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Wie stark eine Person in ihrer alltäglichen Umgebung auf Anzahlen achtet (Spontane Fokussierung auf Anzahligkeit, kurz SFON) ist individuell sehr unterschiedlich. Zwar liegen bereits hinreichende Belege für einen Zusammenhang zwischen SFON und Zählfertigkeiten, Subitizing und basalen sowie höheren arithmetischen Fertigkeiten im Kindergarten und der frühen Grundschulzeit vor, die Einordnung der relativen Bedeutsamkeit von SFON gegenüber bereits bekannten und gut belegten Prädiktoren fehlt jedoch. Daneben lag der bisherige Schwerpunkt vorrangig auf Zählfertigkeiten. Offen bleiben die Kompetenzen des Kindes in der Mengenerfassung und -verarbeitung sowie die bereits im Vorschulalter vorhandene Kenntnis arabischer Ziffern.
Die Daten dieser Arbeit wurden im Rahmen einer großen epidemiologischen Studie (SCHUES) erhoben. Eine Stichprobe von 1868 Kindergartenkindern (964 Jungen und 904 Mädchen) konnte zwölf Monate vor ihrem Schuleintritt erstmalig untersucht werden. Die Kinder waren hier im Mittel 63 Monate alt. 1704 Kinder konnten erneut rund neun Monate später (im Mittel drei Monate vor Schulbeginn) getestet werden. Das mittlere Alter der Kinder lag bei 72 Monaten. Die erfassten numerisch-mathematischen Fertigkeiten lassen sich in drei Teilbereiche gliedern: Zählfertigkeiten, Ziffernkenntnis und Rechnen/Mengenerfassung. Daneben wurden SFON, die nonverbale und verbale Intelligenz, die phonologische Schleife, der visuell-räumliche Notizblock sowie die zentrale Exekutive und die Aufmerksamkeit zu beiden Messzeitpunkten erhoben.
Die SFON-Tendenz zeigte eine mäßige, numerisch-mathematische Fertigkeiten eine mäßige bis hohe Stabilität über die Zeit. Der an bisher deutlich kleineren Stichproben gefundene Zusammenhang zwischen der SFON-Tendenz und den numerisch-mathematischen Fertigkeiten konnte in der vorliegenden Arbeit repliziert werden. Eine Vorhersage auffälliger als auch sehr guter numerisch-mathematischer Leistungen gelang jedoch weder quer- noch längsschnittlich mit ausreichend hoher Genauigkeit. Auch der bereits in der Literatur beschriebene reziproke Zusammenhang zwischen SFON und numerisch-mathematischen Fertigkeiten konnte durch die vorliegende Arbeit an einer großen Stichprobe repliziert werden. Darüber hinaus wurden Hinweise auf die kausale Struktur des Zusammenhangs gewonnen: Die Ergebnisse zeigten, dass numerisch-mathematische Fertigkeiten SFON besser vorhersagen konnten als andersherum. Die Ergebnisse der Pfadanalysen zeigten weiterhin, dass SFON neben den bedeutsamen Konstrukten des Arbeitsgedächtnisses, der Intelligenz und der Aufmerksamkeit einen eigenständigen Beitrag für die Entwicklung numerischer als auch mathematischer Fertigkeiten leistet. Auch auf die weitere numerische und mathematische Entwicklung bis kurz vor Schuleintritt hat SFON einen bedeutsamen Einfluss. Dieser vollzieht sich jedoch indirekt über das numerisch-mathematische Vorwissen.
Validation of two accelerometers to determine mechanical loading of physical activities in children
(2015)
The purpose of this study was to assess the validity of accelerometers using force plates (i.e., ground reaction force (GRF)) during the performance of different tasks of daily physical activity in children. Thirteen children (10.1 (range 5.4-15.7)years, 3 girls) wore two accelerometers (ActiGraph GT3X+ (ACT), GENEA (GEN)) at the hip that provide raw acceleration signals at 100Hz. Participants completed different tasks (walking, jogging, running, landings from boxes of different height, rope skipping, dancing) on a force plate. GRF was collected for one step per trial (10 trials) for ambulatory movements and for all landings (10 trials), rope skips and dance procedures. Accelerometer outputs as peak loading (g) per activity were averaged. ANOVA, correlation analyses and Bland-Altman plots were computed to determine validity of accelerometers using GRF. There was a main effect of task with increasing acceleration values in tasks with increasing locomotion speed and landing height (P<0.001). Data from ACT and GEN correlated with GRF (r=0.90 and 0.89, respectively) and between each other (r=0.98), but both accelerometers consistently overestimated GRF. The new generation of accelerometer models that allow raw signal detection are reasonably accurate to measure impact loading of bone in children, although they systematically overestimate GRF.
The preference for fruits and vegetables is the main predictor for the longtime healthy eating behavior. There are many factors which affect the development of food preferences. The familiarity with different foods seems to be a special aspect associated with the corresponding preference. To establish a preference for fruits and vegetables during early childhood, we need to know more about the factors that affect this preference development. So far, research has mostly concentrated on the food intake and less on the corresponding preference. Additionally, it is often based on studies of the mere-exposure effect or on older children and their ability to label fruits and vegetables correctly. Findings about the level of food familiarity in young children and its relation to the actual food preference are still missing. Our study focuses on different aspects of food familiarity as well as on their relationship to the child's preference and presents results from 213 children aged 2 to 10 years. Using standardized photos, the food preference was measured with a computer-based method that ran automatically without influence from parents or interviewer. The children knew fewer of the presented vegetables (66 %) than fruits or sweets (78 % each). About the same number of vegetables (63 %) had already been tasted by the children and were considered tasty. Only 48 % of the presented vegetables were named correctly - an ability that increases in older children. Concerning the relationship between the familiarity with vegetables and their preference, the different familiarity aspects showed that vegetables of lower preference were less often recognized, tasted, considered tasty, or named correctly.
Background: Low birth weight (LBW) might be a risk factor for acquiring lower respiratory tract infections (LRTIs) associated with disease related complications in early childhood. HFMD, a frequent viral infection in southern China, is a leading cause of lower respiratory tract infections in children. We analyzed whether LBW is a risk factor for children with HFMD to develop lower respiratory tract infections.
Methods: A total of 298 children with HFMD, admitted to a hospital in Qingyuan city, Guangdong province, were recruited. Demographic data and clinical parameters such as serum glucose level and inflammatory markers including peripheral white blood cell count, serum C-reactive protein, and erythrocyte sedimentation rate were routinely collected on admission. Birth weight data were derived from birth records.
Results: Mean birth weight (BW) was 167 g lower in patients with HFMD and LRTIs as compared to patients with solely HFMD (p = 0.022) and the frequency of birth weight below the tenth percentile was significantly higher in patients with HFMD and LRTIs (p = 0.002).
Conclusions: The results of the study show that low birth weight is associated with a higher incidence of lower respiratory tract infections in young children with HFMD.
We tested the limits of working-memory capacity (WMC) of young adults, old adults, and children with a memory-updating task. The task consisted of mentally shifting spatial positions within a grid according to arrows, their color signaling either only go (control) or go/no-go conditions. The interference model (IM) of Oberauer and Kliegl (2006) was simultaneously fitted to the data of all groups. In addition to the 3 main model parameters (feature overlap, noise, and processing rate), we estimated the time for switching between go and no-go steps as a new model parameter. In this study, we examined the IM parameters across the life span. The IM parameter estimates show that (a) conditions were not different in interference by feature overlap and interference by confusion; (b) switching costs time; (c) young adults and children were less susceptible than old adults to interference due to feature overlap; (d) noise was highest for children, followed by old and young adults; (e) old adults differed from children and young adults in lower processing rate; and (f) children and old adults had a larger switch cost between go steps and no-go steps. Thus, the results of this study indicated that across age, the IM parameters contribute distinctively for explaining the limits of WMC.
Due to their multifunctionality, tablets offer tremendous advantages for research on handwriting dynamics or for interactive use of learning apps in schools. Further, the widespread use of tablet computers has had a great impact on handwriting in the current generation. But, is it advisable to teach how to write and to assess handwriting in pre- and primary schoolchildren on tablets rather than on paper? Since handwriting is not automatized before the age of 10 years, children's handwriting movements require graphomotor and visual feedback as well as permanent control of movement execution during handwriting. Modifications in writing conditions, for instance the smoother writing surface of a tablet, might influence handwriting performance in general and in particular those of non-automatized beginning writers. In order to investigate how handwriting performance is affected by a difference in friction of the writing surface, we recruited three groups with varying levels of handwriting automaticity: 25 preschoolers, 27 second graders, and 25 adults. We administered three tasks measuring graphomotor abilities, visuomotor abilities, and handwriting performance (only second graders and adults). We evaluated two aspects of handwriting performance: the handwriting quality with a visual score and the handwriting dynamics using online handwriting measures [e.g., writing duration, writing velocity, strokes and number of inversions in velocity (NIV)]. In particular, NIVs which describe the number of velocity peaks during handwriting are directly related to the level of handwriting automaticity. In general, we found differences between writing on paper compared to the tablet. These differences were partly task-dependent. The comparison between tablet and paper revealed a faster writing velocity for all groups and all tasks on the tablet which indicates that all participants—even the experienced writers—were influenced by the lower friction of the tablet surface. Our results for the group-comparison show advancing levels in handwriting automaticity from preschoolers to second graders to adults, which confirms that our method depicts handwriting performance in groups with varying degrees of handwriting automaticity. We conclude that the smoother tablet surface requires additional control of handwriting movements and therefore might present an additional challenge for learners of handwriting.