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濒死体验内容量表(NDE-C):编制与心理测量学验证。

The Near-Death Experience Content (NDE-C) scale: Development and psychometric validation.

机构信息

Coma Science Group, GIGA-Consciousness, University of Liège, Avenue de l'hôpital, 11, 4000 Liège, Belgium; Centre du Cerveau(2), University Hospital of Liège, Avenue de l'hôpital, 11, 4000 Liège, Belgium.

Psychology and Neuroscience of Cognition, University of Liège, Bât. B32 Quartier Agora, Place des Orateurs 2, 4000 Liège 1, Belgium.

出版信息

Conscious Cogn. 2020 Nov;86:103049. doi: 10.1016/j.concog.2020.103049. Epub 2020 Nov 20.

DOI:10.1016/j.concog.2020.103049
PMID:33227590
Abstract

As interest grows in near-death experiences (NDEs), it is increasingly important to accurately identify them to facilitate empirical research and reproducibility among assessors. We aimed (1) to reassess the psychometric properties of the NDE scale developed by Greyson (1983) and (2) to validate the Near-Death Experience Content (NDE-C) scale that quantifies NDEs in a more complete way. Internal consistency, construct and concurrent validity analyses were performed on the NDE scale. Based on those results and the most recent empirical evidence, we then developed a new 20-item scale. Internal consistency, explanatory and confirmatory factor, concurrent and discriminant validity analyses were conducted. Results revealed (1) a series of weaknesses in the NDE scale, (2) a 5-factor structure covering relevant dimensions and the very good psychometric properties of the NDE-C scale, including very good internal consistency (Cronbach α = 0.85) and concurrent validity (correlations above 0.76). This new reliable scale should facilitate future research.

摘要

随着对濒死体验(Near-death experience,NDE)的兴趣日益增加,准确识别它们对于促进评估者之间的实证研究和可重复性变得越来越重要。我们旨在(1)重新评估 Greyson(1983 年)开发的 NDE 量表的心理测量特性,(2)验证更全面量化 NDE 的近死体验内容量表(Near-Death Experience Content,NDE-C)。我们对 NDE 量表进行了内部一致性、结构和同时效度分析。基于这些结果和最新的实证证据,我们随后开发了一个新的 20 项量表。我们进行了内部一致性、解释和验证性因子、同时和判别效度分析。结果表明(1)NDE 量表存在一系列弱点,(2)涵盖相关维度的 5 因素结构和 NDE-C 量表非常好的心理测量特性,包括非常好的内部一致性(Cronbach α=0.85)和同时效度(相关性高于 0.76)。这个新的可靠量表应有助于未来的研究。

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