ArticleThe Psychiatric quarterly2017
A Pilot Study on Developing a Standardized and Sensitive School Violence Risk Assessment with Manual Annotation.
Article in The Psychiatric quarterly, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Forecasting school violence risk with incomplete interview data: an automated assessment approach.JAMIA open · 2025Article
- Investigation of bias in the automated assessment of school violence.Journal of biomedical informatics · 2024Article
- Finding warning markers: Leveraging natural language processing and machine learning technologies to detect risk of school violence.International journal of medical informatics · 2020Article
- Automated Risk Assessment for School Violence: a Pilot Study.The Psychiatric quarterly · 2018Article
- Eye Gaze Patterns Associated with Aggressive Tendencies in Adolescence.The Psychiatric quarterly · 2018Article
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Authors and funding
7 authors.
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Abstract
School violence has increased over the past decade and innovative, sensitive, and standardized approaches to assess school violence risk are needed. In our current feasibility study, we initialized a standardized, sensitive, and rapid school violence risk approach with manual annotation. Manual annotation is the process of analyzing a student's transcribed interview to extract relevant information (e.g., key words) to school violence risk levels that are associated with students' behaviors, attitudes, feelings, use of technology (social media and video games), and other activities. In this feasibility study, we first implemented school violence risk assessments to evaluate risk levels by interviewing the student and parent separately at the school or the hospital to complete our novel school safety scales. We completed 25 risk assessments, resulting in 25 transcribed interviews of 12-18 year olds from 15 schools in Ohio and Kentucky. We then analyzed structured professional judgments, language, and patterns associated with school violence risk levels by using manual annotation and statistical methodology. To analyze the student interviews, we initiated the development of an annotation guideline to extract key information that is associated with students' behaviors, attitudes, feelings, use of technology and other activities. Statistical analysis was applied to associate the significant categories with students' risk levels to identify key factors which will help with developing action steps to reduce risk. In a future study, we plan to recruit more subjects in order to fully develop the manual annotation which will result in a more standardized and sensitive approach to school violence assessments.
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