1,993 publications from this institution
SupplementaryFigure from Concurrent Disruption of the Ras/MAPK and NF-κB Pathways Induces Circadian Deregulation and Hepatocarcinogenesis
<p>guide to murine tumor analysis</p>
Introduction The Nutrition Environment Measurement Survey (NEMS) measures were developed to assess the consumer food environment in stores and restaurants. NEMS tools have been widely used in research and adapted for diverse settings and populations in the 15 years since they were created. This systematic review examines the use and adaptations of these measures and what can be learned from published studies using NEMS tools. Methods A comprehensive search of bibliographic databases was conducted from 2007 to September 2021, supplemented by backward searches and communications with authors, to identify research articles using NEMS tools. Data on purpose, key findings, sample characteristics, NEMS characteristics, and modifications were abstracted. Articles were categorized on the basis of study goals, NEMS tool(s) used, variables measured, and common themes. Results A total of 190 articles from 18 countries were identified. Most studies (69.5%, n=123) used a modified version of NEMS tools. There were 23 intervention studies that used measures from NEMS tools or adaptations as outcomes, moderators, or process assessments. A total of 41% (n=78) of the articles evaluated inter-rater reliability, and 17% (n=33) evaluated test–retest reliability. Discussion NEMS measures have played an important role in the growth of research on food environments and have helped researchers to explore the relationships among healthy food availability, demographic variables, eating behaviors, health outcomes, and intervention-driven changes in food environments. The food environment is constantly changing, so NEMS measures should continue to evolve. Researchers should document data quality of modifications and use in new settings.
A primary purpose of this study was to describe differences between self-contained and team teaching approaches when two groups of fourth- and fifth-grade classroom teachers attempted to implement a physical education curriculum during a 4-month in-service program. One school featured team teaching in pairs during physical education classes; the other used a self-contained teaching approach. The program required a minimum of three 30-min physical education classes weekly. All teachers participated in an extensive in-service training program that included weekly on-site assistance. Data collection included teachers’ lesson-completion forms, specialist’s reports, SOFIT PE class observations, teacher-completed Stages of Concern questionnaires, and teachers’ formal interviews. Results indicated that classroom teachers who used the self-contained model more consistently implemented the curriculum and more frequently expressed positive responses. Participants who used the team model for the physical education curriculum frequently strayed from the assigned pedagogical approach, ignored major portions of the program, and experienced extreme management concerns.
The objective of this study was to examine the association of scholastic performance with physical activity and fitness of children. To do so, school ratings of scholastic ability on a five-point scale for a nationally representative sample of 7,961 Australian schoolchildren aged 7–15 years were compared with physical activity and fitness measurements. Consistently across age and sex groups, the ratings were significantly correlated with questionnaire measures of physical activity and with performance on the 1.6-kilometer run, sit-ups and push-ups challenges, 50-meter sprint, and standing long jump. There were no significant associations for physical work capacity at a heart rate of 170 (PWC 170 ). The results are concordant with the hypothesis that physical activity enhances academic performance, but the cross-sectional nature of the observations limits causal inference, and the disparity for PWC 170 gives reason to question whether the associations were due to measurement bias or residual confounding.