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.

强化敏感性理论（RST）认为，奖励和惩罚过程中的个体差异会预测认知，行为和心理病理学方面的差异。我们在两组独立的分析中对增强敏感度，抑郁和焦虑之间的关系进行了定量回顾。首先，我们回顾了204项研究，这些研究报告了增强敏感性和自我报告的症状严重程度之间的相关性，或者诊断和健康参与者之间增强敏感性的差异，产生了483个效应值。抑郁（Hedges'g =  0.99）和焦虑（g =  1.21）均对惩罚敏感度较高。奖励敏感度只能预测抑郁症（g = -.21）。更严重的临床状态（例如，急性与缓解）预示着抑郁症会产生更大的影响，但焦虑却不会。接下来，我们回顾了另外39项研究，这些研究报告了增强敏感性与抑郁和焦虑之间的相关性，产生了156种效果大小。然后，我们进行了元分析结构方程建模，以同时估计所有协方差并控制合并症。同样，我们发现惩罚敏感性可以预测抑郁（β=  .37）和焦虑（β=  .35），而奖励敏感性只能预测抑郁（β=  -.07）。惩罚敏感性的转诊作用和奖赏敏感性的区别作用支持对RST和心理病理学的分层方法。