In one paragraph

Article in PloS one, 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

3 authors.

Yan ShenSchool of Economics, Management, and Law, Hubei Normal University, Huangshi, Hubei, China.ORCID https://orcid.org/0000-0002-8950-2802
Yingying ZhongSchool of Economics, Management, and Law, Hubei Normal University, Huangshi, Hubei, China.ORCID https://orcid.org/0009-0002-1944-2143
Fei SunSchool of Social Work, Michigan State University, East Lansing, Michigan, United States of America.ORCID https://orcid.org/0000-0001-6291-1879

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To address the demographic challenges posed by accelerated aging and shrinking labor force, it is crucial to develop human resources and encourage labor participation among older adults to achieve active aging. This study constructs a three-party evolutionary game model involving government departments, local enterprises, and older workers based on evolutionary game theory. It analyses the strategic choices of each party during the gaming process and their evolutionary strategies under different conditions, with numerical simulations conducted to examine the impact of parameter adjustments on these evolutionary dynamics. The findings indicate that: the effectiveness of digital government construction serves as a critical determinant for governmental support of older adults' labor participation; the probability of enterprises actively employing older workers correlates with both the outcomes of corporate digital transformation and labor costs associated with older adults' employment; older individuals' likelihood of labor participation relates to employment income and age discrimination, while digital technology empowerment facilitates strategic shifts from negative to positive engagement for both government and enterprises. Based on these conclusions, policy recommendations including strengthening digital government development, accelerating enterprise digital transformation, and fostering age-friendly employment environments are proposed, thereby providing theoretical foundations for implementing national strategies addressing the labor shortage challenges due to population aging.

Indexed as

AgingEmploymentGame TheoryAgedHumans

Identifiers

PMID41945623
PMCPMC13056212

What OpenQuestion holds

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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.