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利用维度凸显解决计划行为理论中的“期望-价值混乱”。

Resolving the theory of planned behaviour's 'expectancy-value muddle' using dimensional salience.

机构信息

School of Psychology and Psychiatry, Caulfield Campus, Monash University, P.O. Box 197, Caulfield East, Victoria 3145, Australia.

出版信息

Psychol Health. 2012;27(5):588-602. doi: 10.1080/08870446.2011.611244. Epub 2011 Aug 31.

Abstract

The theory of planned behaviour is one of the most widely used models of decision-making in the health literature. Unfortunately, the primary method for assessing the theory's belief-based expectancy-value models results in statistically uninterpretable findings, giving rise to what has become known as the 'expectancy-value muddle'. Moreover, existing methods for resolving this muddle are associated with various conceptual or practical limitations. This study addresses these issues by identifying and evaluating a parsimonious method for resolving the expectancy-value muddle. Three hundred and nine Australian residents aged 18-24 years rated the expectancy and value of 18 beliefs about posthumous organ donation. Participants also nominated their five most salient beliefs using a dimensional salience approach. Salient beliefs were perceived as being more likely to eventuate than non-salient beliefs, indicating that salient beliefs could be used to signify the expectancy component. The expectancy-value term was therefore represented by summing the value ratings of salient beliefs, an approach that predicted attitude (adjusted R2 = 0.21) and intention (adjusted R2 = 0.21). These findings suggest that the dimensional salience approach is a useful method for overcoming the expectancy-value muddle in applied research settings.

摘要

计划行为理论是健康文献中决策最广泛使用的模型之一。不幸的是,评估该理论基于信念的期望价值模型的主要方法导致了统计学上无法解释的结果,从而产生了所谓的“期望价值混乱”。此外,现有的解决这种混乱的方法存在各种概念或实际限制。本研究通过确定和评估一种简洁的方法来解决期望价值混乱问题,从而解决了这些问题。309 名年龄在 18-24 岁的澳大利亚居民对 18 种关于死后器官捐赠的信念的期望和价值进行了评分。参与者还使用维度显著性方法提名了他们的五个最突出的信念。显著信念被认为比非显著信念更有可能发生,这表明显著信念可以用来表示期望成分。因此,期望价值项是通过将显著信念的价值评分相加来表示的,这种方法可以预测态度(调整 R2=0.21)和意图(调整 R2=0.21)。这些发现表明,维度显著性方法是克服应用研究环境中期望价值混乱的一种有用方法。

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