A faster running speed is associated with a greater body weight loss in 100-km ultra-marathoners

In 219 recreational male runners, we investigated changes in body mass, total body water, haematocrit, plasma sodium concentration ([Na(+)]), and urine specific gravity as well as fluid intake during a 100-km ultra-marathon. The athletes lost 1.9 kg (s = 1.4) of body mass, equal to 2.5% (s = 1.8) of body mass (P < 0.001), 0.7 kg (s = 1.0) of predicted skeletal muscle mass (P < 0.001), 0.2 kg (s = 1.3) of predicted fat mass (P < 0.05), and 0.9 L (s = 1.6) of predicted total body water (P < 0.001). Haematocrit decreased (P < 0.001), urine specific gravity (P < 0.001), plasma volume (P < 0.05), and plasma [Na(+)] (P < 0.05) all increased. Change in body mass was related to running speed (r = -0.16, P < 0.05), change in plasma volume was associated with change in plasma [Na(+)] (r = -0.28, P < 0.0001), and change in body mass was related to both change in plasma [Na(+)] (r = -0.36) and change in plasma volume (r = 0.31) (P < 0.0001). The athletes consumed 0.65 L (s = 0.27) fluid per hour. Fluid intake was related to both running speed (r = 0.42, P < 0.0001) and change in body mass (r = 0.23, P = 0.0006), but not post-race plasma [Na(+)] or change in plasma [Na(+)] (P > 0.05). In conclusion, faster runners lost more body mass, runners lost more body mass when they drank less fluid, and faster runners drank more fluid than slower runners.     

Integrating technical editing students into a multidisciplinary engineering project

A three‐year experiment in integrating technical editing students into a multidisciplinary engineering design project developed several ways of helping students apply classroom learning to practical problems. Each year, the engineering students formed Integrated Product Teams (IPTs) and the technical editing students provided editorial support, first as full members of IPTs, then as separate editorial support teams. Research from cooperative learning and teamwork indicates strategies and techniques for best integrating the technical editing students.     

Models and Strategies for Factor Mixture Analysis: An Example Concerning the Structure Underlying Psychological Disorders

The factor mixture model (FMM) uses a hybrid of both categorical and continuous latent variables. The FMM is a good model for the underlying structure of psychopathology because the use of both categorical and continuous latent variables allows the structure to be simultaneously categorical and dimensional. This is useful because both diagnostic class membership and the range of severity within and across diagnostic classes can be modeled concurrently. Although the conceptualization of the FMM has been explained in the literature, the use of the FMM is still not prevalent. One reason is that there is little research about how such models should be applied in practice and, once a well-fitting model is obtained, how it should be interpreted. In this article, the FMM is explored by studying a real data example on conduct disorder. By exploring this example, this article aims to explain the different formulations of the FMM, the various steps in building a FMM, and how to decide between an FMM and alternative models.     

Sickness presenteeism of German teachers: prevalence and influencing factors

The aim of the present study was to investigate teachers’ sickness presenteeism (SP). We examined the prevalence of SP in a sample of teachers as well as work-related and health-related influencing factors of teachers’ SP. We used a cross-sectional study design. Teachers working at different types of schools in Rhineland-Palatinate (Germany) participated in an online survey. We used Pearson’s Chi-squared test (in case of categorical variables) or Mann–Whitney-U-test (in case of continuous variables) to test for differences between SP and sociodemographic/work-related/health-related factors. Factors influencing SP were identified using multivariable logistic regression analyses. Nine hundred and twenty-four teachers working at 42 different schools completed the questionnaire (response proportion: 50.1%). The prevalence of SP in our study was 57.1%. The multivariable logistic regression analyses showed less support by supervisors (aOR: 1.77; 95-CI: 1.21–2.60), inappropriate administration efforts (aOR: 1.56; 95-CI: 1.16–2.11), and inappropriate recognition of performance (aOR: 1.44; 95-CI: 1.04–198) as well as exhaustion/fatigue (aOR: 2.29; 95-CI: 1.71–3.08) as main predictors of teachers’ SP. SP is widespread among teachers. As SP is associated with impairment of psychological and physical health in the long run, it is important to implement measures to reduce SP. A climate of support and cooperation as well as assistance for ill teachers to deal with work missed due to absence might be useful strategies.     

Shape recognition in infancy: visual integration of sequential information

To investigate the integration of visual information across space and time, infants watched the contour of a shape being traced out by a moving point source of light and then viewed 2 objects: 1 with the shape they had just seen traced and 1 with a novel shape. In the first study, which varied the number of tracings (velocity about 16.7 cm/sec), 12-month-olds looked longer at the novel object in all conditions, indicating that they recognized the similarity between the alternative object and tracing of like contour. Study 2, which varied velocity (14.7 and 7.4 cm/sec), stimuli, and the number of tracings, provided evidence for the generalizability of these results but indicated that performance suffered at the slower speed. Studies 3 and 4 held velocity constant (14.7 cm/sec) while varying the size of the tracings and age of the infant: 12-month-olds, but not 6-month-olds, recognized figures in instances where it took up to 10 sec to complete a single tracing. Because it took so long to complete many of the tracings, central rather than purely retinal mechanisms appear to be involved in integrating shape in these situations.     

Visual Learning and the Brain: Implications for Dyslexia

ABSTRACT— The central and peripheral visual fields are structurally segregated in the brain and are differentiated by their anatomical and functional characteristics. While the central field appears well suited for tasks such as visual search, the periphery is optimized for rapid processing over broad regions. People vary in their abilities to make use of information in the center versus the periphery, and we propose that this bias leads to a trade-off between abilities for sequential search versus contemporaneous comparisons. The parameter of periphery-to-center ratio (PCR) describes the degree of peripheral bias, which evidence suggests is high in many people with dyslexia. That is, many dyslexics favor the peripheral visual field over the center, which results in not only search deficits but also (more surprisingly) talents for visual comparison. The PCR framework offers a coherent explanation for these seemingly contradictory observations of both deficit and talent in visual processing. The framework has potential implications for instructional support in visually intensive domains such as science and mathematics.