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一种针对自恋人格量表的探索性结构方程建模方法:对NPI - 13简版的支持以及基于与其他变量关系的证据

An Exploratory Structural Equation Modeling Approach for the Narcissistic Personality Inventory: Support for the NPI-13 Brief Version and Evidence Based on Relations to Other Variables.

作者信息

Bottaro Rossella, Craparo Giuseppe, Faraci Palmira

机构信息

Department of Human and Social Sciences - University of Enna "Kore".

出版信息

Clin Neuropsychiatry. 2025 Apr;22(2):125-140. doi: 10.36131/cnfioritieditore20250203.

Abstract

OBJECTIVE

The Narcissistic Personality Inventory (NPI) is the most commonly used psychometric instrument for assessing narcissistic traits in the general population. Despite its widespread adoption, various factorial structures have been proposed. The present study aimed to provide new evidence for the NPI factorial solution using the not-yet-explored Exploratory Structural Equation Modeling (ESEM) approach and to improve understanding of its relationship with other variables.:We administered the NPI along with measures of anxiety, depression, stress, self-esteem, and loneliness to 583 participants (50.8% male, M age = 30.96, SD = 12.12) in a survey online. We compared confirmatory factor analyses and ESEMs for both the long and brief versions.

RESULTS

The NPI-13 ESEM model was the optimal fitting model (ꭓ2=72.060, df = 42, CFI = 0.979, TLI = 0.961, RMSEA = .035 [.021-.049]) also for its bifactorial solution. Moreover, our findings supported the evidence based on relations to other variables for the NPI-13.

CONCLUSIONS

In conclusion, our results argued the use of a multidimensional brief version of the NPI and supported the ESEM's advantages for explaining the factorial structure of complex psychological constructs.

摘要

目的

自恋人格问卷(NPI)是评估普通人群自恋特质最常用的心理测量工具。尽管它被广泛采用,但人们提出了各种因子结构。本研究旨在使用尚未探索的探索性结构方程模型(ESEM)方法为NPI因子解提供新证据,并增进对其与其他变量关系的理解。我们在一项在线调查中,对583名参与者(50.8%为男性,年龄均值=30.96,标准差=12.12)施测了NPI以及焦虑、抑郁、压力、自尊和孤独感量表。我们比较了长版和简版的验证性因子分析和ESEM。

结果

NPI-13的ESEM模型也是其双因子解的最佳拟合模型(卡方=72.060,自由度=42,比较拟合指数=0.979,塔克-刘易斯指数=0.961,近似误差均方根=0.035[0.021-0.049])。此外,我们的研究结果支持了基于NPI-13与其他变量关系的证据。

结论

总之,我们的结果支持使用NPI的多维简版,并支持ESEM在解释复杂心理结构因子结构方面的优势。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/758b/12090371/14da9ce257bf/cn-22-125-f01.jpg

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