Automatic Extraction of Research Themes in Epidemiological Criminology From PubMed Abstracts From 1946 to 2020: Text Mining Study.

PubMed criminology epidemiological criminology epidemiology open research research priorities study determinant study outcome

Journal

JMIR formative research
ISSN: 2561-326X
Titre abrégé: JMIR Form Res
Pays: Canada
ID NLM: 101726394

Informations de publication

Date de publication:
22 Sep 2023
Historique:
received: 06 06 2023
accepted: 21 08 2023
revised: 21 08 2023
medline: 22 9 2023
pubmed: 22 9 2023
entrez: 22 9 2023
Statut: epublish

Résumé

The emerging field of epidemiological criminology studies the intersection between public health and justice systems. To increase the value of and reduce waste in research activities in this area, it is important to perform transparent research priority setting considering the needs of research beneficiaries and end users along with a systematic assessment of the existing research activities to address gaps and harness opportunities. In this study, we aimed to examine published research outputs in epidemiological criminology to assess gaps between published outputs and current research priorities identified by prison stakeholders. A rule-based method was applied to 23,904 PubMed epidemiological criminology abstracts to extract the study determinants and outcomes (ie, "themes"). These were mapped against the research priorities identified by Australian prison stakeholders to assess the differences from research outputs. The income level of the affiliation country of the first authors was also identified to compare the ranking of research priorities in countries categorized by income levels. On an evaluation set of 100 abstracts, the identification of themes returned an F The identification of research themes from PubMed epidemiological criminology research abstracts is possible through the application of a rule-based text mining method. The frequency of the investigated themes may reflect historical developments concerning disease prevalence, treatment advances, and the social understanding of illness and incarcerated populations. The differences between income status groups are likely to be explained by local health priorities and immediate health risks. Notable gaps between stakeholder research priorities and research outputs concerned themes that were more focused on social factors and systems and may reflect publication bias or self-publication selection, highlighting the need for further research on prison health services and the social determinants of health. Different jurisdictions, countries, and regions should undertake similar systematic and transparent research priority-setting processes.

Sections du résumé

BACKGROUND BACKGROUND
The emerging field of epidemiological criminology studies the intersection between public health and justice systems. To increase the value of and reduce waste in research activities in this area, it is important to perform transparent research priority setting considering the needs of research beneficiaries and end users along with a systematic assessment of the existing research activities to address gaps and harness opportunities.
OBJECTIVE OBJECTIVE
In this study, we aimed to examine published research outputs in epidemiological criminology to assess gaps between published outputs and current research priorities identified by prison stakeholders.
METHODS METHODS
A rule-based method was applied to 23,904 PubMed epidemiological criminology abstracts to extract the study determinants and outcomes (ie, "themes"). These were mapped against the research priorities identified by Australian prison stakeholders to assess the differences from research outputs. The income level of the affiliation country of the first authors was also identified to compare the ranking of research priorities in countries categorized by income levels.
RESULTS RESULTS
On an evaluation set of 100 abstracts, the identification of themes returned an F
CONCLUSIONS CONCLUSIONS
The identification of research themes from PubMed epidemiological criminology research abstracts is possible through the application of a rule-based text mining method. The frequency of the investigated themes may reflect historical developments concerning disease prevalence, treatment advances, and the social understanding of illness and incarcerated populations. The differences between income status groups are likely to be explained by local health priorities and immediate health risks. Notable gaps between stakeholder research priorities and research outputs concerned themes that were more focused on social factors and systems and may reflect publication bias or self-publication selection, highlighting the need for further research on prison health services and the social determinants of health. Different jurisdictions, countries, and regions should undertake similar systematic and transparent research priority-setting processes.

Identifiants

pubmed: 37738080
pii: v7i1e49721
doi: 10.2196/49721
pmc: PMC10559193
doi:

Types de publication

Journal Article

Langues

eng

Pagination

e49721

Informations de copyright

©George Karystianis, Paul Simpson, Wilson Lukmanjaya, Natasha Ginnivan, Goran Nenadic, Iain Buchan, Tony Butler. Originally published in JMIR Formative Research (https://formative.jmir.org), 22.09.2023.

Références

J Biomed Semantics. 2014 May 19;5:22
pubmed: 24949194
Int J Prison Health. 2017 Jun 12;13(2):113-123
pubmed: 28581378
Trends Biotechnol. 2006 Dec;24(12):571-9
pubmed: 17045684
AMIA Annu Symp Proc. 2008 Nov 06;:141-5
pubmed: 18999067
PLoS Comput Biol. 2013;9(2):e1002854
pubmed: 23408875
J Health Soc Behav. 2010;51 Suppl:S28-40
pubmed: 20943581
Am J Orthod Dentofacial Orthop. 2006 Oct;130(4):523-30
pubmed: 17045153
J Biomed Inform. 2017 Jun;70:27-34
pubmed: 28455150
BMJ Open. 2019 Jul 23;9(7):e026806
pubmed: 31340959
Lancet Public Health. 2021 Oct;6(10):e771-e779
pubmed: 34115972
Interact J Med Res. 2022 Dec 5;11(2):e42891
pubmed: 36469411
J Law Med. 2015 Sep;23(1):41-9
pubmed: 26554196
BMC Med Inform Decis Mak. 2010 Sep 28;10:56
pubmed: 20920176
Lancet. 2011 Mar 12;377(9769):956-65
pubmed: 21093904
Lancet. 2014 Jan 11;383(9912):156-65
pubmed: 24411644
Am J Public Health. 2009 Mar;99(3):397-402
pubmed: 19150901
BMJ Open. 2016 Jan 14;6(1):e010125
pubmed: 26769790
BMC Med Res Methodol. 2018 Nov 14;18(1):131
pubmed: 30428834
Syst Rev. 2022 Dec 23;11(1):277
pubmed: 36564846
Crim Behav Ment Health. 2013 Dec;23(5):315-20
pubmed: 24311445
J Gen Intern Med. 2019 Aug;34(8):1388-1389
pubmed: 31011958
Med J Aust. 1991 Dec 2-16;155(11-12):812-8
pubmed: 1745179
J Telemed Telecare. 2008;14(7):354-8
pubmed: 18852316
Med J Aust. 2007 Oct 1;187(7):387-90
pubmed: 17908000
Nat Rev Gastroenterol Hepatol. 2022 Aug;19(8):533-550
pubmed: 35595834

Auteurs

George Karystianis (G)

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

Paul Simpson (P)

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

Wilson Lukmanjaya (W)

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

Natasha Ginnivan (N)

School of Psychology, University of New South Wales, Sydney, Australia.

Goran Nenadic (G)

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

Iain Buchan (I)

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

Tony Butler (T)

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

Classifications MeSH