Objective: To explore the influencing factors of psychological crisis risk in college students and to construct and validate a crisis risk prediction model.
Methods: Using 1 879 college students from initial interviews enrolled in the Psychological Centre of Zhejiang University from September 2019 to April 2021 as research subjects, univariate logistic regression and Lasso regression were used to screen characteristic variables of crisis risk. A random sampling method was used to divide the subject into a training set and a validation set at a ratio of 7:3. A multi-factor logistic regression analysis model was constructed in the training set, and the discriminative ability of this model was verified separately in the training and validation sets.
Results: In this study, there were 255 (13.4%) cases of college students at risk of crisis. Univariate logistic regression and Lasso regression were used to screen out six relevant variables of crisis risk. The results of the multi-factorial regression analysis showed that ‘interpersonal relationships’(p=0.007),‘ college’(p<0.05), ‘student status’(p≤0.001), ‘suicidal thoughts’(p<0.001), and ‘substance use’(p=0.005) were independent risk factors for crisis risk. The validation analysis results indicated that the predictive model had good discrimination, with an area under the curve (AUC) of 0.834.
Conclusion: The risk prediction model constructed in this study has good discriminative ability and can be used to guide the early identification and timely intervention of high-risk students with crisis risk in mental health work in colleges.
ZHU Yihong
,
HUANG Fang
,
LIU Yan
,
LIU Dandan
,
TAN Lunyu
. Building a Predictive Model for Psychological Crisis Risk of College Students Based on Lasso-Logistic Regression[J]. Psychological Communications, 2023
, 6(4)
: 198
-204
.
DOI: 10.12100/j.issn.2096-5494.223031
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