An Early Warning Study of College Students’ Mental Health Risk Based on Dual-Factor Modeling
Authors
Jia Guo1, Feifei Wang2, *
1Chongqing Business Vocational College, Chongqing, China
2Department of Developmental Psychology of Armymen, Department of Medical Psychology, Army Medical University, Chongqing, China
*Corresponding author.
Email: wff_0918@163.com
Corresponding Author
Feifei Wang
Available Online 29 July 2024.
- DOI
- 10.2991/978-2-38476-271-2_9How to use a DOI?
- Keywords
- College Student; Mental health; Dual-Factor Model·Risk Early Warning
- Abstract
This study analyzes how to carry out early warning of mental health risks of college students based on the dual-factor model. We understand the dual-factor theoretical model of mental health. The influencing factors of mental health are analyzed in terms of both protective factors and risk factors. This leads to how to carry out mental health risk early warning and construct a mental health risk early warning model for college students. The field of mental health risk early warning for college students has become a new trend in mental health research.
- Copyright
- © 2024 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Jia Guo AU - Feifei Wang PY - 2024 DA - 2024/07/29 TI - An Early Warning Study of College Students’ Mental Health Risk Based on Dual-Factor Modeling BT - Proceedings of the 2024 5th International Conference on Mental Health, Education and Human Development (MHEHD 2024) PB - Atlantis Press SP - 58 EP - 64 SN - 2352-5398 UR - https://doi.org/10.2991/978-2-38476-271-2_9 DO - 10.2991/978-2-38476-271-2_9 ID - Guo2024 ER -