Mandy W M Gijzen1, Sanne P A Rasing2, Daan H M Creemers3, Filip Smit4, Rutger C M E Engels5, Derek De Beurs6. 1. Trimbos Institute (Netherlands Institute of Mental Health and Addiction), P.O. Box 725, 3500 AS, Utrecht, Netherlands; Erasmus School of Social and Behavioural Sciences, Erasmus University Rotterdam, P.O. Box 1738, 3000 DR, Rotterdam, Netherlands; GGZ Oost Brabant, P.O. Box 3, 5427 ZG, Boekel, Netherlands. Electronic address: MGijzen@trimbos.nl. 2. GGZ Oost Brabant, P.O. Box 3, 5427 ZG, Boekel, Netherlands; Child and Adolescent Studies, Utrecht University, P.O. Box 80140, 3508 TC, Utrecht, Netherlands. Electronic address: SPA.Rasing@ggzoostbrabant.nl. 3. GGZ Oost Brabant, P.O. Box 3, 5427 ZG, Boekel, Netherlands; Behavioral Science Institute, Radboud University Nijmegen, P.O. Box 9104, 6500 HC, Nijmegen, Netherlands. Electronic address: DHM.Creemers@ggzoostbrabant.nl. 4. Trimbos Institute (Netherlands Institute of Mental Health and Addiction), P.O. Box 725, 3500 AS, Utrecht, Netherlands; Department of Clinical, Neuro and Developmental Psychology and Department of Epidemiology and Biostatistics, Amsterdam Public Health research institute, University Medical Centers, Location VUmc, P.O. Box 7057, 1007 MB, Amsterdam, Netherlands. Electronic address: FSmit@trimbos.nl. 5. Erasmus School of Social and Behavioural Sciences, Erasmus University Rotterdam, P.O. Box 1738, 3000 DR, Rotterdam, Netherlands. Electronic address: Rutger.engels@eur.nl. 6. Trimbos Institute (Netherlands Institute of Mental Health and Addiction), P.O. Box 725, 3500 AS, Utrecht, Netherlands; Department of Clinical, Neuro and Developmental Psychology and Department of Epidemiology and Biostatistics, Amsterdam Public Health research institute, University Medical Centers, Location VUmc, P.O. Box 7057, 1007 MB, Amsterdam, Netherlands. Electronic address: DBeurs@trimbos.nl.
Abstract
INTRODUCTION: According to the network perspective, psychopathology is the result of interactions between symptoms. A previous study used network analysis to identify central symptoms of adolescent depression. The aim of the current study was replicate and extend this study by including suicide ideation as a symptom of depression and evaluating which depression symptoms are contributing factors to suicide ideation in adolescents. METHOD: A large community sample (N = 5,888) of adolescents aged 11-16 years completed the Children's Depression Inventory (CDI-2). Network analysis was used to identify the network structure of the CDI-2 and which symptoms were directly related to suicide ideation in the network. Additionally, the network structure of adolescents who did and did not experience suicide ideation were compared. RESULTS: Results pertaining the depression network were highly similar to the study we aimed to replicate. The most central symptoms in the depression network were loneliness, sadness, self-hatred, fatigue, self-deprecation and crying. Loneliness explained most variance of suicide ideation. Adolescents who experience suicide ideation had a similar network structure as those who do not. Adolescents with suicide ideation scored higher on all depression symptoms. LIMITATIONS: The use of cross-sectional data indicates that only undirected networks and results based on between-subject data could be estimated. CONCLUSIONS: Loneliness was a central factor for depression networks and also the most contributing factor of suicide ideation. Preventative efforts should consider taking experiences of loneliness into account as these are especially prevalent in adolescents. Suicide ideation seems more representative of depression symptom severity in adolescents.
INTRODUCTION: According to the network perspective, psychopathology is the result of interactions between symptoms. A previous study used network analysis to identify central symptoms of adolescent depression. The aim of the current study was replicate and extend this study by including suicide ideation as a symptom of depression and evaluating which depression symptoms are contributing factors to suicide ideation in adolescents. METHOD: A large community sample (N = 5,888) of adolescents aged 11-16 years completed the Children's Depression Inventory (CDI-2). Network analysis was used to identify the network structure of the CDI-2 and which symptoms were directly related to suicide ideation in the network. Additionally, the network structure of adolescents who did and did not experience suicide ideation were compared. RESULTS: Results pertaining the depression network were highly similar to the study we aimed to replicate. The most central symptoms in the depression network were loneliness, sadness, self-hatred, fatigue, self-deprecation and crying. Loneliness explained most variance of suicide ideation. Adolescents who experience suicide ideation had a similar network structure as those who do not. Adolescents with suicide ideation scored higher on all depression symptoms. LIMITATIONS: The use of cross-sectional data indicates that only undirected networks and results based on between-subject data could be estimated. CONCLUSIONS: Loneliness was a central factor for depression networks and also the most contributing factor of suicide ideation. Preventative efforts should consider taking experiences of loneliness into account as these are especially prevalent in adolescents. Suicide ideation seems more representative of depression symptom severity in adolescents.
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