Literature DB >> 27528455

A Pilot Study on Developing a Standardized and Sensitive School Violence Risk Assessment with Manual Annotation.

Drew H Barzman1, Yizhao Ni2, Marcus Griffey2, Bianca Patel2, Ashaki Warren2, Edward Latessa2, Michael Sorter2.   

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.

Keywords:  Manual annotation; Prevention; Risk assessment; School violence

Mesh:

Year:  2017        PMID: 27528455     DOI: 10.1007/s11126-016-9458-7

Source DB:  PubMed          Journal:  Psychiatr Q        ISSN: 0033-2720


  12 in total

1.  A comparative study of adolescent risk assessment instruments: predictive and incremental validity.

Authors:  Jennifer L Welsh; Fred Schmidt; Lauren McKinnon; H K Chattha; Joanna R Meyers
Journal:  Assessment       Date:  2008-03

2.  Predictive validity of risk assessments in juvenile offenders: Comparing the SAVRY, PCL:YV, and YLS/CMI with unstructured clinical assessments.

Authors:  Ed L B Hilterman; Tonia L Nicholls; Chijs van Nieuwenhuizen
Journal:  Assessment       Date:  2013-08-06

3.  Valuing structured professional judgment: predictive validity, decision-making, and the clinical-actuarial conflict.

Authors:  Paul R Falzer
Journal:  Behav Sci Law       Date:  2013-01-21

4.  Brief Rating of Aggression by Children and Adolescents (BRACHA): development of a tool for assessing risk of inpatients' aggressive behavior.

Authors:  Drew H Barzman; Lauren Brackenbury; Loretta Sonnier; Beverly Schnell; Amy Cassedy; Shelia Salisbury; Michael Sorter; Douglas Mossman
Journal:  J Am Acad Psychiatry Law       Date:  2011

5.  Automated detection of medication administration errors in neonatal intensive care.

Authors:  Qi Li; Eric S Kirkendall; Eric S Hall; Yizhao Ni; Todd Lingren; Megan Kaiser; Nataline Lingren; Haijun Zhai; Imre Solti; Kristin Melton
Journal:  J Biomed Inform       Date:  2015-07-17       Impact factor: 6.317

6.  Brief Rating of Aggression by Children and Adolescents (BRACHA): a reliability study.

Authors:  Drew Barzman; Douglas Mossman; Loretta Sonnier; Michael Sorter
Journal:  J Am Acad Psychiatry Law       Date:  2012

7.  An end-to-end hybrid algorithm for automated medication discrepancy detection.

Authors:  Qi Li; Stephen Andrew Spooner; Megan Kaiser; Nataline Lingren; Jessica Robbins; Todd Lingren; Huaxiu Tang; Imre Solti; Yizhao Ni
Journal:  BMC Med Inform Decis Mak       Date:  2015-05-06       Impact factor: 2.796

8.  Evaluating the impact of pre-annotation on annotation speed and potential bias: natural language processing gold standard development for clinical named entity recognition in clinical trial announcements.

Authors:  Todd Lingren; Louise Deleger; Katalin Molnar; Haijun Zhai; Jareen Meinzen-Derr; Megan Kaiser; Laura Stoutenborough; Qi Li; Imre Solti
Journal:  J Am Med Inform Assoc       Date:  2013-09-03       Impact factor: 4.497

9.  Developing a manually annotated clinical document corpus to identify phenotypic information for inflammatory bowel disease.

Authors:  Brett R South; Shuying Shen; Makoto Jones; Jennifer Garvin; Matthew H Samore; Wendy W Chapman; Adi V Gundlapalli
Journal:  BMC Bioinformatics       Date:  2009-09-17       Impact factor: 3.169

10.  Developing and evaluating an automated appendicitis risk stratification algorithm for pediatric patients in the emergency department.

Authors:  Louise Deleger; Holly Brodzinski; Haijun Zhai; Qi Li; Todd Lingren; Eric S Kirkendall; Evaline Alessandrini; Imre Solti
Journal:  J Am Med Inform Assoc       Date:  2013-10-15       Impact factor: 4.497

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  3 in total

1.  Finding warning markers: Leveraging natural language processing and machine learning technologies to detect risk of school violence.

Authors:  Yizhao Ni; Drew Barzman; Alycia Bachtel; Marcus Griffey; Alexander Osborn; Michael Sorter
Journal:  Int J Med Inform       Date:  2020-04-25       Impact factor: 4.046

2.  Eye Gaze Patterns Associated with Aggressive Tendencies in Adolescence.

Authors:  Cameron Laue; Marcus Griffey; Ping-I Lin; Kirk Wallace; Menno van der Schoot; Paul Horn; Ernest Pedapati; Drew Barzman
Journal:  Psychiatr Q       Date:  2018-09

3.  Automated Risk Assessment for School Violence: a Pilot Study.

Authors:  Drew Barzman; Yizhao Ni; Marcus Griffey; Alycia Bachtel; Kenneth Lin; Hannah Jackson; Michael Sorter; Melissa DelBello
Journal:  Psychiatr Q       Date:  2018-12
  3 in total

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