Sarah Hodgkinson, Anthony Dixon, Eric Halford, Graham Farrell
{"title":"新冠肺炎大流行中的家庭虐待:旨在克服趋势衡量的共同局限性的措施。","authors":"Sarah Hodgkinson, Anthony Dixon, Eric Halford, Graham Farrell","doi":"10.1186/s40163-023-00190-7","DOIUrl":null,"url":null,"abstract":"<p><p>Research on pandemic domestic abuse trends has produced inconsistent findings reflecting differences in definitions, data and method. This study analyses 43,488 domestic abuse crimes recorded by a UK police force. Metrics and analytic approaches are tailored to address key methodological issues in three key ways. First, it was hypothesised that reporting rates changed during lockdown, so natural language processing was used to interrogate untapped free-text information in police records to develop a novel indicator of change in reporting. Second, it was hypothesised that abuse would change differentially for those cohabiting (due to physical proximity) compared to non-cohabitees, which was assessed via a proxy measure. Third, the analytic approaches used were change-point analysis and anomaly detection: these are more independent than regression analysis for present purposes in gauging the timing and duration of significant change. However, the main findings were largely contrary to expectation: (1) domestic abuse did not increase during the first national lockdown in early 2020 but increased across a prolonged post-lockdown period, (2) the post-lockdown increase did not reflect change in reporting by victims, and; (3) the proportion of abuse between cohabiting partners, at around 40 percent of the total, did not increase significantly during or after the lockdown. The implications of these unanticipated findings are discussed.</p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at 10.1186/s40163-023-00190-7.</p>","PeriodicalId":37844,"journal":{"name":"Crime Science","volume":null,"pages":null},"PeriodicalIF":3.1000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10262932/pdf/","citationCount":"0","resultStr":"{\"title\":\"Domestic abuse in the Covid-19 pandemic: measures designed to overcome common limitations of trend measurement.\",\"authors\":\"Sarah Hodgkinson, Anthony Dixon, Eric Halford, Graham Farrell\",\"doi\":\"10.1186/s40163-023-00190-7\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Research on pandemic domestic abuse trends has produced inconsistent findings reflecting differences in definitions, data and method. This study analyses 43,488 domestic abuse crimes recorded by a UK police force. Metrics and analytic approaches are tailored to address key methodological issues in three key ways. First, it was hypothesised that reporting rates changed during lockdown, so natural language processing was used to interrogate untapped free-text information in police records to develop a novel indicator of change in reporting. Second, it was hypothesised that abuse would change differentially for those cohabiting (due to physical proximity) compared to non-cohabitees, which was assessed via a proxy measure. Third, the analytic approaches used were change-point analysis and anomaly detection: these are more independent than regression analysis for present purposes in gauging the timing and duration of significant change. However, the main findings were largely contrary to expectation: (1) domestic abuse did not increase during the first national lockdown in early 2020 but increased across a prolonged post-lockdown period, (2) the post-lockdown increase did not reflect change in reporting by victims, and; (3) the proportion of abuse between cohabiting partners, at around 40 percent of the total, did not increase significantly during or after the lockdown. The implications of these unanticipated findings are discussed.</p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at 10.1186/s40163-023-00190-7.</p>\",\"PeriodicalId\":37844,\"journal\":{\"name\":\"Crime Science\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.1000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10262932/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Crime Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1186/s40163-023-00190-7\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2023/6/13 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"CRIMINOLOGY & PENOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Crime Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1186/s40163-023-00190-7","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2023/6/13 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"CRIMINOLOGY & PENOLOGY","Score":null,"Total":0}
Domestic abuse in the Covid-19 pandemic: measures designed to overcome common limitations of trend measurement.
Research on pandemic domestic abuse trends has produced inconsistent findings reflecting differences in definitions, data and method. This study analyses 43,488 domestic abuse crimes recorded by a UK police force. Metrics and analytic approaches are tailored to address key methodological issues in three key ways. First, it was hypothesised that reporting rates changed during lockdown, so natural language processing was used to interrogate untapped free-text information in police records to develop a novel indicator of change in reporting. Second, it was hypothesised that abuse would change differentially for those cohabiting (due to physical proximity) compared to non-cohabitees, which was assessed via a proxy measure. Third, the analytic approaches used were change-point analysis and anomaly detection: these are more independent than regression analysis for present purposes in gauging the timing and duration of significant change. However, the main findings were largely contrary to expectation: (1) domestic abuse did not increase during the first national lockdown in early 2020 but increased across a prolonged post-lockdown period, (2) the post-lockdown increase did not reflect change in reporting by victims, and; (3) the proportion of abuse between cohabiting partners, at around 40 percent of the total, did not increase significantly during or after the lockdown. The implications of these unanticipated findings are discussed.
Supplementary information: The online version contains supplementary material available at 10.1186/s40163-023-00190-7.
期刊介绍:
Crime Science is an international, interdisciplinary, peer-reviewed journal with an applied focus. The journal''s main focus is on research articles and systematic reviews that reflect the growing cooperation among a variety of fields, including environmental criminology, economics, engineering, geography, public health, psychology, statistics and urban planning, on improving the detection, prevention and understanding of crime and disorder. Crime Science will publish theoretical articles that are relevant to the field, for example, approaches that integrate theories from different disciplines. The goal of the journal is to broaden the scientific base for the understanding, analysis and control of crime and disorder. It is aimed at researchers, practitioners and policy-makers with an interest in crime reduction. It will also publish short contributions on timely topics including crime patterns, technological advances for detection and prevention, and analytical techniques, and on the crime reduction applications of research from a wide range of fields. Crime Science publishes research articles, systematic reviews, short contributions and theoretical articles. While Crime Science uses the APA reference style, the journal welcomes submissions using alternative reference styles on a case-by-case basis.