Applying the questionnaire-based Implicit Association Test to measure automatic negative thinking

In a cognitive-behavioural theoretical framework, automatic negative thoughts are considered among the main determinants of depression and other disorders. Negative thinking is usually assessed through self-report scales, although several studies demonstrated their proneness to well-known confounds like introspective limits and social desirability. In the last decades several measures have been developed, within an implicit social cognition framework, that allow to moderate these confounds. Among them, the questionnaire-based Implicit Association Test (qIAT) is a latency-based paradigm well-suited to measure automatic propositional thinking. In this vein, two versions of the qIAT were designed to measure negative thinking, and successively tested in two different studies (with 118 and 71 participants, respectively). Internal consistency and concurrent validity of the new qIATs were assessed, along with their vulnerability to faking. Results showed adequate, even though not optimal, internal consistency for both qIATs. Across the two studies small/moderate positive correlations of the qIAT with two traditional self-report measures of depression were found, along with small/moderate negative correlations with satisfaction with life, self-esteem, and positive affects scales, supporting the concurrent validity of the new measures. Finally, both studies showed that the qIAT is considerably less vulnerable to faking compared to a traditional self-report scale of depression.