UC Irvine

Positive and negative affect has been associated with numerous health factors. However, what is commonly investigated are the mean levels of affect. While means reveal important information, how affect varies over time may provide further information about how the experience of affect relates to important outcomes. This change from moment to moment, day to day, or week to week has been referred to as affect variability and is often operationally defined as the standard deviation of affect over time. While useful, this methodology is incomplete as it loses important information about the temporal aspect of affect variability (i.e., information about patterns of affect responses over time are lost). Nevertheless, greater affect variability has been associated with several psychological health and health-relevant outcomes such as low self-esteem and higher depressive symptoms. What remains unclear is how affect variability patterns and interactions with mean levels relate to such variables. What is also unknown is whether affect variability is associated with markers of physical health. Therefore, the goals of this dissertation are to 1. assess whether affect variability is associated with markers of physical health, 2. examine a new method for assessing affect variability that may overcome the downsides of standard deviation (i.e., loss of information about patterns), and 3. use this new method to better understand how affect variability patterns relate to mental and physical health and health-relevant variables.