본문 바로가기
HOME> 논문 > 논문 검색상세

논문 상세정보

Journal of biomedical informatics v.75 suppl., 2017년, pp.S149 - S159   SCI SCIE
본 등재정보는 저널의 등재정보를 참고하여 보여주는 베타서비스로 정확한 논문의 등재여부는 등재기관에 확인하시기 바랍니다.

Exploring associations of clinical and social parameters with violent behaviors among psychiatric patients

Dai, Hong-Jie (Department of Computer Science and Information Engineering, National Taitung University, Taitung, Taiwan ) ; Su, Emily Chia-Yu (Graduate Institute of Biomedical Informatics, Taipei Medical University, Taipei, Taiwan ) ; Uddin, Mohy (King Abdullah International Medical Research Center, King Saud Bin Abdulaziz University for Health Sciences, Publication Office, King Abdulaziz Medical City, Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia ) ; Jonnagaddala, Jitendra (School of Public Health and Community Medicine, UNSW Sydney, Australia ) ; Wu, Chi-Shin (Department of Psychiatry, National Taiwan University Hospital and College of Medicine, National Taiwan University, Taipei, Taiwan ) ; Syed-Abdul, Shabbir (Graduate Institute of Biomedical Informatics, Taipei Medical University, Taipei, Taiwan ) ;
  • 초록  

    Abstract Evidence has revealed interesting associations of clinical and social parameters with violent behaviors of patients with psychiatric disorders. Men are more violent preceding and during hospitalization, whereas women are more violent than men throughout the 3days following a hospital admission. It has also been proven that mental disorders may be a consistent risk factor for the occurrence of violence. In order to better understand violent behaviors of patients with psychiatric disorders, it is important to investigate both the clinical symptoms and psychosocial factors that accompany violence in these patients. In this study, we utilized a dataset released by the Partners Healthcare and Neuropsychiatric Genome-scale and RDoC Individualized Domains project of Harvard Medical School to develop a unique text mining pipeline that processes unstructured clinical data in order to recognize clinical and social parameters such asage, gender, history of alcohol use, and violent behaviors, and explored the associations between these parameters and violent behaviors of patients with psychiatric disorders. The aim of our work was to demonstrate the feasibility of mining factors that are strongly associated with violent behaviors among psychiatric patients from unstructured psychiatric evaluation records using clinical text mining. Experiment results showed that stimulants, followed by a family history of violent behavior, suicidal behaviors, and financial stress were strongly associated with violent behaviors. Key aspects explicated in this paper include employing our text mining pipeline to extract clinical and social factors linked with violent behaviors, generating association rules to uncover possible associations between these factors and violent behaviors, and lastly the ranking of top rules associated with violent behaviors using statistical analysis and interpretation. Highlights Text mining can be used to explore parameters associated with violent behaviors in unstructured clinical notes. Mental disorders are a significant risk factor for the violent behavior among the patients. Stimulants and suicidal tendency were also strongly associated with the patients’ violent behavior. Graphical abstract [DISPLAY OMISSION]


  • 주제어

    Violent behavior .   Text mining .   Psychiatric evaluation record .   Association rule mining .   Odds ratio.  

 활용도 분석

  • 상세보기

    amChart 영역
  • 원문보기

    amChart 영역

원문보기

무료다운로드
  • 원문이 없습니다.
유료다운로드

유료 다운로드의 경우 해당 사이트의 정책에 따라 신규 회원가입, 로그인, 유료 구매 등이 필요할 수 있습니다. 해당 사이트에서 발생하는 귀하의 모든 정보활동은 NDSL의 서비스 정책과 무관합니다.

원문복사신청을 하시면, 일부 해외 인쇄학술지의 경우 외국학술지지원센터(FRIC)에서
무료 원문복사 서비스를 제공합니다.

NDSL에서는 해당 원문을 복사서비스하고 있습니다. 위의 원문복사신청 또는 장바구니 담기를 통하여 원문복사서비스 이용이 가능합니다.

이 논문과 함께 출판된 논문 + 더보기