A study on the factors influencing university students’ subjective well-being based on machine learning methods
Bibliographic Data
| ID | 15699280 |
|---|---|
| Authors | Yunkun Zhang (Hechi University, corresponding author), Muhammad Syawal Amran (0000-0001-6308-8757, National University of Malaysia), Hazrati Husnin (0000-0002-6165-2411, National University of Malaysia), Lanlan Yin (Hechi University) |
| Year | 2026 |
| Volume | 14 |
| Issue | 1 |
| Publication date | 2026-03-28 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | BMC Psychology (JOURNAL) |
| Journal identifiers | ISSN: 2050-7283 • E-ISSN: 2050-7283 |
| Publisher | BioMed Central (PUBLISHER • GB) |
| DOI | 10.1186/s40359-026-04415-7 |
| PMID | 41897012 |
| OpenAlex | W7141264215 |
| Language | EN |
| References cited | 39 |
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
Animal learning · Experimental psychology · Psychological research · Research methodology · Educational Technology and Pedagogy · Mental Health via Writing · Psychological Well-being and Life Satisfaction
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| Highly cited | No |
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