A latent profile analysis of implicit and explicit cognitions associated with depression

Dual-process cognitive profiles associated with depression were identified in an undergraduate sample (N = 306) and dysphoric sub-sample (n = 57). Two Latent Profile Analyses (LPAs) were conducted on four implicit and four explicit cognitions associated with depression (self-esteem, negative memory, positive memory and dysfunctional beliefs). The first LPA, performed on the total sample, produced a three-profile solution reflecting quantitative shifts from generally negative, through intermediate, to generally positive biases on both implicit and explicit indicators. Patterns of biases across the profiles were associated with incremental decreases in current depressive symptoms, and logistic regression revealed that profile membership significantly predicted depression status 3 months later. Sequential logistic regression indicated that implicit self-esteem was the strongest predictor of subsequent dysphoria. The second LPA, focusing on a subgroup of dysphoric participants, identified two qualitatively distinct profiles that may represent cognitive subtypes of depression: (1) a schematic profile with multiple negative biases and (2) a profile dominated by implicit negative memory. These results are consistent with the dual-process premise that implicit and explicit cognitive processes are involved in depression and suggest that treatment efficacy may be improved by incorporating strategies that address implicit cognitive biases.