Misol Kwon1, Young S Seo2, Amanda B Nickerson3, Suzanne S Dickerson4, Eunhee Park5, Jennifer A Livingston6. 1. Gamma Kappa, Doctoral Student, School of Nursing, University at Buffalo, The State University of New York, Buffalo, NY, USA. 2. Database Manager, School of Nursing, University at Buffalo, The State University of New York, Buffalo, NY, USA. 3. Professor and Director, Alberti Center for Bullying Abuse Prevention, Counseling, School, and Educational Psychology, Graduate School of Education, University at Buffalo, The State University of New York, Buffalo, NY, USA. 4. Gamma Kappa, Department Chair, Biobehavioral Health & Clinical Sciences, and Professor, School of Nursing, University at Buffalo, The State University of New York, Buffalo, NY, USA. 5. Assistant Professor, School of Nursing, University at Buffalo, The State University of New York, Buffalo, NY, USA. 6. Associate Professor, School of Nursing, University at Buffalo, The State University of New York, Buffalo, NY, USA.
Abstract
PURPOSE: Cyber victimization is a national mental health concern, especially among adolescents who are digital natives. The current study examined sleep quality as a mediator of the association between cyber victimization and depressive symptoms among adolescents. DESIGN AND METHOD: A prospective study design was utilized with a community sample of adolescents (N = 801; 57% female; mean age = 14.45, SD = .85) from the eastern United States. Participants completed (a) the Pittsburgh Sleep Quality Index; (b) the Cyber Victimization Scale; and (c) the Center for Epidemiologic Studies Depression Scale Revised via online surveys at baseline and 6-month follow-up. The inter-relationship between variables was analyzed by Hayes' mediation approach. FINDINGS: Cyber victimization was not directly associated with having depressive symptoms 6 months later when controlling for adolescents' poor sleep quality, sex, and age (direct effect [c'] = .012, t(676) = 1.12, p < .05, confidence interval [CI] -.008, .036). The mediation analysis indicated a significant indirect effect of poor sleep quality on the relationship between cyber victimization and depressive symptoms (ab = .005, bootstrapped standard error [SE] = .003, bootstrapped CI .001, .011; a is the effect of cyber victimization on poor sleep quality; b is the effect of poor sleep quality on depressive symptoms). Specifically, adolescents' cyber victimization led to poor sleep quality (a = .039, SE = .041, p < .05), which also led to increased depressive symptoms (b = .116, SE = .019, p < .001), after controlling for depressive symptoms at baseline, sex, and age. The indirect effect of cyber victimization on depressive symptoms was estimated through poor sleep quality (a*b = .039(.116) = .0045). CONCLUSIONS: The findings suggest that poor sleep quality may be a mechanism through which cyber bullying is related prospectively to depressive symptoms. Interventions for cyber-victimized adolescents should include assessment of sleep quality and incorporate sleep hygiene education. CLINICAL RELEVANCE: Adolescents should be screened for cyber victimization and sleep quality. Moreover, promotion of sleep hygiene among cyber-victimized adolescents may help to reduce depression.
PURPOSE: Cyber victimization is a national mental health concern, especially among adolescents who are digital natives. The current study examined sleep quality as a mediator of the association between cyber victimization and depressive symptoms among adolescents. DESIGN AND METHOD: A prospective study design was utilized with a community sample of adolescents (N = 801; 57% female; mean age = 14.45, SD = .85) from the eastern United States. Participants completed (a) the Pittsburgh Sleep Quality Index; (b) the Cyber Victimization Scale; and (c) the Center for Epidemiologic Studies Depression Scale Revised via online surveys at baseline and 6-month follow-up. The inter-relationship between variables was analyzed by Hayes' mediation approach. FINDINGS: Cyber victimization was not directly associated with having depressive symptoms 6 months later when controlling for adolescents' poor sleep quality, sex, and age (direct effect [c'] = .012, t(676) = 1.12, p < .05, confidence interval [CI] -.008, .036). The mediation analysis indicated a significant indirect effect of poor sleep quality on the relationship between cyber victimization and depressive symptoms (ab = .005, bootstrapped standard error [SE] = .003, bootstrapped CI .001, .011; a is the effect of cyber victimization on poor sleep quality; b is the effect of poor sleep quality on depressive symptoms). Specifically, adolescents' cyber victimization led to poor sleep quality (a = .039, SE = .041, p < .05), which also led to increased depressive symptoms (b = .116, SE = .019, p < .001), after controlling for depressive symptoms at baseline, sex, and age. The indirect effect of cyber victimization on depressive symptoms was estimated through poor sleep quality (a*b = .039(.116) = .0045). CONCLUSIONS: The findings suggest that poor sleep quality may be a mechanism through which cyber bullying is related prospectively to depressive symptoms. Interventions for cyber-victimized adolescents should include assessment of sleep quality and incorporate sleep hygiene education. CLINICAL RELEVANCE: Adolescents should be screened for cyber victimization and sleep quality. Moreover, promotion of sleep hygiene among cyber-victimized adolescents may help to reduce depression.
Authors: Ann John; Alexander Charles Glendenning; Amanda Marchant; Paul Montgomery; Anne Stewart; Sophie Wood; Keith Lloyd; Keith Hawton Journal: J Med Internet Res Date: 2018-04-19 Impact factor: 7.076