Validation of a Skinfold Prediction Equation Based on Dual-Energy X-Ray Absorptiometry to Estimate Body Fat Percentage in Women

ABSTRACT

The purpose of this study was to validate an alternative skinfold equation for women created from dual-energy x-ray absorptiometry (DXA). Anthropometrics and a whole-body DXA scan were completed on 77 women (mean age: 28.0 ± 10.2 years). Four Jackson-Pollack (JP) skinfold prediction equations and the DXA criterion (DC) equation were compared to DXA-derived body fat percentage (%BF). One-way repeated measures ANOVA revealed significant differences (p ≤ .001) in the %BF with post hoc-comparisons revealing significant differences among JP7 (21.3 ± 5.7), JP4 (21.4 ± 5.7), JP3a (22.2 ± 5.9), and JP3b (22.6 ± 5.7) when compared to the DXA-derived %BF; no significant difference existed between DC %BF (26.5 ± 5.6) and DXA-derived %BF (26.5 ± 5.4) (p = 1.0). The DC equation more accurately predicted %BF in women volunteers compared to Jackson-Pollack equations.     

Science Motivation and Achievement Among Minority Urban High School Students: an Examination of the Flipped Classroom Model

Journal of Science Education and Technology - The effect of the flipped classroom model (FCM) on high school students’ science motivation and achievement in an urban public school was...     

Analyzing Mixed-Dyadic Data Using Structural Equation Models

Mixed-dyadic data, collected from distinguishable (nonexchangeable) or indistinguishable (exchangeable) dyads, require statistical analysis techniques that model the variation within dyads and between dyads appropriately. The purpose of this article is to provide a tutorial for performing structural equation modeling analyses of cross-sectional and longitudinal models for mixed independent variable dyadic data, and to clarify questions regarding various dyadic data analysis specifications that have not been addressed elsewhere. Artificially generated data similar to the Newlywed Project and the Swedish Adoption Twin Study on Aging were used to illustrate analysis models for distinguishable and indistinguishable dyads, respectively. Due to their widespread use among applied researchers, the AMOS and Mplus statistical analysis software packages were used to analyze the dyadic data structural equation models illustrated here. These analysis models are presented in sufficient detail to allow researchers to perform these analyses using their preferred statistical analysis software package.     

Relations Between Fantasy Orientation and Emotion Regulation in Preschool

Research Findings: Emotion regulation is a strong predictor of both short- and long-term peer relationships and social competence and is often targeted in preschool curricula and interventions. Pretense is a natural activity of childhood that is thought to facilitate the development of socialization, perspective taking, language, and possibly emotion regulation. This study investigated whether fantasy-oriented children, who engage in more pretense, demonstrate higher levels of emotion regulation. Prekindergartners (n = 103) and teachers were given a battery of measures assessing children’s emotion regulation, fantasy orientation, theory of mind, and language. Results from hierarchical regression analyses indicated that children’s proclivity toward fantastical play (their fantasy orientation) uniquely predicted 24% of the variance in their emotion regulation skills over and above typical predictors: age, theory of mind, and language skills. That is, children who participated in more fantasy pretense demonstrated better emotion regulation skills than their peers. Practice or Policy: The present study suggests that future research, curriculum, and interventions should focus on targeting fantastical pretense to assess causal mechanisms of emotion regulation development. Teachers and parents should encourage children’s fantastical pretense, as research suggests it may be an important contributor to the development of critical socialization skills such as emotion regulation.     

Answering the Call: How Group Mentoring Makes a Difference

Mentoring programs answer the call for social justice for many students who are in success-inhibiting environments. This study employed a case study design to investigate the perceived benefits from a group mentoring program. Data was collected from pre- and post-assessments focus groups, and artifacts. Four participant benefits were revealed: comfort, non-academic support, academic support, and safety. This study argues that group mentoring offers a viable option to traditional mentoring approaches. Additionally, recommendations include further exploration into benefits from other types of group mentoring programs. Schools with scarce volunteers and monetary resources could benefit from the implementation of this mentoring approach.     

Learning as identity and practice through involvement in online moderation

For teachers working in a standards-based assessment system, professional conversations through organised social moderation meetings are a vital element. This qualitative research investigated the learning that occurred as a result of online moderation discussions. Findings illustrate how participating in social moderation meetings in an online context can support teachers to understand themselves as assessors, and can provide opportunities for teachers to imagine possibilities for their teaching that move beyond the moderation practice.     

Predictive relationship between gender,ethnicity, science self-efficacy,teacher interpersonal behaviors,and science achievement of students in a diverse urban high school

Learning Environments Research - We examined the predictive relationship between high school students’ gender, ethnicity, science self-efficacy as measured by the Science Self-Efficacy...