心理学
情感(语言学)
社会心理学
结构效度
内隐联想测验
含蓄的态度
差异(会计)
考试(生物学)
内部一致性
可靠性(半导体)
认知心理学
测试有效性
构造(python库)
一致性(知识库)
发展心理学
心理测量学
沟通
会计
业务
古生物学
功率(物理)
物理
量子力学
程序设计语言
生物
计算机科学
数学
几何学
作者
Markus Quirin,Miguel Kazén,Julius Kühl
摘要
This article introduces an instrument for the indirect assessment of positive and negative affect, the Implicit Positive and Negative Affect Test (IPANAT). This test draws on participant ratings of the extent to which artificial words subjectively convey various emotions. Factor analyses of these ratings yielded two independent factors that can be interpreted as implicit positive and negative affect. The corresponding scales show adequate internal consistency, test-retest reliability, stability (Study 1), and construct validity (Study 2). Studies 3 and 4 demonstrate that the IPANAT also measures state variance. Finally, Study 5 provides criterion-based validity by demonstrating that correlations between implicit affect and explicit affect are higher under conditions of spontaneous responding than under conditions of reflective responding to explicit affect scales. The present findings suggest that the IPANAT is a reliable and valid measure with a straightforward application procedure.
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