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Psychometric validation and measurement invariance of the Arabic version of the problem-solving inventory-20: An instrument validation study in AI-supported learning
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DOI:10.1016/j.nepr.2026.104798.png)
Abstract
En 中文
Aim: This study aimed to translate and validate the Arabic PSI-20, examine its psychometric properties, test measurement invariance across key subgroups and establish an optimal cut-off score. Background: Problem-solving ability (PSA) is a core cognitive competence underpinning nursing students' academic success, clinical reasoning and professional readiness. Although the Problem-Solving Inventory-20 (PSI20) is widely used internationally, no validated Arabic version is available for Arabic-speaking nursing students. Design: A two-phase methodological and cross-sectional validation study. Settings: Faculty of Nursing, Mansoura University, Egypt, during the 2024-2025 academic year. Participants: A total of 633 undergraduate nursing students participated in Phase Two. Methods: Phase One followed Beaton's cross-cultural adaptation framework. Phase Two involved psychometric evaluation using confirmatory factor analysis (CFA), assessment of convergent and discriminant validity, internal consistency, test-retest reliability, receiver operating characteristic (ROC) curve analysis and multi-group measurement invariance across gender, GPA, family structure, living arrangements, sleep regularity and ChatGPT use. Results: The Arabic PSI-20 demonstrated excellent internal consistency (Cronbach's alpha = 0.956) and strong construct validity. CFA supported the original three-factor structure (CFI = 0.979, RMSEA = 0.055). Measurement invariance was confirmed across most subgroups, with partial invariance across ChatGPT-use categories. PSA was positively associated with self-directed learning and negatively associated with academic stress. ROC analysis identified an optimal cut-off score of >= 57 for detecting low PSA (AUC = 0.799). Conclusions: The Arabic PSI-20 is a valid and reliable instrument for evaluating PSA.
Keywords:
Problem-solving ability
Nursing students
ChatGPT
Psychometric validation
Measurement invariance
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