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Implications of sex offender classification on reporting demographic characteristics, health, and criminal careers: results from an Australian jurisdiction

BACKGROUND: Cross-sectional and retrospective offence data are often used to classify sex offenders in epidemiological and survey research, but little empirical evidence exists regarding the practical implications of this for applied research. This study describes the classification of sex offenders...

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Autores principales: Gullotta, Mathew, Greenberg, David, Adily, Armita, Cale, Jesse, Butler, Tony G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7189498/
https://www.ncbi.nlm.nih.gov/pubmed/32345224
http://dx.doi.org/10.1186/s12874-020-00960-w
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author Gullotta, Mathew
Greenberg, David
Adily, Armita
Cale, Jesse
Butler, Tony G.
author_facet Gullotta, Mathew
Greenberg, David
Adily, Armita
Cale, Jesse
Butler, Tony G.
author_sort Gullotta, Mathew
collection PubMed
description BACKGROUND: Cross-sectional and retrospective offence data are often used to classify sex offenders in epidemiological and survey research, but little empirical evidence exists regarding the practical implications of this for applied research. This study describes the classification of sex offenders from a cohort of prisoners recruited as part of an Australian inmate health survey and the implications for reporting results. METHODS: Data-linkage was used to join the New South Wales (NSW) Inmate Health Surveys to the states re-offending database to identify men with histories of sexual offending. Sex offenders were classified into men who sexually offended against children only (ChildSOs), against adults only (AdultSOs), and men who sexually offended against both children and adults (Age-PolySOs). RESULTS: Using historical offending data rather than the current offence information only, an additional 35.4% of men with histories of sexual offences were identified. Differences were found between the three sex offender subgroups in terms of demographic characteristics, health, and criminal careers. Age-PolySOs reported higher educational attainment, were less likely to report being self-employed, single marital status, and having children. Half the ChildSOs self-reported a mental health issue and half of the ChildSOs and Age-PolySOs reported four or more chronic health conditions. Age-PolySOs were older than the other sex offender groups when committing their first non-sexual, non-violent crime (M = 43.2 years, SD = 13.8); violent crime (M = 39.5 years, SD = 11.1); and sexual crime (M = 47.8 years, SD = 11.2). Age-PolySOs also committed more sexual offences (M = 5.91, SD = 11.2) compared to those who only offended against one victim age group. CONCLUSION: These findings suggested that historical offending records should be used to more accurately identify sex offender subgroups and that differences in demographic, health, and criminal careers exist for the different sex offender subgroups.
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spelling pubmed-71894982020-05-04 Implications of sex offender classification on reporting demographic characteristics, health, and criminal careers: results from an Australian jurisdiction Gullotta, Mathew Greenberg, David Adily, Armita Cale, Jesse Butler, Tony G. BMC Med Res Methodol Research Article BACKGROUND: Cross-sectional and retrospective offence data are often used to classify sex offenders in epidemiological and survey research, but little empirical evidence exists regarding the practical implications of this for applied research. This study describes the classification of sex offenders from a cohort of prisoners recruited as part of an Australian inmate health survey and the implications for reporting results. METHODS: Data-linkage was used to join the New South Wales (NSW) Inmate Health Surveys to the states re-offending database to identify men with histories of sexual offending. Sex offenders were classified into men who sexually offended against children only (ChildSOs), against adults only (AdultSOs), and men who sexually offended against both children and adults (Age-PolySOs). RESULTS: Using historical offending data rather than the current offence information only, an additional 35.4% of men with histories of sexual offences were identified. Differences were found between the three sex offender subgroups in terms of demographic characteristics, health, and criminal careers. Age-PolySOs reported higher educational attainment, were less likely to report being self-employed, single marital status, and having children. Half the ChildSOs self-reported a mental health issue and half of the ChildSOs and Age-PolySOs reported four or more chronic health conditions. Age-PolySOs were older than the other sex offender groups when committing their first non-sexual, non-violent crime (M = 43.2 years, SD = 13.8); violent crime (M = 39.5 years, SD = 11.1); and sexual crime (M = 47.8 years, SD = 11.2). Age-PolySOs also committed more sexual offences (M = 5.91, SD = 11.2) compared to those who only offended against one victim age group. CONCLUSION: These findings suggested that historical offending records should be used to more accurately identify sex offender subgroups and that differences in demographic, health, and criminal careers exist for the different sex offender subgroups. BioMed Central 2020-04-28 /pmc/articles/PMC7189498/ /pubmed/32345224 http://dx.doi.org/10.1186/s12874-020-00960-w Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research Article
Gullotta, Mathew
Greenberg, David
Adily, Armita
Cale, Jesse
Butler, Tony G.
Implications of sex offender classification on reporting demographic characteristics, health, and criminal careers: results from an Australian jurisdiction
title Implications of sex offender classification on reporting demographic characteristics, health, and criminal careers: results from an Australian jurisdiction
title_full Implications of sex offender classification on reporting demographic characteristics, health, and criminal careers: results from an Australian jurisdiction
title_fullStr Implications of sex offender classification on reporting demographic characteristics, health, and criminal careers: results from an Australian jurisdiction
title_full_unstemmed Implications of sex offender classification on reporting demographic characteristics, health, and criminal careers: results from an Australian jurisdiction
title_short Implications of sex offender classification on reporting demographic characteristics, health, and criminal careers: results from an Australian jurisdiction
title_sort implications of sex offender classification on reporting demographic characteristics, health, and criminal careers: results from an australian jurisdiction
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7189498/
https://www.ncbi.nlm.nih.gov/pubmed/32345224
http://dx.doi.org/10.1186/s12874-020-00960-w
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