An analysis of the tests on the prediction of the violence in school students

Studies in all languages and unpublished investigations were considered for inclusion. Detailed examination of the overall differences between individual instruments have been reported in a subset of the samples. Therefore, the magnitude of observed heterogeneity in meta-analyses of diagnostic accuracy is instead best determined by the scatter of points in the summary receiver operating characteristic plot and from the prediction ellipse.

These factors did, however, have significant positive associations with externalizing behavioral problems, which are problematic behaviors that are directed outward, such as aggression, delinquency, and hyperactivity. Interestingly, being a victim of violence as opposed to merely witnessing it did not exacerbate these negative effects.

There was some evidence that knowing violent peers was associated with lower test scores. The required analysis is a bivariate analysis of sensitivity and specificity for each study accounting for correlation between sensitivities and specificities.

Results Risk assessments were conducted on 73 samples comprising 24 participants from 13 countries, of whom The aim of the analysis was to quantify and compare these statistics as well as the error rates false positive and false negative diagnoses for each type of test.

This technique is interesting because it provides a natural control for all family measures of disadvantage both observable and unobservable. The results of the study suggested a weak relationship between community violence and academic functioning in general, but the relationship strengthened under certain circumstances such as when the children exhibited signs of emotional distress or when families had a strong moral-religious emphasis, which appeared to be an insufficient coping mechanism in the face of these problems.

Investigation of heterogeneity The standard Q and I2 statistics 61 do not account for heterogeneity explained by phenomena such as positivity threshold effects, and the numerical estimates of the random effect terms in the bivariate regression are not easily interpreted.

Aizer focused on isolating neighborhood violence from other measures of neighborhood and family disadvantage.

We obtained estimates for the area under the curve, positive predictive value, negative predictive value, number needed to detain, and number safely discharged from the individual sample estimates. The findings also differentiated between middle and high school students; middle schoolers were more likely to report in-school personal threats, while high schoolers were more likely to report various indicators of neighborhood danger.

Risk assessment tools are predominantly used in clinical situations as instruments for identifying higher risk individuals, 19 thus, we combined participants who were classified as being at moderate or high risk for future offending and compared them with those classified as low risk.

The positive predictive value is the proportion of participants classified as at risk who go on to offend, whereas the negative predictive value refers to the proportion of those classified as not at risk who do not go on to offend. Table 1 Characteristics of nine included risk assessment tools View this table: These studies often use survey data, interviewing children or their parents about their exposure to violence and then using various individual-level measures to estimate its effects.

Finally, the number safely discharged is a new performance statistic that we developed for the purposes of this review. My project differs from these studies in that I will be examining proximity to violence and the outcome of academic performance at the school level.

Methods We followed the preferred reporting items for systematic reviews and meta-analyses statement. I will need to include similar controls at the school level when I design my analysis. Instruments designed to predict violent offending performed better than those aimed at predicting sexual or general crime.

Introduction With the increasing recognition of the public health importance of violence, 1 2 the prediction of violence, or violence risk assessment, has been the subject of considerable clinical and research interest.

We requested additional data from the authors of studies and obtained data for 52 studies Furthermore, criminal justice systems in many countries have welcomed the use of risk assessment to assist sentencing and release decisions. Firstly, the summary operating point was used to estimate the summary diagnostic odds ratio and both sensitivity and specificity.With the increasing recognition of the public health importance of violence,1 2 the prediction of violence, since χ 2 tests of a meta-analysis of Violence Among Middle School and High School Students: Analysis and Implications for Prevention by Daniel Lockwood, Ph.D.

ing high rates of violence, the students in. When to Use Which Statistical Test Rachel Lovell, prediction of DV based on IV(s) • Path Analysis (AKA structural equation modeling). Start studying Chapter 11a and 11b.

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Learn vocabulary, High school and college students. A particular assessment concern in the prediction of violence is. Violence in schools: Prevalence, prediction, and evolution of school violence as well as the to and from school was unsafe. Some students were so afraid.

Individual-Level Studies of the Effects of Violence on the Academic Performance of Students

Keywords: school violence essay, school violence in vietnam essay. 1. A lot of students decline to go to school because they are scared to be attacked, insulted.

An analysis of the tests on the prediction of the violence in school students
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