Cognitive Inhibition, Rumination, and Insomnia in Depressed Suicide-Prone Individuals

The overall goal of this investigation was to broaden our understanding of suicidality among those with depression. Specifically, I sought to clarify the relationship between rumination, cognitive inhibition, insomnia, and suicidal ideation. Prior research has shown that suicide is highly correlated with rumination, cognitive inhibition deficits, and insomnia. Yet, although various studies have examined these factors individually, little information exists regarding possible associations between these constructs within suicidal individuals. Given that these constructs are related to both depressive and suicidal phenomenon, it is important to consider how these factors may interrelate in order to gain a better understanding of the potential mechanisms which lead to suicidality. The aims of the present study were to: (1) examine whether cognitive inhibition deficits exist among those with suicidal ideation; (2) test the hypothesis that rumination mediates the relationship between cognitive inhibition deficits and suicidality; (3) examine whether insomnia serves as a moderating variable in the relationship between cognitive inhibition and suicidality; (4) expand previous research by directly comparing three suicidal mental states (i.e., suicidal ideation, suicidal attempts, and the combination of both); and (5) examine the variables of interest in a more precise sample of suicidal individuals than currently present in the literature. The results indicated cognitive inhibition deficits and an affective bias for negative stimuli among both of the groups with current suicidal ideation. Furthermore, it was hypothesized that the relationship between cognitive inhibition and suicidal ideation would be mediated by depressive rumination, and moderated by insomnia severity. Two moderated mediation path models were evaluated using Structural Equation Modeling. Contrary to expectations, the results did not indicate that there was a good fit between either model and the data. However, individual path analysis revealed that ...