Parsing Trait and State Effects of Depression Severity on Neurocognition: Evidence From a 26-Year Longitudinal Study
journal contributionposted on 26.11.2013 by Casey Sarapas, Stewart A. Shankman, Martin Harrow, Joseph F. Goldberg
Any type of content formally published in an academic journal, usually following a peer-review process.
Cognitive dysfunction in mood disorders falls along a continuum, such that more severe current depression is associated with greater cognitive impairment. It is not clear whether this association reflects transient state effects of current symptoms on cognitive performance, or persistent, trait-like differences in cognition that are related to overall disorder severity. We addressed this question in 42 unipolar and 47 bipolar participants drawn from a 26-year longitudinal study of psychopathology, using measures of attention/psychomotor processing speed, cognitive flexibility, verbal fluency, and verbal memory. We assessed (a) the extent to which current symptom severity and past average disorder severity predicted unique variance in cognitive performance; (b) whether cognitive performance covaried with within-individual changes in symptom severity; and (c) the stability of neurocognitive measures over six years. We also tested for differences among unipolar and bipolar groups and published norms. Past average depression severity predicted performance on attention/psychomotor processing speed in both groups, and in cognitive flexibility among unipolar participants, even after controlling for current symptom severity, which did not independently predict cognition. Within-participant state changes in depressive symptoms did not predict change in any cognitive domain. All domains were stable over the course of six years. Both groups showed generalized impairment relative to published norms, and bipolar participants performed more poorly than unipolar participants on attention/psychomotor processing speed. The results suggest a stable relationship between mood disorder severity and cognitive deficits.