Suppr超能文献

测量催眠易感性:自我报告深度量表及斯坦福长式量表常模数据的情况

Measuring hypnotizability: the case for self-report depth scales and normative data for the long Stanford scale.

作者信息

Wagstaff Graham F, Cole Jon C, Brunas-Wagstaff Joana

机构信息

University of Liverpool, Liverpool, UK.

出版信息

Int J Clin Exp Hypn. 2008 Apr;56(2):119-42. doi: 10.1080/00207140701849452.

Abstract

Conventional suggestion-based tests of hypnotizability have been criticized because they confound hypnotic and nonhypnotic suggestibility. One way around this might be to measure hypnotizability in terms of differences in suggestibility before and after hypnotic induction. However, analysis of data from a 1966 classic study by Hilgard and Tart confirms that difference scores are subject to statistical and methodological problems. Simple verbal hypnotic depth scales are presented as a useful alternative. They correlate well with conventional suggestion-based measures and enable the presence of hypnosis to be indexed independently of formal hypnotic induction procedures. Criticisms of depth scales are addressed, and normative data for the Long Stanford Scale of hypnotic depth are presented, along with data lending empirical support for the construct validity of depth reports.

摘要

传统的基于暗示的催眠易感性测试受到了批评,因为它们混淆了催眠暗示性和非催眠暗示性。解决这一问题的一种方法可能是根据催眠诱导前后暗示性的差异来衡量催眠易感性。然而,对希尔加德和塔特1966年一项经典研究数据的分析证实,差异分数存在统计和方法上的问题。简单的言语催眠深度量表被认为是一种有用的替代方法。它们与传统的基于暗示的测量方法相关性良好,并且能够独立于正式的催眠诱导程序来对催眠状态进行索引。文中对深度量表的批评进行了回应,并给出了斯坦福催眠深度长量表的常模数据,以及为深度报告的结构效度提供实证支持的数据。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验