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To develop and validate a multidimensional framework for assessing psychological resilience in vocational college students.

March 6, 2026Frontiers in PsychologyOpen Access

AI-enhanced assessment of psychological resilience: development and validation of a multidimensional psychological model in vocational college students

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To develop and validate a multidimensional framework for assessing psychological resilience in vocational college students.
Utilized a dual-track design with a sample size of 1,588 students.
Conducted psychometric analyses that identified a three-factor structure of resilience.
Applied machine learning techniques for predictive validation, specifically the XGBoost model.
Identified tenacity, strength, and optimism as key components of resilience.
Demonstrated measurement invariance across genders.
Achieved an AUC of 0.883 with the XGBoost model, indicating superior predictive ability compared to logistic regression.

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Develops and validates a multidimensional resilience model in vocational college students, indicating AI's role in improving evaluation methods.

Xu et al. (2026) studied this question.

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Develops and validates a multidimensional resilience model in vocational college students, indicating AI's role in improving evaluation methods.