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We examined special education classifications among students aged 3–21 in North Carolina public schools, highlighting autism spectrum disorder (ASD) and intellectual disability (ID). Results revealed variability by county in ASD and ID prevalence, and in county-level ratios of ID vs. ASD classifications. Sociodemographic characteristics predicted proportion of ASD or ID within a county; correlations showed an association between race and ID, but not ASD. County’s median household income predicted proportion of students classified as ASD and ID (opposite directions), controlling for number of students and gender. Variability was unlikely related to biological incidence, and more likely related to district/school practices, or differences in resources. Disparities warrant further examination to ensure that North Carolina’s youth with disabilities access necessary, appropriate resources.

Poorer outcomes for youth labeled with learning disabilities (LDs) are often attributed to the student's own deficiencies or cumulative disadvantage; but the more troubling possibility is that special education placement limits rather than expands these students' opportunities. Labeling theory partially attributes the poorer outcomes of labeled persons to stigma related to labels. This study uses data on approximately 11,740 adolescents and their schools from the Education Longitudinal Survey of 2002 to determine if stigma influences teachers' and parents' educational expectations for students labeled with LDs and labeled adolescents' expectations for themselves. Supporting the predictions of labeling theory, teachers and parents are more likely to perceive disabilities in, and hold lower educational expectations for labeled adolescents than for similarly achieving and behaving adolescents not labeled with disabilities. The negative effect of being labeled with LDs on adolescents' educational expectations is partially mechanized through parents' and particularly teachers' lower expectations.

We estimated the proportion of the nation’s public school districts that have high school grades in which random drug testing is conducted. We collected data in spring 2005 from 1343 drug prevention coordinators in a nationally representative sample of school districts with schools that have high school grades; of these districts, 14% conducted random drug testing. Almost all districts randomly tested athletes, and 65% randomly tested other students engaged in extracurricular activities; 28% randomly tested all students, exceeding the current sanction of the US Supreme Court.

This study used mixed-effects logistic regression to examine undergraduates’ ( N  = 142) evaluations and reasoning about scenarios involving disability-based exclusion. Scenarios varied by disability [autism spectrum disorder (ASD) versus learning disability (LD)], the context of exclusion (classroom versus social), and whether or not a grade was at stake. Participants were more likely to determine exclusion was acceptable if the excluded student had an ASD diagnosis, there was a grade at stake, and it occurred in a classroom. Exclusion was less likely to be considered acceptable in the “no grade” compared to the “grade” conditions for LD students, but remained high in both conditions for autistic students. This study also describes contextual variations in participants’ justifications for their evaluations.

Objectives: The Pittsburgh Influenza Prevention Project (PIPP) has previously shown that school-aged children in grades K-5 can learn hygiene-based, nonpharmaceutical interventions (NPIs) and persist in these behaviors over the duration of an influenza season. The purpose of this study was to determine whether age (as estimated by grade) plays any role in this ability. Methods: The Pittsburgh Influenza Prevention Project is a prospective, controlled, randomized trial of the effectiveness of a suite of NPIs in 10 elementary schools. The project measured adoption of NPIs by students through surveys of intervention homeroom teachers before, during, and after the influenza season and control home-room teachers after influenza season. Results: There were large, statistically significant improvements and persistence over time across all grade levels, in students' concern about influenza and their daily practice of NPIs that promote health behaviors—\"wash or sanitize your hands often\" and \"cover your coughs and sneezes.\" Nonpharmaceutical interventions characterized as extinguishing unhealthy behaviors, such as \"avoid touching your eyes, nose, and mouth\" or \"home is where you stay when you are sick,\" showed no reliable improvement. Conclusions: The study provides evidence that elementary school-aged children, across all grades, can understand and implement protective NPIs and maintain these activities throughout influenza season and beyond. Improvements were most prominent when teaching students to engage in health-promoting behaviors. Habitual behaviors (unconscious touching) and changing family behaviors (staying home) seem less susceptible to intervention. These results will be useful to public health policy makers and health care practitioners considering methods of infectious disease prevention in school-based settings.

Background To reduce nursing shortages, accelerated nursing programs are available for domestic and international students. However, the withdrawal and failure rates from these programs may be different than for the traditional programs. The main aim of our study was to improve the retention and experience of accelerated nursing students. Methods The academic background, age, withdrawal and failure rates of the accelerated and traditional students were determined. Data from 2009 and 2010 were collected prior to intervention. In an attempt to reduce the withdrawal of accelerated students, we set up an intervention, which was available to all students. The assessment of the intervention was a pre-post-test design with non-equivalent groups (the traditional and the accelerated students). The elements of the intervention were a) a formative website activity of some basic concepts in anatomy, physiology and pharmacology, b) a workshop addressing study skills and online resources, and c) resource lectures in anatomy/physiology and microbiology. The formative website and workshop was evaluated using questionnaires. Results The accelerated nursing students were five years older than the traditional students (p < 0.0001). The withdrawal rates from a pharmacology course are higher for accelerated nursing students, than for traditional students who have undertaken first year courses in anatomy and physiology (p = 0.04 in 2010). The withdrawing students were predominantly the domestic students with non-university qualifications or equivalent experience. The failure rates were also higher for this group, compared to the traditional students (p = 0.05 in 2009 and 0.03 in 2010). In contrast, the withdrawal rates for the international and domestic graduate accelerated students were very low. After the intervention, the withdrawal and failure rates in pharmacology for domestic accelerated students with non-university qualifications were not significantly different than those of traditional students. Conclusions The accelerated international and domestic graduate nursing students have low withdrawal rates and high success rates in a pharmacology course. However, domestic students with non-university qualifications have higher withdrawal and failure rates than other nursing students and may be underprepared for university study in pharmacology in nursing programs. The introduction of an intervention was associated with reduced withdrawal and failure rates for these students in the pharmacology course.

Student modeling approaches are important to identify students’ needs, learning styles, and to monitor their improvements for individual modules. Lecturers may incorrectly identify the students’ needs and learning styles based on solely an exam grade or performance in the class. In doing so, students need to be classified using more parameters such as e-learning activities, attendance to virtual live class (for theory and practice) and submission time of the assignment, etc. This study proposes a novel color-labeled student modeling/classification approach using e-learning activities to identify students’ learning styles and to monitor students’ weekly improvements for individual modules. A novel Student Classification Rate (SCR) formula was created by combining three stages including pre-study stage, virtual_class stage, and virtual_LAB_class stage. In the evaluation part of the SCR, Artificial Neural Network and Random Forest algorithms were employed based on two different feature sets for an Object-Oriented Programming Module. Feature set 1 consisted of a combination of e-learning and regular data while the feature set 2 was referred as the combination of the SCR and the regular data. Random Forest yielded the lowest MAE (0.7) by using feature set 2. Also, the majority of the students’ (81%) learning styles referred to attending the live virtual class. Students’ weekly learning progress was also monitored successfully since the Pearson correlation was measured as 0.78 with the 95% confidence interval between the mean of SCR and lab grades. Additionally, SCR used for two more different modules yielded convincing results in the determination of students’ learning styles. The obtained results reveal that the proposed SCR approach has significant potential to correctly classify students, identify students’ learning styles, and help the lecturer to monitor the students' weekly progress. Finally, it seems that SCR would have a significant impact on improvement of students learning.

To compare the frequency and magnitude of head impacts between National Collegiate Athletic Association Division I and American high school football players. The long-term goal is to correlate impact forces with injury patterns, leading to improvements in protective headgear. The helmets of football players at the University of Oklahoma (n = 40) and Casady High School (n = 16) were instrumented with the Head Impact Telemetry System (Simbex, Lebanon, NH). Data were collected for practices and games for the 2005 football season and were analyzed by player position and school. Player positions were separated into two groups (skill and line) for analysis. Two case studies of athletes who sustained a concussion are also presented. A total of 54,154 impacts were recorded at the University of Oklahoma and 8326 at Casady High School. College players sustained high-level impacts greater than 98 g more frequently than high school players. The mean linear accelerations for the top 1, 2, and 5% of all impacts were also higher for college players (P < 0.02). Skill position players received 24.6% of all impacts and sustained an impact greater than 98 g once every 70 impacts. In contrast, linemen sustained the highest number of impacts, but most were relatively low-magnitude (20-30 g). Linemen sustained an impact greater than 98 g once every 125 impacts. Differences in the frequency and magnitude of head acceleration after impact exist between a Division I college team and a high school team. Compared with linemen, skill position players typically sustain the highest-level impacts. Additional data collection and analysis are required to correlate concussion diagnosis with acceleration magnitude and impact location.

We compared food insecurity status, coping strategies, demographic characteristics, and self-rated health of international and domestic postsecondary students requesting emergency food hampers from a campus food bank (CFB). We collected data from a cross-sectional convenience sample of domestic and international students who accessed the CFB at the University of Alberta. Food insecurity was prevalent (international students: n = 26/27 (96.2%), domestic students: n = 31/31 (100%)). Compared with their domestic peers, international students were less likely to rate their mental health negatively (14.8% vs 38.7%, P = 0.04). The primary income source was government loans (54.8%) for domestic students and research assistantships (33.3%) for international students. To cope with not having enough money for food, the majority of both student groups delayed bill payments or buying university supplies, applied for loans or bursaries, purchased food on credit, or worked more. International students were less likely to ask friends or relatives for food (48.1% vs 77.4%, P = 0.02). Domestic and international students mostly used similar coping strategies to address food insecurity; however, they paid for their education using different income sources. Distinct strategies for international and domestic students are required to allow more students to cover their educational and living expenses.

This study examined stakeholders’ satisfaction with current student classification and progress monitoring systems and explored their perceptions of the potential role of artificial intelligence (AI) in enhancing these processes. A cross-sectional survey was administered to 313 stakeholders, including teachers, administrators, decision-makers, and educational service providers. Descriptive statistics, multiple regression analysis, and group comparisons were employed to examine satisfaction levels, predictors of satisfaction, and expectations regarding AI integration. Despite high satisfaction with the current systems (85%), nearly 80% of stakeholders rated AI integration as essential. The most frequently expected functions of an AI-enabled system were predicting student challenges (33.2%), generating detailed analyses and reports (32.9%), customizing individual learning plans (22.7%), and providing immediate feedback (11.2%). Anticipated challenges focused on acceptance and adaptation by teachers and students (40.9%) and concerns about privacy and system integration. Regression analysis revealed that perceptions of classification practices (β = 0.473, p < 0.001) were a stronger predictor of satisfaction than perceptions of progress monitoring practices (β = 0.315, p < 0.001). Demographic analyses revealed greater dissatisfaction among non-teaching staff, females, and mid-career professionals. The findings show that stakeholders are broadly satisfied with existing systems while simultaneously demanding AI-driven innovation, suggesting satisfaction reflects acceptance rather than alignment with stakeholders’ needs and expectations.