基于大语言模型的跨文化个性测量表(CPAI-2)人际取向结构探索:一项初步研究OA

Objective:This study aimed to explore the structural model of the Interpersonal Relatedness factor in the Cross-Cultural Personality Assessment Inventory(CPAI-2). Methods:A sample of 100 Chinese adults was recruited through an online survey.Participants completed the Interpersonal Relatedness scale of the CPAI-2 and an open-ended language task.The study examined whether the structural features of the Interpersonal Relatedness factor could be reflected in participants'natural language expressions.Responses from the open-ended task were coded and analyzed using the large language model ChatGPT-5 for model construction.Cosine similarity analysis was conducted to evaluate the consistency and correspondence of the derived structures. Results:(1)The results of two independent coding rounds demonstrated a high degree of similarity.(2)The model constructed by ChatGPT showed both convergence and divergence relative to the original CPAI-2 model.Specifically,the dimensions of Harmony and Social Sensitivity were not supported in the present findings.This may be related to differences in textual meaning and levels of coding and warrants further investigation. Conclusion:By integrating an open-ended language task with large language model coding,this study extends the validation approach of the CPAI-2,provides empirical support for methodological diversification in personality assessment,and contributes to the continued application and development of the CPAI-2.