Interpretive bias in anxiety: the search for an elusive cognitive effect

[Truncated abstract] Cognitive models of anxiety vulnerability such as Beck's (1976) and Bower's (1981; 1983) models, predict that trait anxiety is associated with cognitive biases, such as an attentional bias of preferentially encoding negative information; a memory bias of preferentially retrieving negative information; and an interpretive bias of preferentially imposing negative interpretations upon ambiguous information. These models also predict that these cognitive biases operate automatically. Automatic processing is generally defined as cognitive processes with three characteristics, being: rapid, capacity-independent, and unconscious. A number of previous studies have demonstrated empirical support for the automaticity of the hypothesised anxiety-linked attentional bias. However, it has not been widely investigated as to whether anxiety-linked interpretive bias operates automatically or strategically. The present program of research was undertaken to address this general lack of attention given to the automaticity of the hypothesised anxiety-linked interpretive bias. The priming paradigm employed by Richards and French's (1992) study was used in Phase One of the present research to address this issue. It is due to the fact that this study is so far the only published study that found empirical support for the hypothesised anxiety-linked interpretive bias on ambiguous lexical materials that is not amenable to alternative explanations. This experimental paradigm is also amenable to experimental manipulations in examining the automaticity of such bias. The first three priming tasks in Phase One of the present research were conducted to examine whether such bias operates rapidly, and whether it is capacity-independent and unconscious. However, only one of the three priming tasks has demonstrated the evidence that both High Trait Anxious and Low Trait Anxious participants processed the semantic content of the ambiguous materials, rendering these tasks