Mental disorders and medical comorbidities: Association rule mining approach

Chia Hui Wang, Tzu Yin Lee, King Cheung Hui, Min Huey Chung

Research output: Contribution to journalArticle

Abstract

Purpose: This study explored the medical comorbidities of mental disorders using association rule mining. Design and methods: Patients diagnosed with mental disorders between 2002 and 2010 were identified. An equal number of nonmental disorder subjects were randomly selected and matched with case group by age and gender. Findings: Sleep disorders and digestive diseases were frequent comorbidities among mental disorders. The specific medical comorbidities were diabetes mellitus, chronic liver disease, extrapyramidal diseases, disorders of stomach function, general symptoms, sleep disturbance, and family circumstances. Practice implications: The results suggest that education of professional knowledge of comorbid conditions should be provided to nurses for caring patients with mental illnesses.

Original languageEnglish
Pages (from-to)517-526
Number of pages10
JournalPerspectives in Psychiatric Care
Volume55
Issue number3
DOIs
Publication statusPublished - Jul 1 2019

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Mental Disorders
Comorbidity
Basal Ganglia Diseases
Stomach Diseases
Professional Education
Mentally Ill Persons
Liver Diseases
Diabetes Mellitus
Sleep
Chronic Disease
Age Groups
Nurses

Keywords

  • association rule mining
  • comorbidity
  • psychiatric disorder

ASJC Scopus subject areas

  • Phychiatric Mental Health

Cite this

Mental disorders and medical comorbidities : Association rule mining approach. / Wang, Chia Hui; Lee, Tzu Yin; Hui, King Cheung; Chung, Min Huey.

In: Perspectives in Psychiatric Care, Vol. 55, No. 3, 01.07.2019, p. 517-526.

Research output: Contribution to journalArticle

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