Implicit Associations of Nonsuicidal Self-Injury with Relief in Posttraumatic Stress and Depressive Disorders*. Issue 2 (3rd April 2022)

• Record Type: Journal Article
• Authors: Forbes, Courtney N.; Tull, Matthew T.; Chapman, Alexander L.; Dixon-Gordon, Katherine L.; Gratz, Kim L.
• Is Part Of: Archives of suicide research. Volume 26:Issue 2(2022)
• Page Start: 565
• Page End: 580
• Publication Date: 2022-04-03
• Subjects: Depression -- implicit association test -- nonsuicidal self-injury -- posttraumatic stress disorder -- self-injurious behavior; Suicide -- Periodicals; 179.7
• DOI: 10.1080/13811118.2020.1811182
• Languages: English
• ISSNs: 1381-1118

Abstract

Abstract: Objective: Although once considered a defining feature of borderline personality disorder, research has found high rates of NSSI among individuals with other psychiatric disorders, particularly posttraumatic stress disorder (PTSD) and depressive disorders. A recent study from our research team found that lifetime PTSD and depressive disorders were associated with unique self-reported NSSI motives. Given well-established limitations of assessing motives via self-report measures, the present study sought to extend this line of research by using a novel laboratory measure of the implicit NSSI-relief association to examine NSSI emotional relief motives. Method: A subset of participants from our previous study ( N = 109) completed diagnostic interviews and the laboratory-based DSH-Relief Implicit Association Test (IAT). Results: Findings indicated that individuals with lifetime PTSD evidenced stronger NSSI-relief associations than those without PTSD. Further, this main effect was qualified by a PTSD by depressive disorder interaction, such that stronger NSSI-relief associations were found among individuals with lifetime PTSD but no lifetime depressive disorder than among individuals without a history of either PTSD or a depressive disorder. Conclusions: Results highlight the importance of investigating NSSI motives associated with different symptom profiles using a multi-method approach.