CC BY 4.0 · ACI Open 2020; 04(02): e136-e148
DOI: 10.1055/s-0040-1718542
Original Article

Discovery of Comorbid Psychiatric Conditions among Youth Detainees in Juvenile Justice System using Clinical Data

Humayera Islam
1  Department of Health Management and Informatics, University of Missouri, Columbia, Missouri, United States
2  Institute of Statistical Research and Training, University of Dhaka, Dhaka, Bangladesh
3  Center for Biomedical Informatics, School of Medicine, University of Missouri, Columbia, Missouri, United States
,
Abu S. M. Mosa
1  Department of Health Management and Informatics, University of Missouri, Columbia, Missouri, United States
3  Center for Biomedical Informatics, School of Medicine, University of Missouri, Columbia, Missouri, United States
4  Institute for Data Science and Informatics, University of Missouri, Columbia, Missouri, United States
5  Department of Electrical and Computer Science, University of Missouri, Columbia, Missouri, United States
,
Hirsch K. Srivastava
6  Department of Psychiatry, School of Medicine, University of Missouri, Columbia, Missouri, United States
,
Vasanthi Mandhadi
3  Center for Biomedical Informatics, School of Medicine, University of Missouri, Columbia, Missouri, United States
,
Dhinakaran Rajendran
1  Department of Health Management and Informatics, University of Missouri, Columbia, Missouri, United States
,
Laine M. Young-Walker
6  Department of Psychiatry, School of Medicine, University of Missouri, Columbia, Missouri, United States
› Author Affiliations
Funding None.

Abstract

Objective The main aim was to analyze the prevalence and patterns of comorbidity in 11 identified broad categories of psychiatric conditions and 48 specific psychiatric conditions among 613 youth from the Missouri Division of Youth Services (DYS) residential sites using advanced data mining techniques on clinical assessment data.

Methods This study was based on youth detainee population at DYS residential placements receiving psychiatric care through the telemedicine network established between DYS and University of Missouri Department of Psychiatry. Association Rule Mining (ARM) algorithm was used to determine the associations and the co-occurrence pattern among the comorbid psychiatric conditions.

Results About 88% of the DYS youth are diagnosed with two or more psychiatric disorders. From the ARM analysis, the most commonly co-occurred disorders are obtained as substance-related or -addicted disorders (SUD) and disruptive, impulse-control, and conduct disorders (CD) (n [%] = 258 [42.1%], followed by SUD, CD, and depressive disorder (DD) (145 [23.7%]), SUD, CD, and neurodevelopmental disorder (NDD) (133 [21.7%]), and DD, CD and NDD (120 [19.6%]).

Discussion The study found high prevalence of comorbidity among the youth patients of the Missouri DYS facilities receiving care through the University of Missouri telemedicine network. The ideal scenario for assessment of any of these disorders in a patient should include substantial consideration in delineating the symptoms and history before eliminating any of them.

Conclusion The comorbid patterns obtained can help in determining treatment regimens for DYS youth that can be effective in reducing recidivism and delinquency.

Protection of Human and Animal Subjects

The study was approved by University of XXX Institutional Review Board.




Publication History

Received: 12 February 2020

Accepted: 27 August 2020

Publication Date:
17 November 2020 (online)

© 2020. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution License, permitting unrestricted use, distribution, and reproduction so long as the original work is properly cited. (https://creativecommons.org/licenses/by/4.0/)

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