Juvenile Institutional Misconduct: Examining the Role of Educational Attainment and Academic Achievement

2020 ◽  
Vol 66 (5) ◽  
pp. 663-686
Author(s):  
Ronda Shepherd Engstrom ◽  
Daniel Scott
Keyword(s):  
High School ◽  
Academic Achievement ◽  
Juvenile Offenders ◽  
Educational Attainment ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Future Research ◽  
Institutional Misconduct ◽  
Binomial Regression ◽  
Educational Variables

Identifying risk factors of institutional misconduct among juvenile offenders is important in curbing costs and consequences of these infractions. Research shows low educational attainment and poor academic achievement are consistently related to delinquency and crime. Yet, no research has examined whether these educational variables are associated with institutional misconduct among juveniles. Official records and interviews yielded information on the educational characteristics and institutional misconduct of 349 juvenile prisoners in a California facility. Negative binomial regression analysis was employed to examine hypothesized relationships. Results indicate that graduating high school significantly predicts institutional misconduct. Implications for juvenile corrections policies, including the importance of assisting juvenile detainees in obtaining their high school diploma, and directions for future research are provided.

scholarly journals Is area deprivation associated with greater impacts of COVID-19 in care homes across England? A preliminary analysis of COVID-19 outbreaks and deaths

2021 ◽  
pp. jech-2020-215039 ◽  
Author(s):  
Anders Malthe Bach-Mortensen ◽  
Michelle Degli Esposti
Keyword(s):  
Negative Binomial ◽  
Care Home ◽  
Negative Binomial Regression ◽  
Population Characteristics ◽  
Care Homes ◽  
Future Research ◽  
Area Deprivation ◽  
Binomial Regression ◽  
Index Of Multiple Deprivation

IntroductionThe COVID-19 pandemic has disproportionately impacted care homes and vulnerable populations, exacerbating existing health inequalities. However, the role of area deprivation in shaping the impacts of COVID-19 in care homes is poorly understood. We examine whether area deprivation is linked to higher rates of COVID-19 outbreaks and deaths among care home residents across upper tier local authorities in England (n=149).MethodsWe constructed a novel dataset from publicly available data. Using negative binomial regression models, we analysed the associations between area deprivation (Income Deprivation Affecting Older People Index (IDAOPI) and Index of Multiple Deprivation (IMD) extent) as the exposure and COVID-19 outbreaks, COVID-19-related deaths and all-cause deaths among care home residents as three separate outcomes—adjusting for population characteristics (size, age composition, ethnicity).ResultsCOVID-19 outbreaks in care homes did not vary by area deprivation. However, COVID-19-related deaths were more common in the most deprived quartiles of IDAOPI (incidence rate ratio (IRR): 1.23, 95% CI 1.04 to 1.47) and IMD extent (IRR: 1.16, 95% CI 1.00 to 1.34), compared with the least deprived quartiles.DiscussionThese findings suggest that area deprivation is a key risk factor in COVID-19 deaths among care home residents. Future research should look to replicate these results when more complete data become available.

Latent Profile Analysis of Personality Dimensions Among Juvenile Offenders: Relevance for Predicting Offending Seriousness

2020 ◽  
pp. 001112872092892
Author(s):  
Thomas Wojciechowski
Keyword(s):  
Juvenile Offenders ◽  
Latent Profile Analysis ◽  
Negative Binomial ◽  
Profile Analysis ◽  
Negative Binomial Regression ◽  
Personality Profiles ◽  
Personality Dimensions ◽  
Binomial Regression ◽  
Pathways To Desistance ◽  
Latent Profile

There is a burgeoning base of research identifying personality as a predictor of offending. However, research has focused on personality dimensions, rather than full personality profiles as predictors. The present study utilized the Pathways to Desistance data to examine the relationship between personality profiles and offending. This sample comprised 1,354 juvenile offenders followed during the study period of 2000 to 2010. Latent profile analysis was used to identify patterns across dimensions to elucidate personality profiles. Negative binomial regression was used to examine profiles as predictors of offending. Results indicated that a two-profile model fit the data. Participants assigned to the Undercontrolled profile (high in neuroticism and low in all other dimensions) engaged in more serious offending than the Resilient profile.

The Cycle of Violence Revisited: Childhood Victimization, Resilience, and Future Violence

2016 ◽  
Vol 34 (6) ◽  
pp. 1261-1286 ◽  
Author(s):  
Kevin A. Wright ◽  
Jillian J. Turanovic ◽  
Eryn N. O’Neal ◽  
Stephanie J. Morse ◽  
Evan T. Booth
Keyword(s):  
Protective Factors ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Future Research ◽  
Cycle Of Violence ◽  
Childhood Victimization ◽  
Adult Health ◽  
Violent Offending ◽  
Binomial Regression ◽  
The Individual

The individual and social protective factors that help break the cycle of violence are examined. Specifically, this study investigates (a) the individual and social protective factors that reduce violent offending among previously victimized children, and (b) whether certain protective factors are more or less important depending on the type and frequency of childhood victimization experienced. Data on young adults from Wave III of the National Longitudinal Study of Adolescent to Adult Health are used ( N = 13,116). Negative binomial regression models are estimated to examine the protective factors that promote resiliency to violent offending among individuals who reported being physically and sexually victimized as children. Results indicate that a number of individual and social protective factors reduce violent offending in young adulthood. With a few exceptions, these factors are specific to the type, frequency, and comorbidity of abuse experienced. The results suggest a number of promising approaches to break the cycle of violence among previously victimized children. Future research should move beyond explaining the cycle of violence to examine how the cycle may be broken.

Hate Groups and Muslim Population Changes in the Fifty States: Does the Presence of Muslims Encourage Hate Group Formation?

2018 ◽  
Vol 25 (2) ◽  
pp. 317-332
Author(s):  
Daniel Hummel
Keyword(s):  
Negative Binomial ◽  
Group Formation ◽  
Negative Binomial Regression ◽  
The United States ◽  
Future Research ◽  
Group Status ◽  
Hate Groups ◽  
Muslim Population ◽  
Binomial Regression ◽  
Positive Correlations

The size of the Muslim population in the United States is growing, while the number of hate groups also continues to increase across the states. Based on the social dominance theory and group threat theory, there may be a link between these two dynamics as social dominators become concerned about their group status, i.e. white Christian males. This potential relationship is explored in this article. Although there were significant positive correlations between the number of hate groups and the size of the Muslim population, a panelled negative binomial regression with a number of relevant control variables found that there was not a significant relationship between these variables at the 0.05 probability level. The article further explores these findings and future research in this area.

School Physical Education Policies and Practices and Student Physical Education Attendance

2020 ◽  
Vol 31 (2) ◽  
Author(s):  
Jinsook Kim ◽  
Lynn Herrmann
Keyword(s):  
High School ◽  
High School Students ◽  
Physical Education ◽  
Negative Binomial ◽  
State Level ◽  
Negative Binomial Regression ◽  
Education Policies ◽  
School Students ◽  
Binomial Regression ◽  
Using Data

This study examined how state-level measures of school-reported physical education (PE) provisions and exemption practices correlated to student-reported PE attendance among high school students, using data (n=50077) from state-representative schools and students from multiple states. Negative binomial regression was used to examine the association of the frequency of PE attendance with schools’ PE provision and exemption, controlling for student characteristics. The percentage of schools offering PE for all grades was positively associated with PE attendance more strongly among girls and higher-grade students. Permissive exemption policies were not associated with PE attendance. Offering PE for all grades may enhance PE attendance.

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.

scholarly journals Association between breakfast skipping and metabolic outcomes by sex, age, and work status stratification

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Jun Heo ◽  
Won-Jun Choi ◽  
Seunghon Ham ◽  
Seong-Kyu Kang ◽  
Wanhyung Lee
Keyword(s):  
Regression Analysis ◽  
Negative Binomial ◽  
Metabolic Diseases ◽  
Young Male ◽  
Negative Binomial Regression ◽  
Final Analysis ◽  
Work Status ◽  
Breakfast Skipping ◽  
Metabolic Outcomes ◽  
Binomial Regression

Abstract Background The association between breakfast skipping and abnormal metabolic outcomes remains controversial. A comprehensive study with various stratified data is required. Objective The aim of this study was to investigate the relationship between abnormal metabolic outcomes and breakfast skipping by sex, age, and work status stratification. Methods We used data from the Korea National Health and Nutrition Examination Surveys from 2013 to 2018. A total of 21,193 (9022 men and 12,171 women) participants were included in the final analysis. The risk of metabolic outcomes linked to breakfast skipping was estimated using the negative binomial regression analysis by sex, work status, and age stratification. Results A total of 11,952 (56.4%) participants consumed breakfast regularly. The prevalence of abnormal metabolic outcomes was higher among those with irregular breakfast consumption habits. Among young male workers, negative binomial regression analysis showed that irregular breakfast eaters had a higher risk of abnormal metabolic outcomes, after adjusting for covariates (odds ratio, 1.15; 95% confidence interval, 1.03–1.27). Conclusions The risk of abnormal metabolic outcomes was significant in young men in the working population. Further studies are required to understand the association of specific working conditions (working hours or shift work) with breakfast intake status and the risk of metabolic diseases.

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