{Reference Type}: Journal Article
{Title}: The Ambiguous Cue Task: Measurement reliability of an experimental paradigm for the assessment of interpretation bias and associations with mental health.
{Author}: Armbruster-Genç DJN;Rammensee RA;Jungmann SM;Drake P;Wessa M;Basten U;
{Journal}: Behav Res Methods
{Volume}: 0
{Issue}: 0
{Year}: 2024 Jul 12
{Factor}: 5.953
{DOI}: 10.3758/s13428-024-02451-y
{Abstract}: Interpretation biases in the processing of ambiguous affective information are assumed to play an important role in the onset and maintenance of emotional disorders. Reports of low reliability for experimental measures of cognitive biases have called into question previous findings on the association of these measures with markers of mental health and demonstrated the need to systematically evaluate measurement reliability for measures of cognitive biases. We evaluated reliability and correlations with self-report measures of mental health for interpretation bias scores derived from the Ambiguous Cue Task (ACT), an experimental paradigm for the assessment of approach-avoidance behavior towards ambiguous affective stimuli. For a non-clinical sample, the measurement of an interpretation bias with the ACT showed high internal consistency (rSB = .91 - .96, N = 354) and acceptable 2-week test-retest correlations (rPearson = .61 - .65, n = 109). Correlations between the ACT interpretation bias scores and mental health-related self-report measures of personality and well-being were generally small (r ≤ |.11|) and statistically not significant when correcting for multiple comparisons. These findings suggest that in non-clinical populations, individual differences in the interpretation of ambiguous affective information as assessed with the ACT do not show a clear association with self-report markers of mental health. However, in allowing for a highly reliable measurement of interpretation bias, the ACT provides a valuable tool for studies considering potentially small effect sizes in non-clinical populations by studying bigger samples as well as for work on clinical populations, for which potentially greater effects can be expected.