Evidence map›Paper›PMID 39813189›Full record

ArticlePloS one2025

Do higher educated people feel happier?-Evidence of Han and minority nationalities from China.

Yuanyuan Wang, Zhenyi Hu, Jiameng Yuan, Kun Zhang

Abstract read
In one paragraph

Article in PloS one, 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

4 authors.

Yuanyuan WangSchool of Accounting, Hebei University of Economics and Business, Shijiazhuang, Hebei, China.
Zhenyi HuSchool of Economics, Hebei University of Economics and Business, Shijiazhuang, Hebei, China.ORCID 0009-0007-0833-7109
Jiameng YuanBusiness School, The University of Sydney, Camperdown, New South Wales, Australia.
Kun ZhangSchool of Economics, Guangdong University of Technology, Guangzhou, Guangdong, China.ORCID 0009-0001-8388-5259

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Based on the data of China General Social Survey (CGSS), this study adopts empirical analysis method to explore the impact of education on residents' subjective well-being and its differentiated mechanism in different ethnic groups. The results show that, first of all, education significantly improves residents' subjective well-being, and the conclusion is still robust after controlling for endogenous problems. Secondly, compared with Han nationality, education has a more significant effect on the subjective well-being of ethnic minority residents. Finally, by comparing the internal mechanism of education on the subjective well-being of Han and ethnic minority residents, the research finds that education mainly improves subjective well-being by improving residents' relative income level and enhancing their social class identification, in which the intermediary effect of income is particularly prominent. However, in the Han population, education may weaken the sense of fairness, and thus reduce happiness to some extent; This phenomenon has not been verified in ethnic minority groups. This study not only expands the literature on the relationship between education and subjective well-being, but also has important policy implications, providing a strong empirical basis for formulating more accurate education policies, improving the happiness of ethnic minority residents, and enhancing national cohesion.

Indexed as

Educational StatusEthnicityHappinessMinority GroupsAdultChinaEast Asian PeopleFemaleHumansMaleMiddle AgedSurveys and QuestionnairesYoung Adult

Identifiers

PMID39813189
PMCPMC11735008

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.