Analysis of mental health status assessment of college students based on interpolation and fitting algorithm
Pubblicato online: 21 ott 2023
Ricevuto: 08 gen 2023
Accettato: 01 mag 2023
DOI: https://doi.org/10.2478/amns.2023.2.00706
Parole chiave
© 2023 Juhu Ou, published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.
For common psychological problems among college students, the current mental health assessment methods are analyzed, and the least squares method of curve fitting is chosen for this paper. Based on the interrelationship between personality traits and mental health and the correlation between perceived campus climate and mental health inequalities, factors affecting the mental health status of college students were identified. The OLS and 2SLS algorithms, as well as the stepwise addition of control variables, were used for empirical testing, and a binary regression analysis model was established for individual UPI score values and mean UPI score values, and the results showed a peer effect coefficient of 0.654, which verified the existence of a significant positive peer effect of campus environment on college student’s mental health level.