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Houchins, David E.; Jimenez, Eliseo; Langley, Nickolas; Plescow, Katelyn; Henrich, Christopher C. – Behavioral Disorders, 2021
The purpose of this article was to examine the relationships between: (1) youth and facility characteristics; and (2) youth risk and resilience factors (i.e., mental health, self-determination [SD]) in juvenile justice facilities. Extant self-report data from 205 nationally representative correctional facilities and 7,073 youth, collected as part…
Descriptors: Predictor Variables, Self Determination, Mental Health, Mental Disorders
Factors That Enhance the Quality of Relationships between Mentors and Mentees during Check & Connect
Kern, Lee; Harrison, Judith R.; Custer, Beth E.; Mehta, Paras D. – Behavioral Disorders, 2019
School engagement is an important predictor of graduation. One strategy to enhance student engagement is mentoring. Check & Connect is a structured mentoring program that has resulted in favorable outcomes for many students, including those with emotional and behavioral disorders. Effectiveness, however, depends on the quality of the…
Descriptors: Mentors, Interpersonal Relationship, Learner Engagement, Program Effectiveness
David E. Houchins; Richard G. Lambert; Christopher Henrich; Joseph Calvin Gagnon – Behavioral Disorders, 2024
A major challenge for juvenile correctional facilities (JCF) is providing literacy instruction to a transitory student population with a wide range of literacy abilities. The purpose of this study was to identify unique literacy profiles of students in long-term JCF taking into consideration their reading abilities, language abilities,…
Descriptors: Delinquency, Institutionalized Persons, Correctional Institutions, Literacy Education
Lane, Kathleen Lynne; Oakes, Wendy Peia; Swogger, Emily D.; Schatschneider, Christopher; Menzies, Holly Mariah; Sanchez, Jeremy – Behavioral Disorders, 2015
We report findings of a convergent validity study examining the internalizing subscale (SRSS-I5) of the newly adapted Student Risk Screening Scale for Internalizing and Externalizing (SRSS-IE12) with the internalizing subscale of the Teacher Report Form (TRF; Achenbach, 1991) conducted in 13 schools across three states with 195 kindergarten…
Descriptors: Screening Tests, Behavior Problems, Cutting Scores, Decision Making
Barrett, David E.; Katsiyannis, Antonis – Behavioral Disorders, 2015
Using large-sample, archival data from the state of South Carolina's juvenile justice agency, we examine the question of race differences in predictors of repeat offending for a sample of approximately 100,000 youth who had been referred for criminal offenses. Independent variables relating to background, adverse parenting, mental health,…
Descriptors: Delinquency, Archives, Juvenile Justice, Racial Differences
Lambert, Matthew C.; Epstein, Michael; Ingram, Stephanie; Simpson, Amy; Bernstein, Seth – Behavioral Disorders, 2014
Many students who exhibit behavioral and emotional problems during adolescence often show less severe problems in school in early grades. Screening for these early indicators can help educational professionals direct support to students who are more likely to benefit from increased support. The screening protocol needs to be psychometrically…
Descriptors: Emotional Problems, Behavior Problems, Adolescents, Severity (of Disability)
Alexandra L. Trout; Matthew C. Lambert; Timothy D. Nelson; Ronald W. Thompson – Behavioral Disorders, 2014
The prevalence of weight problems among youth in general and youth in out-of-home care has been well documented; however, the prevalence of obesity/overweight among youth with high-incidence disabilities in more restrictive settings, such as residential care, has not been assessed. The purpose of the present study was to evaluate the prevalence of…
Descriptors: Residential Care, Body Weight, Youth Problems, Disabilities
Lin, Yu-Chu; Morgan, Paul L.; Hillemeier, Marianne; Cook, Michael; Maczuga, Steve; Farkas, George – Behavioral Disorders, 2013
We examined three questions. First, do reading difficulties increase children's risk of behavioral difficulties? Second, do behavioral difficulties increase children's risk of reading difficulties? Third, do mathematics difficulties increase children's risk of reading or behavioral difficulties? We investigated these questions using (a) a sample…
Descriptors: Behavior Problems, Elementary School Students, At Risk Students, Reading Difficulties
Zablotsky, Benjamin; Bradshaw, Catherine P.; Anderson, Connie; Law, Paul – Behavioral Disorders, 2012
Children with developmental disabilities are at an increased risk for involvement in bullying, and children with autism spectrum disorders (ASDs) may be at particular risk because of challenges with social skills and difficulty maintaining friendships, yet there has been little empirical research on involvement in bullying among children with ASD.…
Descriptors: Prevention, Bullying, Autism, Structural Equation Models
Zhang, Dalun; Willson, Victor; Katsiyannis, Antonis; Barrett, David; Ju, Song; Wu, Jiun-Yu – Behavioral Disorders, 2010
Truancy remains a persistent concern, with serious consequences for the individual, family, and society, as truancy is often linked to academic failure, disengagement with school, school dropout, and delinquency. This study analyzed large-scale data covering multiple years of cohorts of delinquent youths born between 1981 and 1988. Truancy…
Descriptors: Truancy, Attendance Patterns, Delinquency, At Risk Students
Mattison, Richard E.; Blader, Joseph C. – Behavioral Disorders, 2013
Concern is growing over the limited academic progress in special education students with emotional and/or behavioral disorders (EBD). We know little about how academic and behavioral factors interact in these students to affect their academic functioning. Therefore, potential associations were investigated over the course of one school year for…
Descriptors: Emotional Disturbances, Behavior Disorders, Severe Disabilities, Academic Achievement

Cullinan, Douglas; And Others – Behavioral Disorders, 1984
Behaviorally disordered (N=727) and nonhandicapped (N=1116) students of three age levels were assessed for adjustment problems, using a teacher-completed checklist. Results showed that on most checklist items significantly more behaviorally disordered students experienced problems than nonhandicapped students. Among the behaviorally disordered Ss,…
Descriptors: Age Differences, Behavior Disorders, Behavior Patterns, Behavior Rating Scales

Center, David B.; Wascom, Alan M. – Behavioral Disorders, 1987
Comparison of teacher perceptions of either behaviorally disordered or socially normal students (total N=410 and ages between 8 and 15) indicated teachers perceived more prosocial behavior by normal, female, and older subjects. Teachers perceived an increase in negative social behavior for normal secondary-age students but not for behaviorally…
Descriptors: Age Differences, Behavior Disorders, Behavior Patterns, Behavior Problems
Billingsley, Glenna; Scheuermann, Brenda; Webber, Jo – Behavioral Disorders, 2009
The purpose of this study was to determine the most effective of three instructional methods for teaching mathematics to secondary students with emotional and behavioral disorders. A single-subject alternating-treatments research design was used to compare three instructional methods: direct teach, computer-assisted instruction, and a combination…
Descriptors: Emotional Disturbances, Behavior Disorders, Intelligence Quotient, Mathematics Skills

Maag, John W.; Behrens, John T. – Behavioral Disorders, 1989
The study examined the relationship between extreme levels of depressive symptomatology and age, gender, and placement label among 465 secondary-level students in special education resource programs for the seriously emotionally disturbed and learning disabled. Gender was the only significant predictor of severe depressive symptomatology, with…
Descriptors: Age Differences, Depression (Psychology), Emotional Disturbances, Incidence
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