Benjamin D. Maldonado, Ryan Schuerkamp, Cassidy M. Martin, Ketra L. Rice, Nisha Nataraj, Margaret M. Brown, Christopher R. Harper, Curtis Florence, Philippe J. Giabbanelli
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引用次数: 0
Abstract
Suicide is a leading cause of death in the United States, particularly among adolescents. In recent years, suicidal ideation, attempts, and fatalities have increased. Systems maps can effectively represent complex issues such as suicide, thus providing decision-support tools for policymakers to identify and evaluate interventions. While network science has served to examine systems maps in fields such as obesity, there is limited research at the intersection of suicidology and network science. In this paper, we apply network science to a large causal map of adverse childhood experiences (ACEs) and suicide to address this gap. The National Center for Injury Prevention and Control (NCIPC) within the Centers for Disease Control and Prevention recently created a causal map that encapsulates ACEs and adolescent suicide in 361 concept nodes and 946 directed relationships. In this study, we examine this map and three similar models through three related questions: (Q1) how do existing network-based models of suicide differ in terms of node- and network-level characteristics? (Q2) Using the NCIPC model as a unifying framework, how do current suicide intervention strategies align with prevailing theories of suicide? (Q3) How can the use of network science on the NCIPC model guide suicide interventions?
在美国,自杀是导致死亡的一个主要原因,尤其是在青少年中。近年来,自杀意念、自杀未遂和死亡人数都有所增加。系统地图可以有效地表示自杀等复杂问题,从而为决策者提供决策支持工具,以确定和评估干预措施。虽然网络科学已在肥胖症等领域用于研究系统地图,但在自杀学和网络科学的交叉领域,研究还很有限。在本文中,我们将网络科学应用于童年不良经历(ACE)与自杀的大型因果关系图,以弥补这一不足。美国疾病控制和预防中心(Centers for Disease Control and Prevention)下属的国家伤害预防和控制中心(NCIPC)最近绘制了一张因果关系图,将ACE和青少年自杀囊括在361个概念节点和946个定向关系中。在本研究中,我们通过三个相关问题对该地图和三个类似模型进行了研究:(问题1)现有的基于网络的自杀模型在节点和网络层面的特征方面有何不同?(Q2) 以 NCIPC 模型为统一框架,当前的自杀干预策略如何与流行的自杀理论保持一致?(Q3) 如何利用网络科学来指导 NCIPC 模型中的自杀干预措施?
期刊介绍:
Network Science is an important journal for an important discipline - one using the network paradigm, focusing on actors and relational linkages, to inform research, methodology, and applications from many fields across the natural, social, engineering and informational sciences. Given growing understanding of the interconnectedness and globalization of the world, network methods are an increasingly recognized way to research aspects of modern society along with the individuals, organizations, and other actors within it. The discipline is ready for a comprehensive journal, open to papers from all relevant areas. Network Science is a defining work, shaping this discipline. The journal welcomes contributions from researchers in all areas working on network theory, methods, and data.