Article
Innovation of Mental Health Education Talent Cultivation Mode Based on Environmental Influence
Authors
Abstract
Actively exploring the factors that influence the construction of mental health education talent cultivation models and identifying effective countermeasures for their reform and innovation are important tasks in contemporary education. This article takes the characteristics and existing problems of mental health education as its starting point, analyzes the relevant issues and environmental influencing factors, and develops a mental health education talent cultivation model integrated with Internet technology. Students from five colleges and universities in Province N were selected as the research subjects. The Kessler-10 (K10) scale was used to quantify students’ mental health levels, and a quality analysis model for mental health education talent cultivation was established based on a multivariate linear regression model estimated using the least squares method. Regression analysis, heterogeneity analysis, and robustness testing were conducted to evaluate the quality of mental health education talent cultivation under different environmental influences, and the results were used to propose optimization strategies. The findings indicate that for every one-unit increase in the level of family education, students’ mental health scale scores decrease by 0.147 units. Compared with female students, male students’ total mental health scale scores increase significantly by 1.35 points for every one standard deviation increase in environmental influences. These results suggest that mental health education talent cultivation models should fully consider the coordinated interaction among families, society, and higher education institutions. Furthermore, the integration of Internet technology into the cultivation process can effectively enhance the quality of talent development.
Keywords
Citation
(2 years)
- DOI: 10.66833/eia-2026-0004
- Type: article
- Source: Engineering and Its Applications
- Published: 2026-09-08
- OpenAlex ID: W7211965104
Published by: Engineering Journals


