Surveillance of Domestic Violence Using Text Mining Outputs From Australian Police Records.

domestic violence mental illness public health surveillance text mining

Journal

Frontiers in psychiatry
ISSN: 1664-0640
Titre abrégé: Front Psychiatry
Pays: Switzerland
ID NLM: 101545006

Informations de publication

Date de publication:
2021
Historique:
received: 04 10 2021
accepted: 01 12 2021
entrez: 28 2 2022
pubmed: 1 3 2022
medline: 1 3 2022
Statut: epublish

Résumé

In Australia, domestic violence reports are mostly based on data from the police, courts, hospitals, and

Identifiants

pubmed: 35222105
doi: 10.3389/fpsyt.2021.787792
pmc: PMC8863744
doi:

Types de publication

Journal Article

Langues

eng

Pagination

787792

Informations de copyright

Copyright © 2022 Karystianis, Adily, Schofield, Wand, Lukmanjaya, Buchan, Nenadic and Butler.

Déclaration de conflit d'intérêts

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Auteurs

George Karystianis (G)

School of Population Health, University of New South Wales (NSW), Sydney, NSW, Australia.

Armita Adily (A)

School of Population Health, University of New South Wales (NSW), Sydney, NSW, Australia.

Peter W Schofield (PW)

Hunter New England Local Health District, Newcastle, NSW, Australia.

Handan Wand (H)

The Kirby Institute, University of New South Wales, Sydney, NSW, Australia.

Wilson Lukmanjaya (W)

School of Computer Science, University of Technology, Sydney, NSW, Australia.

Iain Buchan (I)

Institute of Population Health, University of Liverpool, Liverpool, United Kingdom.

Goran Nenadic (G)

School of Computer Science, University of Manchester, Manchester, United Kingdom.

Tony Butler (T)

School of Population Health, University of New South Wales (NSW), Sydney, NSW, Australia.

Classifications MeSH