An Exploration of the Relationship between PBIS and Discipline Outcomes for Students With Disabilities

2021 ◽  
pp. 074193252110634
Author(s):  
Brandi Simonsen ◽  
Jennifer Freeman ◽  
Anthony J. Gambino ◽  
Sandra Sears ◽  
Katherine Meyer ◽  
...  
Keyword(s):  
Students With Disabilities ◽  
Behavioral Interventions ◽  
National Study ◽  
Data Sets ◽  
Data Set ◽  
Beneficial Effects ◽  
Positive Behavioral Interventions ◽  
Rigorous Research ◽  
Tier 1 ◽  
The Relationship

To support all students, including students with disabilities, many schools have adopted a positive behavioral interventions and supports (PBIS) framework. Although rigorous research documents the beneficial effects of Tier 1 PBIS for all students and emerging research extends these findings to students with disabilities, there has not been a national study focused on PBIS and discipline outcomes for students with disabilities. In this exploratory study, we combine existing national data sets to explore the relationship between (a) known PBIS exposure (i.e., being in the PBIS data set) and fidelity (i.e., meeting the criterion on an established fidelity measure of Tier 1 PBIS) and (b) exclusionary discipline for students with disabilities. Using two-part path analysis, we document that PBIS may be associated with decreased use of suspension; however, findings are less consistent for other discipline outcomes. This study highlights the critical need for more accurate data on discipline outcomes and further research on effective intervention.

Optimal Timing for Launching Installation of Tier 2 and 3 Systems of School-Wide Positive Behavioral Interventions and Supports

2021 ◽  
pp. 109830072199608
Author(s):  
Angus Kittelman ◽  
Sterett H. Mercer ◽  
Kent McIntosh ◽  
Robert Hoselton
Keyword(s):  
Longitudinal Study ◽  
Behavioral Interventions ◽  
Structural Equation ◽  
Equation Modeling ◽  
Optimal Timing ◽  
First Year ◽  
Tier 2 ◽  
Positive Behavioral Interventions ◽  
Tier 1 ◽  
Tier 3

The purpose of this longitudinal study was to examine patterns in implementation of Tier 2 and 3 school-wide positive behavioral interventions and supports (SWPBIS) systems to identify timings of installation that led to higher implementation of advanced tiers. Extant data from 776 schools in 27 states reporting on the first 3 years of Tier 2 implementation and 359 schools in 23 states reporting on the first year of Tier 3 implementation were analyzed. Using structural equation modeling, we found that higher Tier 1 implementation predicted subsequent Tier 2 and Tier 3 implementation. In addition, waiting 2 or 3 years after initial Tier 1 implementation to launch Tier 2 systems predicted higher initial Tier 2 implementation (compared with implementing the next year). Finally, we found that launching Tier 3 systems after Tier 2 systems, compared with launching both tiers simultaneously, predicted higher Tier 2 implementation in the second and third year, so long as Tier 3 systems were launched within 3 years of Tier 2 systems. These findings provide empirical guidance for when to launch Tier 2 and 3 systems; however, we emphasize that delays in launching advanced systems should not equate to delays in more intensive supports for students.

PSVI-8 Meta-regression Analysis to Determine the Relationship Between Growing Pig Body Weight and Variation

2021 ◽  
Vol 99 (Supplement_1) ◽  
pp. 218-219
Author(s):  
Andres Fernando T Russi ◽  
Mike D Tokach ◽  
Jason C Woodworth ◽  
Joel M DeRouchey ◽  
Robert D Goodband ◽  
...  
Keyword(s):  
Body Weight ◽  
Regression Analysis ◽  
Sample Size ◽  
Polynomial Regression ◽  
Data Sets ◽  
Regression Equations ◽  
Prediction Equations ◽  
Data Set ◽  
Rate Of Increase ◽  
The Relationship

Abstract The swine industry has been constantly evolving to select animals with improved performance traits and to minimize variation in body weight (BW) in order to meet packer specifications. Therefore, understanding variation presents an opportunity for producers to find strategies that could help reduce, manage, or deal with variation of pigs in a barn. A systematic review and meta-analysis was conducted by collecting data from multiple studies and available data sets in order to develop prediction equations for coefficient of variation (CV) and standard deviation (SD) as a function of BW. Information regarding BW variation from 16 papers was recorded to provide approximately 204 data points. Together, these data included 117,268 individually weighed pigs with a sample size that ranged from 104 to 4,108 pigs. A random-effects model with study used as a random effect was developed. Observations were weighted using sample size as an estimate for precision on the analysis, where larger data sets accounted for increased accuracy in the model. Regression equations were developed using the nlme package of R to determine the relationship between BW and its variation. Polynomial regression analysis was conducted separately for each variation measurement. When CV was reported in the data set, SD was calculated and vice versa. The resulting prediction equations were: CV (%) = 20.04 – 0.135 × (BW) + 0.00043 × (BW)2, R2=0.79; SD = 0.41 + 0.150 × (BW) - 0.00041 × (BW)2, R2 = 0.95. These equations suggest that there is evidence for a decreasing quadratic relationship between mean CV of a population and BW of pigs whereby the rate of decrease is smaller as mean pig BW increases from birth to market. Conversely, the rate of increase of SD of a population of pigs is smaller as mean pig BW increases from birth to market.

Utilizing Positive Behavioral Interventions and Supports to Reinforce Therapeutic Practices in the Schools

2015 ◽  
Vol 16 (1) ◽  
pp. 4-10 ◽  
Author(s):  
Lyndsey Zurawski
Keyword(s):  
Students With Disabilities ◽  
Behavioral Interventions ◽  
Classroom Setting ◽  
Behavior Interventions ◽  
Behavioral Strategies ◽  
Speech Language Pathologists ◽  
Positive Behavior Interventions ◽  
Positive Behavioral Interventions ◽  
Therapeutic Services ◽  
Support Students

Speech-language pathologists (SLPs) are faced with providing therapeutic services to students with a variety of disorders. Students with disorders such as speech and language impairments, autism, and intellectual disabilities can demonstrate behaviors within the classroom setting. Speech-language pathologists are a part of a collaborative team responsible for providing supports or interventions. Often, SLPs are unaware of behavioral strategies/interventions that correlate to school-wide expectations. This article provides examples of positive behavior interventions and supports (PBIS) that can be utilized to support students with disabilities in and out of the classroom.

Disparities Across Time: Exploring Absenteeism Patterns between Cohorts of Students with Disabilities

2020 ◽  
Vol 122 (11) ◽  
pp. 1-32
Author(s):  
Michael A. Gottfried ◽  
Vi-Nhuan Le ◽  
J. Jacob Kirksey
Keyword(s):  
Students With Disabilities ◽  
Social Needs ◽  
Data Sets ◽  
Chronic Absenteeism ◽  
Data Set ◽  
Full Day Kindergarten ◽  
Effective Interventions ◽  
Nationally Representative ◽  
Single Data ◽  
Over Time

Background It is of grave concern that kindergartners are missing more school than students in any other year of elementary school; therefore, documenting which students are absent and for how long is of upmost importance. Yet, doing so for students with disabilities (SWDs) has received little attention. This study addresses this gap by examining two cohorts of SWDs, separated by more than a decade, to document changes in attendance patterns. Research Questions First, for SWDs, has the number of school days missed or chronic absenteeism rates changed over time? Second, how are changes in the number of school days missed and chronic absenteeism rates related to changes in academic emphasis, presence of teacher aides, SWD-specific teacher training, and preschool participation? Subjects This study uses data from the Early Childhood Longitudinal Study (ECLS), a nationally representative data set of children in kindergarten. We rely on both ECLS data sets— the kindergarten classes of 1998–1999 and 2010–2011. Measures were identical in both data sets, making it feasible to compare children across the two cohorts. Given identical measures, we combined the data sets into a single data set with an indicator for being in the older cohort. Research Design This study examined two sets of outcomes: The first was number of days absent, and the second was likelihood of being chronically absent. These outcomes were regressed on a measure for being in the older cohort (our key measure for changes over time) and numerous control variables. The error term was clustered by classroom. Findings We found that SWDs are absent more often now than they were a decade earlier, and this growth in absenteeism was larger than what students without disabilities experienced. Absenteeism among SWDs was higher for those enrolled in full-day kindergarten, although having attended center-based care mitigates this disparity over time. Implications are discussed. Conclusions Our study calls for additional attention and supports to combat the increasing rates of absenteeism for SWDs over time. Understanding contextual shifts and trends in rates of absenteeism for SWDs in kindergarten is pertinent to crafting effective interventions and research geared toward supporting the academic and social needs of these students.

scholarly journals Children with 5′-end NF1 gene mutations are more likely to have glioma

2017 ◽  
Vol 3 (5) ◽  
pp. e192 ◽  
Author(s):  
Corina Anastasaki ◽  
Stephanie M. Morris ◽  
Feng Gao ◽  
David H. Gutmann
Keyword(s):  
Gene Mutation ◽  
Statistical Significance ◽  
Gene Mutations ◽  
Neurofibromatosis Type ◽  
Published Data ◽  
Data Sets ◽  
Nonsense Mutations ◽  
Data Set ◽  
Nf1 Gene ◽  
The Relationship

Objective:To ascertain the relationship between the germline NF1 gene mutation and glioma development in patients with neurofibromatosis type 1 (NF1).Methods:The relationship between the type and location of the germline NF1 mutation and the presence of a glioma was analyzed in 37 participants with NF1 from one institution (Washington University School of Medicine [WUSM]) with a clinical diagnosis of NF1. Odds ratios (ORs) were calculated using both unadjusted and weighted analyses of this data set in combination with 4 previously published data sets.Results:While no statistical significance was observed between the location and type of the NF1 mutation and glioma in the WUSM cohort, power calculations revealed that a sample size of 307 participants would be required to determine the predictive value of the position or type of the NF1 gene mutation. Combining our data set with 4 previously published data sets (n = 310), children with glioma were found to be more likely to harbor 5′-end gene mutations (OR = 2; p = 0.006). Moreover, while not clinically predictive due to insufficient sensitivity and specificity, this association with glioma was stronger for participants with 5′-end truncating (OR = 2.32; p = 0.005) or 5′-end nonsense (OR = 3.93; p = 0.005) mutations relative to those without glioma.Conclusions:Individuals with NF1 and glioma are more likely to harbor nonsense mutations in the 5′ end of the NF1 gene, suggesting that the NF1 mutation may be one predictive factor for glioma in this at-risk population.

scholarly journals Involvement and Participation of Students With Severe Disabilities in SWPBIS

2018 ◽  
Vol 52 (3) ◽  
pp. 131-141
Author(s):  
Jennifer A. Kurth ◽  
Alison L. Zagona
Keyword(s):  
General Education ◽  
Student Outcomes ◽  
Behavioral Interventions ◽  
Severe Disabilities ◽  
General Educators ◽  
Support Needs ◽  
Positive Behavioral Interventions ◽  
Tier 1 ◽  
Tiered System ◽  
Students With Severe Disabilities

With more schools implementing Schoolwide Positive Behavioral Interventions and Supports (SWPBIS) and achieving valued student outcomes associated with these efforts, the inclusion of students with extensive and pervasive support needs (i.e., “severe” disabilities) in this tiered system must be considered. These students remain programmatically and physically separated from general education instruction and activities. Given that SWPBIS is implemented in general education settings and it is designed to support all students, the purpose of this study was to investigate SWPBIS coaches’ perceptions of the involvement of students with extensive support needs in SWPBIS processes and procedures within one state. Findings suggest the coaches believe that students with extensive support needs are physically and programmatically separated from Tier 1 SWPBIS instruction and activities, with few general educators expressing participation in facilitating their involvement. Implications and recommendations for these findings are provided.

Determination of Optimal Clusters Using a Genetic Algorithm

2008 ◽  
pp. 98-117 ◽  
Author(s):  
Tushar ◽  
Tushar ◽  
Shibendu Shekhar Roy ◽  
Dilip Kumar Pratihar
Keyword(s):  
Genetic Algorithm ◽  
Threshold Value ◽  
Data Sets ◽  
Self Organizing Map ◽  
Data Set ◽  
Fcm Algorithm ◽  
Data Points ◽  
The Relationship

Clustering is a potential tool of data mining. A clustering method analyzes the pattern of a data set and groups the data into several clusters based on the similarity among themselves. Clusters may be either crisp or fuzzy in nature. The present chapter deals with clustering of some data sets using Fuzzy C-Means (FCM) algorithm and Entropy-based Fuzzy Clustering (EFC) algorithm. In FCM algorithm, the nature and quality of clusters depend on the pre-defined number of clusters, level of cluster fuzziness and a threshold value utilized for obtaining the number of outliers (if any). On the other hand, the quality of clusters obtained by the EFC algorithm is dependent on a constant used to establish the relationship between the distance and similarity of two data points, a threshold value of similarity and another threshold value used for determining the number of outliers. The clusters should ideally be distinct and at the same time compact in nature. Moreover, the number of outliers should be as minimum as possible. Thus, the above problem may be posed as an optimization problem, which will be solved using a Genetic Algorithm (GA). The best set of multi-dimensional clusters will be mapped into 2-D for visualization using a Self-Organizing Map (SOM).

Promoting the Accessibility of SWPBIS for Students With Severe Disabilities

2017 ◽  
Vol 20 (2) ◽  
pp. 113-123 ◽  
Author(s):  
Sheldon L. Loman ◽  
M. Kathleen Strickland-Cohen ◽  
Virginia L. Walker
Keyword(s):  
Special Education Teachers ◽  
Behavioral Interventions ◽  
Universal Design For Learning ◽  
Severe Disabilities ◽  
Evidence Based Practices ◽  
Call To Action ◽  
Positive Behavioral Interventions ◽  
Tier 1 ◽  
Design For Learning ◽  
Students With Severe Disabilities

This study heeds a decade-long call to action to examine the accessibility of Schoolwide Positive Behavioral Interventions and Supports (SWPBIS) for students with severe disabilities. To improve the accessibility of SWPBIS, Universal Design for Learning (UDL) and evidence-based practices were used to teach three students with severe disabilities schoolwide behavior expectations in inclusive schoolwide settings. Special education teachers from three different elementary schools adapted their campus SWPBIS Tier 1 lesson plans with additional visual supports, social narratives, and systematic instructional procedures. All participants showed improvement as evidenced by a reduction in the duration of their problem behavior in schoolwide settings. Implementing teachers found the intervention and corresponding materials to be socially valid.

The Case Law on Aversive Interventions for Students with Disabilities

1998 ◽  
Vol 65 (1) ◽  
pp. 101-123 ◽  
Author(s):  
Sharon Lohrmann-O'rourke ◽  
Perry A. Zirkel
Keyword(s):  
Students With Disabilities ◽  
Corporal Punishment ◽  
Behavioral Intervention ◽  
Electric Shock ◽  
Challenging Behavior ◽  
Behavioral Interventions ◽  
Case Law ◽  
Intervention Strategies ◽  
Positive Interventions ◽  
Positive Behavioral Interventions

Parents and professionals have increasingly rejected aversive intervention strategies that rely on their punishing effect to decrease occurrences of challenging behavior. As a result, positive behavioral intervention strategies have emerged as a viable alternative. Students with disabilities, however, continue to be at risk for exposure to aversive interventions. This article identifies legal boundaries and protections for students through a review of the case law on aversive interventions in five categories: electric shock, noxious substances, corporal punishment, restraints, and timeout. Despite the emergence of positive interventions, qualified support for the use of aversive interventions continues to exist. The article discusses IDEA amendment language supporting positive behavioral interventions and makes recommendations for continued advocacy on behalf of students with disabilities.

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