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DOI: 10.1007/s10608-017-9853-x
¤ OpenAccess: Green
This work has “Green” OA status. This means it may cost money to access on the publisher landing page, but there is a free copy in an OA repository.

Out-of-the-Blue: Depressive Symptoms are Associated with Deficits in Processing Inferential Expectancy-Violations Using a Novel Cognitive Rigidity Task

Paul Liknaitzky,Luke D. Smillie,Nicholas Allen

Psychology
Cognition
Cognitive psychology
2017
Rigid cognition is frequently cited as a plausible maintenance or risk factor for depression. However, most performance-based measures of cognitive rigidity associated with depression offer poor ecological validity, produce mixed findings, and afford little in the way of therapeutic application. In order to establish a more useful and relevant performance-based measure of cognitive rigidity in depression, we developed a novel task that probes a rigidity process using stimuli highly relevant to the level of construal, the thematic content, and the rhetorical mode of depressotypic thinking. The task consists of a set of narrative vignettes that contain an expectancy-violation that is incompatible with an initially-established interpretation. As hypothesized, depressive symptoms were associated with reduced ability to update interpretations. This finding was independent of the valence of the expectancy-violation (i.e., was not merely a negativity bias), and was significant after controlling for basic set-shifting ability, intelligence measures, working memory, and other potential confounds. The novel Contingent Inference Task is a promising approach that may probe a more ecologically and etiologically relevant form of cognitive rigidity in depression than other related performance-based rigidity tasks. This rigidity process may underlie the persistence of biased beliefs in depression, and represent a new therapeutic target.
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    Out-of-the-Blue: Depressive Symptoms are Associated with Deficits in Processing Inferential Expectancy-Violations Using a Novel Cognitive Rigidity Task” is a paper by Paul Liknaitzky Luke D. Smillie Nicholas Allen published in 2017. It has an Open Access status of “green”. You can read and download a PDF Full Text of this paper here.