This study explored associations between students’ perceptions of challenge, teacher-provided support and obstruction, and students’ momentary academic engagement in high school science classrooms. Instrumental and emotional dimensions of support and obstruction were examined separately, and analyses tested whether the relationship between challenge and engagement was moderated by teacher support, teacher obstruction, and individual characteristics like gender and grade level. Students’ perceptions of challenge were positively related to their momentary reports of engagement in science learning activities, while teachers’ instrumental support was positively associated with engagement across all levels of perceived challenge. Even though teachers’ provision of emotional support was not predictive of student engagement, teachers’ emotional obstruction was negatively associated with student engagement. Teachers’ instrumental obstruction had less consistent associations with student engagement, and was only associated with declines in engagement during those moments when students perceived greater challenge in class. Both gender and grade level emerged as moderators of the relationship between challenge and engagement. Results are discussed in terms of implications for future research and instructional practice.

The primary purpose of the study was to determine if girls in one school receiving nurse counseling plus an after-school Physical Activity Club showed greater improvement in physical activity, cardiovascular fitness, and body composition than girls assigned to an attention control condition in another school (N = 69). Linear regressions controlling for baseline measures showed no statistically significant group differences, but directionality of differences was consistent with greater intervention group improvement for minutes of moderate to vigorous physical activity/hour (t = 0.95, p = .35), cardiovascular fitness (t = 1.26, p = .22), body mass index (BMI; t = −1.47, p = .15), BMI z-score (t = −1.19, p = .24), BMI percentile (t = −0.59, p = .56), percent body fat (t = −0.86, p = .39), and waist circumference (t = −0.19, p = .85). Findings support testing with a larger sample.

This study provided initial validity evidence for multidimensional measures of coaching competency derived from the Coaching Competency Scale (CCS). Data were collected from intercollegiate men's (n = 8) and women's (n = 13) soccer and women's ice hockey teams (n = 11). The total number of athletes was 585. Within teams, a multidimensional internal model was retained in which motivation, game strategy, technique, and character building comprised the dimensions of coaching competency. Some redundancy among the dimensions was observed. Internal reliabilities ranged from very good to excellent. Practical recommendations for the CCS are given in the Discussion section.

Background and Purpose-Quality of care may be influenced by patient and hospital factors. Our goal was to use multilevel modeling to identify patient-level and hospital-level determinants of the quality of acute stroke care in a stroke registry. Methods-During 2001 to 2002, data were collected for 4897 ischemic stroke and TIA admissions at 96 hospitals from 4 prototypes of the Paul Coverdell National Acute Stroke Registry. Duration of data collection varied between prototypes (range, 2-6 months). Compliance with 8 performance measures (recombinant tissue plasminogen activator treatment, antithrombotics Ͻ24 hours, deep venous thrombosis prophylaxis, lipid testing, dysphagia screening, discharge antithrombotics, discharge anticoagulants, smoking cessation) was summarized in a composite opportunity score defined as the proportion of all needed care given. Multilevel linear regression analyses with hospital specified as a random effect were conducted. Results-The average hospital composite score was 0.627. Hospitals accounted for a significant amount of variability (intraclass correlationϭ0.18). Bed size was the only significant hospital-level variable; the mean composite score was 11% lower in small hospitals (Յ145 beds) compared with large hospitals (Ն500 beds). Significant patient-level variables included age, race, ambulatory status documentation, and neurologist involvement. However, these factors explained Ͻ2.0% of the variability in care at the patient level. Conclusions-Multilevel modeling of registry data can help identify the relative importance of hospital-level and patient-level factors. Hospital-level factors accounted for 18% of total variation in the quality of care. Although the majority of variability in care occurred at the patient level, the model was able to explain only a small proportion. (Stroke. 2010;41: 2924-2931.)