NRSA Fellowship Dan Evans: Emotion regulation and self-regulation in older adults

Emotion regulation among older adults appears to be a relatively preserved capacity that is vital for wellbeing and successful aging. However, the limits of this ability and the circumstances under which older adults might be less capable of regulating their emotions are unclear. Furthermore, current theories that seek to explain how older adults regulate their emotions, such as increased allocation of resources for emotion regulation or improved efficiency of emotion regulation, have not been compared to each other. Therefore, the aims of the proposed project are to 1) test the limits of older adults’ emotion regulation capacity and 2) gain a better understanding of how older adults use their more limited resources to regulate their emotions. These aims are part of a long-term goal of producing a scientific knowledge base for improving the emotional health and wellbeing of older adults. The proposed project will use a paradigm from the strength model of self-regulation that posits a limited, fatigable, and common pool of self-regulatory resources that are drawn on by any act of selfregulation— controlling one’s thoughts, emotions, and behaviors—such that performance on a subsequent but unrelated act of self-regulation tends to be impaired. An equal number of older and younger participants will be randomly assigned to one of four experimental groups involving an initial activity that is high or low in selfregulatory demand followed by a dependent task of emotion regulation or attention regulation. Comparing the performance of older and younger adults on the dependent emotion regulation task will provide results relevant to aim 1. The proposed project will also include resting heart rate variability (HRV), a physiological measure that may provide an index of self-regulatory capacity. Examining the relationships between performance on the dependent self-regulation tasks and HRV will provide a measure of the extent to which participants are allocating self-regulatory resources for the different tasks, results relevant to aim 2.