Reinforcement Sensitivity Theory (RST) posits that individual differences in reward and punishment processing predict differences in cognition, behavior, and psychopathology. We performed a quantitative review of the relationships between reinforcement sensitivity, depression and anxiety, in two separate sets of analyses. First, we reviewed 204 studies that reported either correlations between reinforcement sensitivity and self-reported symptom severity or differences in reinforcement sensitivity between diagnosed and healthy participants, yielding 483 effect sizes. Both depression (Hedges' g = .99) and anxiety (g = 1.21) were found to be high on punishment sensitivity. Reward sensitivity negatively predicted only depressive disorders (g =-.21). More severe clinical states (e.g., acute vs remission) predicted larger effect sizes for depression but not anxiety. Next, we reviewed an additional 39 studies that reported correlations between reinforcement sensitivity and both depression and anxiety, yielding 156 effect sizes. We then performed meta-analytic structural equation modeling to simultaneously estimate all covariances and control for comorbidity. Again we found punishment sensitivity to predict depression (β = .37) and anxiety (β = .35), with reward sensitivity only predicting depression (β =-.07). The transdiagnostic role of punishment sensitivity and the discriminatory role of reward sensitivity support a hierarchical approach to RST and psychopathology. Highlights: Sensitivity to punishment positively predicts both depression and anxiety. Sensitivity to reward discriminates between them, negatively predicting depression. This pattern was observed even when directly controlling for comorbidity. Depression's effect sizes are uniquely sensitive to clinical state. Depression's effect sizes are also moderated by method of clinical assessment.

The self‐esteem Questionnaire‐based Implicit Association Test (SE‐qIAT) provides an indirect assessment of general self‐worth that is based on the items of the well‐validated Rosenberg Self‐Esteem Scale (RSES), and the structure of this variant of the IAT enables a clearer interpretation, compared with the conventional self‐esteem IAT. Study 1 (N = 224) provided support for the internal consistency, test–retest reliability, and implicit–explicit convergent validity of the SE‐qIAT. In Study 2 (N = 305), the correlation of the SE‐qIAT with the explicit RSES was replicated, and it was larger than the correlations of the SE‐qIAT with other self‐reports. As to criterion validity, the SE‐qIAT moderated the effect of a mild social threat (being excluded in the Cyberball game) on participants’ performance in a subsequent anagram task, and this effect was incremental to the explicit self‐esteem assessment. In Study 3 (N = 334), the SE‐qIAT correlated positively with the self‐esteem IAT and negatively with a measure of depression. The two implicit tasks correlated uniquely with each other, above and beyond the variance they each shared with the explicit RSES. Taken together, these findings provide initial support for the reliability and validity of the SE‐qIAT.

Reinforcement Sensitivity Theory (RST) posits that individual differences in reward and punishment processing predict differences in cognition, behavior, and psychopathology. We performed a quantitative review of the relationships between reinforcement sensitivity, depression and anxiety, in two separate sets of analyses. First, we reviewed 204 studies that reported either correlations between reinforcement sensitivity and self-reported symptom severity or differences in reinforcement sensitivity between diagnosed and healthy participants, yielding 483 effect sizes. Both depression (Hedges’ g = .99) and anxiety (g = 1.21) were found to be high on punishment sensitivity. Reward sensitivity negatively predicted only depressive disorders (g = -.21). More severe clinical states (e.g., acute vs remission) predicted larger effect sizes for depression but not anxiety. Next, we reviewed an additional 39 studies that reported correlations between reinforcement sensitivity and both depression and anxiety, yielding 156 effect sizes. We then performed meta-analytic structural equation modeling to simultaneously estimate all covariances and control for comorbidity. Again we found punishment sensitivity to predict depression (β = .37) and anxiety (β = .35), with reward sensitivity only predicting depression (β = -.07). The transdiagnostic role of punishment sensitivity and the discriminatory role of reward sensitivity support a hierarchical approach to RST and psychopathology. Highlights: Sensitivity to punishment positively predicts both depression and anxiety. Sensitivity to reward discriminates between them, negatively predicting depression. This pattern was ob-served even when directly controlling for comorbidity. Depression’s effect sizes are uniquely sensitive to clinical state. Depression’s effect sizes are also moderated by method of clinical assessment.Data, analysis code, supplementary material: https://osf.io/n6gv4/