Use of a Multitheoretic Model to Understand and Classify Juvenile Computer Hacking Behavior.
Criminological inquiry has identified a range of risk factors associated with juvenile delinquency. However, little research has assessed juvenile computer hacking, despite the substantial harm and opportunities for delinquent behavior online. Therefore, understanding the applicability of criminolog...
| Publicado en: | Criminal Justice & Behavior Vol. 48; no. 7; pp. 943 - 964 |
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| Autores principales: | , |
| Formato: | Artículo |
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Sage Publications Inc.
Jul2021
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=150427373&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 150427373 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 00938548 CJB jtl: Criminal Justice & Behavior issn: 00938548 maglogo: Y pubinfo: dt: Jul2021 vid: 48 iid: 7 pid: 344 pub: Sage Publications Inc. artinfo: ui: 150427373 10.1177/0093854820969754 ppf: 943 ppct: 21 formats: tig: atl: Use of a Multitheoretic Model to Understand and Classify Juvenile Computer Hacking Behavior. aug: au: Fox, Bryanna Holt, Thomas J. affil: University of South Florida Michigan State University su: Forecasting Juvenile delinquency Juvenile offenders Delinquent behavior Computer hacking Logistic regression analysis Computer hackers sug: subj: Forecasting Juvenile delinquency Juvenile offenders Delinquent behavior Computer hacking Logistic regression analysis Computer hackers keyword: cybercrime hacking juvenile justice latent class analysis prevention cybercrime hacking juvenile justice latent class analysis prevention ab: Criminological inquiry has identified a range of risk factors associated with juvenile delinquency. However, little research has assessed juvenile computer hacking, despite the substantial harm and opportunities for delinquent behavior online. Therefore, understanding the applicability of criminological risk factors among a cross-national sample of juvenile hackers is important from a theoretical and applied standpoint. This study aimed to address this gap using a logistic regression and latent class analysis (LCA) of risk factors associated with self-reported hacking behavior in a sample of more than 60,000 juveniles from around the globe. Results demonstrated support for individual- and structural-level predictors of delinquency, although distinct risk factors for hacking among three subtypes are identified in the LCA. This study examines criminological risk factors for juvenile hacking in a cross-national sample and provides insight into the distinct risk factors of hacking, so more tailored prevention and treatment modalities can be developed. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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