The association between mindfulness, psychological flexibility, and rumination in predicting mental health and well-being among university students using machine learning and structural equation modeling
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作者:
Feng, Ruohan
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Georgia Inst Technol, Sch Psychol, North Ave, Atlanta, GA 30332 USAGeorgia Inst Technol, Sch Psychol, North Ave, Atlanta, GA 30332 USA
Feng, Ruohan
[1
]
Mishra, Vaibhav
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Georgia Inst Technol, Sch Comp Sci, Atlanta, GA 30332 USAGeorgia Inst Technol, Sch Psychol, North Ave, Atlanta, GA 30332 USA
Mishra, Vaibhav
[2
]
Hao, Xin
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Vanderbilt Univ, Dept Psychol & Human Dev, Nashville, TN 37235 USAGeorgia Inst Technol, Sch Psychol, North Ave, Atlanta, GA 30332 USA
Hao, Xin
[3
]
Verhaeghen, Paul
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Georgia Inst Technol, Sch Psychol, North Ave, Atlanta, GA 30332 USAGeorgia Inst Technol, Sch Psychol, North Ave, Atlanta, GA 30332 USA
Verhaeghen, Paul
[1
]
机构:
[1] Georgia Inst Technol, Sch Psychol, North Ave, Atlanta, GA 30332 USA
[2] Georgia Inst Technol, Sch Comp Sci, Atlanta, GA 30332 USA
[3] Vanderbilt Univ, Dept Psychol & Human Dev, Nashville, TN 37235 USA
Objectives: This study explores the intricate relationships between mindfulness, psychological flexibility, rumination, and their combined impact on mental health and well-being. Methods: Random forest regression on survey data from 524 undergraduate students was used to identify significant predictors from a comprehensive set of psychological variables. Neural networks were then trained on various combinations of these predictors to evaluate their performance in predicting mental health and wellbeing outcomes. Finally, structural equation modeling (SEM) was employed to validate a model based on the identified key predictors, focusing on pathways from mindfulness through psychological flexibility to rumination and well-being. Results: The random forest analysis revealed that the mindfulness variables exerted their influence partially indirectly through psychological flexibility and rumination. The deep neural network analysis supported these findings and additionally showed that the mindfulness manifold model (consisting of self-awareness, self-regulation, and self-transcendence) was superior to the Five Facet Mindfulness Questionnaire variables in predicting mental health outcomes. The SEM analysis confirmed that psychological flexibility, particularly its avoidance and acceptance components, mediated the relationship between mindfulness and mental health. The hypothesized serial mediation pathway-mindfulness affecting psychological flexibility, which then influences rumination and subsequently mental health and well-being-was supported by the data. Self-transcendence was a particularly powerful predictor of mental health outcomes. Conclusions: The findings underscore the critical role of psychological flexibility and rumination in mediating the effects of mindfulness on mental health and well-being, suggesting that enhancing mindfulness and psychological flexibility might significantly reduce rumination, thereby improving overall mental health and well-being.