A study on the factors influencing university students' subjective well-being based on machine learning methods.

Yunkun Zhang, Muhammad Syawal Amran, Hazrati Husnin, Lanlan Yin

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

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1 · What the graph read from it

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5 · Who and what money

Authors and funding

4 authors.

Yunkun ZhangHechi University, Yizhou, Guangxi, 546300, China. ykzhang@hcnu.edu.cn.

Muhammad Syawal AmranFaculty of Education, Universiti Kebangsaan Malaysia, Bandar Baru Bangi , Selangor, 43600, Malaysia.

Hazrati HusninFaculty of Education, Universiti Kebangsaan Malaysia, Bandar Baru Bangi , Selangor, 43600, Malaysia.

Lanlan YinHechi University, Yizhou, Guangxi, 546300, China. llyin@hcnu.edu.cn.

Funding

14th Five-Year Plan' 2022 + "Research and Practice on the Reform of Moral Education Evaluation in Colleges and Universities in Ethnic Minority Areas under the Concept of Cultivating Virtue and Nurturing Talent" (Project Number: 2022ZJY651) 2022ZJY651

6 · The paper itself

Abstract

Subjective well-being is a key area of research in psychology. Based on survey data from 384 university students, this study employed automated machine learning methods to construct a predictive model of subjective well-being, in which the Support Vector Machine (SVM) model performed best, achieving an overall prediction accuracy of 81.81%. The results indicate that the overall subjective well-being of the current university student population is relatively high; depression and interpersonal sensitivity are the most significant influencing factors, followed by hostility and paranoid ideation, among others. Family emotion also has a significant impact on subjective well-being. Based on these findings, fostering positive psychological traits and optimizing family functioning are suggested as approaches to enhance university students’ subjective well-being, thereby promoting their academic achievement and mental health development.

Indexed as

Machine LearningPsychological Well-BeingStudentsAdultFemaleHumansMalePrediction AlgorithmsPredictive Learning ModelsSupport Vector MachineUniversitiesYoung AdultFamily functioningMachine learning methodsPsychological risk factorsSubjective well-being

Identifiers

PMID41897012

DOI10.1186/s40359-026-04415-7

PMCPMC13151176

What Socratic holds

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LicenceCC BY

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