The Effects of Life Domains on Cyberbullying and Bullying: Testing the Generalizability of Agnew’s Integrated General Theory

2018 ◽  
Vol 65 (6) ◽  
pp. 772-800 ◽  
Author(s):  
Jaeyong Choi ◽  
Nathan E. Kruis
Keyword(s):  
General Theory ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Negative Binomial Regression Model ◽  
Life Domains ◽  
General Theory Of Crime ◽  
Mixed Support ◽  
Binomial Regression ◽  
Theory Of Crime ◽  
Crime And Delinquency

In 2005, Robert Agnew published his book Why Criminals Offend in which he synthesized an array of theoretical predictors of crime and delinquency into a parsimonious integrated general theory. He argued that delinquency is influenced by mechanisms found in five distinct life domains: self, family, peer, school, and work. Using longitudinal data from South Korea, the current research tested the generalizability of Agnew’s theory by applying it to bullying and cyberbullying. Results from a negative binomial regression model provided mixed support for Agnew’s theory as a general theory of crime. The significant effects of life domains were found to differ across types of bullying.

The Impact of Life Domains on Developmental Trajectories of Peer Delinquency among Korean Adolescents: A Partial Test of Agnew’s General Theory of Crime and Delinquency with a Group-Based Trajectory Modeling Approach

2021 ◽  
pp. 0306624X2110163
Author(s):  
Sujung Cho ◽  
Brett Lacey
Keyword(s):  
General Theory ◽  
Early Onset ◽  
The Self ◽  
Life Domains ◽  
General Theory Of Crime ◽  
Peer Delinquency ◽  
Korean Adolescents ◽  
Theory Of Crime ◽  
Crime And Delinquency ◽  
Trajectory Group

Agnew introduced a new integrated theory; the General Theory of Crime and Delinquency, in which he attempted to corral the most influential predictors of criminal behavior into more parsimonious propositions of multiple life domains—self, family, peer, school, and work—as well as constraints against crime and motivations for it. This study presents a partial test of the theory using longitudinal data of 2,351 Korean adolescents. A group-based modeling approach (latent class growth analysis) was run to examine direct effects of life domains on peer delinquency as well as mediating effects of constraints and motivation on their relationships. The study identified three subgroups: early onset/decreasing (3.2%), moderate (12.4%), and low/none (84.4%). The findings revealed that the self and peer domains exhibited a positive impact on the early onset/decreasing trajectory group compared to the low/none group with the constraint exhibiting a negative impact. The moderate trajectory group demonstrated that the self-domain was significant but was not rendered insignificant after controlling for constraints and motivations. The study provided moderate support for life domains within Agnew’s new theory for peer delinquency in nonwestern countries.

scholarly journals Contemporaneous and Lagged Effects of Life Domains and Substance Use: A Test of Agnew's General Theory of Crime and Delinquency

2014 ◽  
Vol 2014 ◽  
pp. 1-20 ◽  
Author(s):  
Fawn T. Ngo ◽  
Raymond Paternoster
Keyword(s):  
Substance Use ◽  
General Theory ◽  
Theoretical Perspective ◽  
Life Domain ◽  
The Self ◽  
Life Domains ◽  
General Theory Of Crime ◽  
Theory Of Crime ◽  
Lagged Effects ◽  
Crime And Delinquency

This study presents a partial test of Agnew’s general theory of crime and delinquency. Relying on a sample of adolescents and employing measures of the self, family, school, and peers domains, this study examines the contemporaneous and lagged effects of these four life domains on the likelihood of consuming alcohol and using marijuana. This study also assesses the contemporaneous and lagged effects of the life domain variables on themselves and on one another. Overall, the results lend support for Agnew’s general theory. The results also reveal several notable puzzles and underscore the complexity of this potentially important contemporary theoretical perspective.

Life domains and crime: A test of Agnew's general theory of crime and delinquency

2011 ◽  
Vol 39 (4) ◽  
pp. 302-311 ◽  
Author(s):  
Fawn T. Ngo ◽  
Raymond Paternoster ◽  
Francis T. Cullen ◽  
Doris Layton Mackenzie
Keyword(s):  
General Theory ◽  
Life Domains ◽  
General Theory Of Crime ◽  
Theory Of Crime ◽  
Crime And Delinquency

scholarly journals Association between fatality rate of COVID-19 and selenium deficiency in China

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Hai-Yang Zhang ◽  
An-Ran Zhang ◽  
Qing-Bin Lu ◽  
Xiao-Ai Zhang ◽  
Zhi-Jie Zhang ◽  
...  
Keyword(s):  
Negative Binomial ◽  
Viral Infections ◽  
Case Fatality ◽  
Selenium Deficiency ◽  
Negative Binomial Regression ◽  
Negative Binomial Regression Model ◽  
Fatality Rate ◽  
Selenium Content ◽  
Individual Level ◽  
Binomial Regression

Abstract Background COVID-19 has impacted populations around the world, with the fatality rate varying dramatically across countries. Selenium, as one of the important micronutrients implicated in viral infections, was suggested to play roles. Methods An ecological study was performed to assess the association between the COVID-19 related fatality and the selenium content both from crops and topsoil, in China. Results Totally, 14,045 COVID-19 cases were reported from 147 cities during 8 December 2019–13 December 2020 were included. Based on selenium content in crops, the case fatality rates (CFRs) gradually increased from 1.17% in non-selenium-deficient areas, to 1.28% in moderate-selenium-deficient areas, and further to 3.16% in severe-selenium-deficient areas (P = 0.002). Based on selenium content in topsoil, the CFRs gradually increased from 0.76% in non-selenium-deficient areas, to 1.70% in moderate-selenium-deficient areas, and further to 1.85% in severe-selenium-deficient areas (P < 0.001). The zero-inflated negative binomial regression model showed a significantly higher fatality risk in cities with severe-selenium-deficient selenium content in crops than non-selenium-deficient cities, with incidence rate ratio (IRR) of 3.88 (95% CIs: 1.21–12.52), which was further confirmed by regression fitting the association between CFR of COVID-19 and selenium content in topsoil, with the IRR of 2.38 (95% CIs: 1.14–4.98) for moderate-selenium-deficient cities and 3.06 (1.49–6.27) for severe-selenium-deficient cities. Conclusions Regional selenium deficiency might be related to an increased CFR of COVID-19. Future studies are needed to explore the associations between selenium status and disease outcome at individual-level.

scholarly journals Statistical models for analyzing count data: predictors of length of stay among HIV patients in Portugal using a multilevel model

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Ahmed Nabil Shaaban ◽  
Bárbara Peleteiro ◽  
Maria Rosario O. Martins
Keyword(s):  
Length Of Stay ◽  
Regression Model ◽  
Random Effects ◽  
Count Data ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Comprehensive Approach ◽  
Negative Binomial Regression Model ◽  
Hiv Patients ◽  
Binomial Regression

Abstract Background This study offers a comprehensive approach to precisely analyze the complexly distributed length of stay among HIV admissions in Portugal. Objective To provide an illustration of statistical techniques for analysing count data using longitudinal predictors of length of stay among HIV hospitalizations in Portugal. Method Registered discharges in the Portuguese National Health Service (NHS) facilities Between January 2009 and December 2017, a total of 26,505 classified under Major Diagnostic Category (MDC) created for patients with HIV infection, with HIV/AIDS as a main or secondary cause of admission, were used to predict length of stay among HIV hospitalizations in Portugal. Several strategies were applied to select the best count fit model that includes the Poisson regression model, zero-inflated Poisson, the negative binomial regression model, and zero-inflated negative binomial regression model. A random hospital effects term has been incorporated into the negative binomial model to examine the dependence between observations within the same hospital. A multivariable analysis has been performed to assess the effect of covariates on length of stay. Results The median length of stay in our study was 11 days (interquartile range: 6–22). Statistical comparisons among the count models revealed that the random-effects negative binomial models provided the best fit with observed data. Admissions among males or admissions associated with TB infection, pneumocystis, cytomegalovirus, candidiasis, toxoplasmosis, or mycobacterium disease exhibit a highly significant increase in length of stay. Perfect trends were observed in which a higher number of diagnoses or procedures lead to significantly higher length of stay. The random-effects term included in our model and refers to unexplained factors specific to each hospital revealed obvious differences in quality among the hospitals included in our study. Conclusions This study provides a comprehensive approach to address unique problems associated with the prediction of length of stay among HIV patients in Portugal.

Evaluation of Strategies to Mitigate Culvert-Involved Crashes

2021 ◽  
pp. 036119812199207
Author(s):  
Hitesh Chawla ◽  
Megat-Usamah Megat-Johari ◽  
Peter T. Savolainen ◽  
Christopher M. Day
Keyword(s):  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Cost Effective ◽  
Negative Binomial Regression Model ◽  
Promising Alternative ◽  
Roadside Safety ◽  
Adverse Conditions ◽  
Traffic Characteristics ◽  
Annual Average Daily Traffic ◽  
Binomial Regression

The objectives of this study were to assess the in-service safety performance of roadside culverts and evaluate the potential impacts of installing various safety treatments to mitigate the severity of culvert-involved crashes. Such crashes were identified using standard fields on police crash report forms, as well as through a review of pertinent keywords from the narrative section of these forms. These crashes were then linked to the nearest cross-drainage culvert, which was associated with the nearest road segment. A negative binomial regression model was then estimated to discern how the risk of culvert-involved crashes varied as a function of annual average daily traffic, speed limit, number of travel lanes, and culvert size and offset. The second stage of the analysis involved the use of the Roadside Safety Analysis Program to estimate the expected crash costs associated with various design contexts. A series of scenarios were evaluated, culminating in guidance as to the most cost-effective treatments for different combinations of roadway geometric and traffic characteristics. The results of this study provide an empirical model that can be used to predict the risk of culvert-involved crashes under various scenarios. The findings also suggest that the installation of safety grates on culvert openings provides a promising alternative for most of the cases where the culvert is located within the clear zone. In general, a guardrail is recommended when adverse conditions are present or when other treatments are not feasible at a specific location.

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