Category: Suicide and Self-Injury
Given the increased risk posed by adolescent suicide attempts for both recurrent attempts and for suicide (U.S. Department of Health and Human Services, 2012), it is of great importance to identify risk and protective factors in the immediate post-attempt time period (Cash & Bridge, 2009). Among the factors that have garnered increased interest in recent years is social support, in particular connectedness with peers. In the only longitudinal study to measure change in peer connectedness among suicidal adolescents across more than two time points, Czyz, Liu, and King (2012) found that adolescents who reported greater increases in connections with peers post-psychiatric hospitalization were roughly 50% less likely to reattempt suicide across a 1-year follow-up. The present study built upon Czyz et al.’s findings. Specifically, 85 adolescents (ages 13-18) who were hospitalized following a medically serious suicide attempt were assessed shortly after the attempt and at 6-month intervals across two years. The associations between trajectories of peer attachment and suicidal ideation were examined, as was the possible role of depression as a moderator of those associations. Specifically, it was expected that increasing levels of perceived peer attachment across the 2 year follow-up would be associated with reduced suicidal ideation across that time span, and that the association between the two trajectories would be stronger for those with lower depression at baseline.
Peer attachment was assessed at each of the five time points with the Inventory of Parent and Peer Attachment (IPPA; Armsden & Greenberg, 1987). Suicidal ideation was assessed at each time point with items from the Diagnostic Interview Schedule for Children, Version 2.3 (DISC 2.3C; Fisher et al., 1992), and DISC 2.3C was also used to assess depressive symptoms, scored as a count of the number of DSM-III-R symptoms endorsed. A history of previous suicide attempts was scored as 0=none vs. 1=one or more attempts. Multi-level growth models were analyzed using HLM (Raudenbush et al., 2004).
Erin Reese– Graduate Student, The Catholic University of America
Barry Wagner– Professor of Psychology, The Catholic University of America, Washington, District Of Columbia
Marcie Goeke-Morey– Associate Professor, The Catholic University of America, Washington, District Of Columbia
Professor of Psychology
The Catholic University of America
Washington, District Of Columbia