Soc Netw Anal Min

Suicide is the second leading cause of death among youth ages 10-19 in the USA. While suicide has long been recognized as a multifactorial issue, there is limited understanding regarding the complexities linking adverse childhood experiences (ACEs) to suicide ideation, attempt, and fatality among youth. In this paper, we develop a map of these complex linkages to provide a decision support tool regarding key issues in policymaking and intervention design, such as identifying multiple feedback loops (e.g., involving intergenerational effects) or comprehensively examining the rippling effects of an intervention. We use the methodology of systems mapping to structure the complex interrelationships of suicide and ACEs based on the perceptions of fifteen subject matter experts. Specifically, systems mapping allows us to gain insight into the feedback loops and potential emergent properties of ACEs and youth suicide. We describe our methodology and the results of fifteen one-on-one interviews, which are transformed into individual maps that are then aggregated and simplified to produce our final causal map. Our map is the largest to date on ACEs and suicide among youth, totaling 361 concepts and 946 interrelationships. Using a previously developed open-source software to navigate the map, we are able to explore how trauma may be perpetuated through familial, social, and historical concepts. In particular, we identify connections and pathways between ACEs and youth suicide that have not been identified in prior research, and which are of particular interest for youth suicide prevention efforts.CC999999/ImCDC/Intramural CDC HHSUnited States

An Online Environment to Compare Students’ and Expert Solutions to Ill-Structured Problems

Practitioners often face ill-structured problems. However, it is difficult for instructors to assess their students’ work on such problems, as a broad set of solutions exist and may depend on the context. One way to assess student learning is through the evaluation of their mental models, which can be presented in the form of a causal network or ‘map’. While comparing a student’s map to an expert’s map can assist with the evaluation, this is a challenging process, in part, due to variations in language, resulting in the use of different terms for the same construct. The first step of the comparison is to address these variations by aligning as many of the students’ terms with their equivalent in the expert’s map. We present the design and implementation of a software to assist with the alignment task. The software improves on previous work by optimizing usability (e.g., minimizing the number of clicks to create an alignment) and by leveraging previous alignments to recommend new ones. In addition, alignments can be done collaboratively, as our system is available online: one instructor can invite others to edit or see the alignments. Further improvements to this system may be achieved using content-based recommender systems or natural language processing