β =.381 (.067) ** Introduction Method Behavioral-Emotional Adjustment and Objective Sleep during Adolescence: Costs of Prosocial Behavior Adolescence is characterized by increased emotionality and impulsivity, as well as opportunities for identity exploration (Birditt & Fingerman, 2003; Spear, 2000). Adolescence also marks a period of profound changes in sleep-wake patterns (Carskadon, 2011; Colrain & Baker, 2011). While the effect of sleep on behavioral- emotional adjustment is well-documented within the literature (e.g., Kahn-Greene et al., 2006), fewer studies have examined the impact of behavioral-emotional adjustment on sleep among adolescents. Moreover, the majority of past studies have been based on concurrent associations between sleep and adolescent adjustment and thus, are unable to tease apart temporal precedence between these two constructs (e.g., Liu & Zhou, 2002; O’Brien & Mindell, 2005). Additionally, less is known about the link between sleep and positive aspects of adolescent adjustment, including prosocial behaviors. To address these gaps in the literature, the present study examined the effect of sleep on behavioral-emotional adjustment, as well as the inverse effect of behavioral-emotional adjustment on sleep. Summary & Discussion Results  More restful sleep predicted less internalizing problems over time. Sleep facilitates the functional connectivity between medial prefrontal cortex and the amygdala (e.g., Yoo et al., 2007).  More conduct problems predicted less restful sleep over time. Conduct problems may increase physiological arousal, which impedes optimal sleep (e.g., Espie, 2002).  Higher pro-social behavior was consistently strongly related to negative sleep over time, (i.e., later bedtimes, shorter sleep duration, and less restful sleep). Pro-social behaviors, which included items such as volunteering and helping others, may come at the expense of poorer sleep, perhaps due to the time commitment that may accompany these behaviors. Future research should replicate this association and assess potential mechanisms (e.g., time management) that explain this finding. Participants N = 46 adolescents (50% female) Age: years (Mean = 15.75, SD = 0.98) Measures Demographics Age, Sex, Race Sleep Activity Monitor: Misfit Shine (Misfit, Inc.) i.Bedtime (week, weekend) ii.Sleep hours (week, weekend) iii.Restful sleep (week, weekend) Behavioral-Emotional Adjustment (Strengths and Difficulties Questionnaire; Goodman, 1997) i.Conduct Problems subscale (5 items): E.g., “I fight a lot. I can make other people do what I want.” ii.Internalizing Problems subscale (10 items): E.g., “I am often unhappy, down- hearted or tearful.” iii.Prosocial subscale (5 items): E.g., “I often volunteer to help others (parents, teachers, children).” Analyses  Hierarchical Multiple Regression  Time 1 (Baseline); Time 2 (3-weeks later, post-intervention) Step 1: Scores on Dependent Variable at Time 1 Step 2: Covariates (i.e., age, sex, and race) Step 3: Predictors RQ. 1: Does Sleep at Time 1 predict Behavioral-Emotional Adjustment at Time 2 (controlling for Time 1 scores on Behavioral-Emotional Adjustment)? RQ. 2 Does Behavioral-Emotional Adjustment at Time 1 predict Sleep at Time 2 (controlling for Time 1 scores on Sleep)? Bedtime (week) Bedtime (weekend) Sleep Hours (week) Sleep Hours (weekend) Restful Sleep (week) Restful Sleep (weekend) Conduct Problems Internalizing Problems Pro-social Behaviors Restful Sleep (week) Internalizing Problems Royette Tavernier 1, Shalin Shah 1, Sarah Dorfman 2, Abigal Durgan 1, Sahar Bhai 1, Royette Tavernier 1,Pooja Kanthawar 1, & Emma K Adam 1 1 Northwestern University, Evanston, IL, U.S.A 2 University of Illinois at Urbana-Champaign, Champaign, IL, U.S.A β = (.066) ** β = (.114) + β = (.045) * β = (.056) * β = (.359) * β = (.151) * Note. *p <.05; **p <.01; +p <.10