Background: Physical health is one of the most important human assets and motor competence can improve this. This study aimed to investigate the effect of physical activity levels and physical maturity on the motor competency of 8–, 11 year-old children in Tehran. Materials and Methods: The present study was a cross sectional-analytical study. The statistical population was children aged 8-11 years in Tehran from which 205 people (105 girls and 100 boys) were randomly selected. Assessment of the level of physical activity using the international physical activity questionnaire for children, index of physical maturity through Khamis-Roche method and motor competency was assessed using the TMC test. Data were analyzed using multifactorial analysis of variance and Bonferroni Post hoc test. Results: The results of multifactorial analysis of variance showed that the main effect of physical activity level was not significant (P =0. 74). Children with late adulthood had better mean motor fitness at all three levels of physical activity. Children with high levels of physical activity had better mean motor fitness than children with moderate and low levels of physical activity. The main effect of physical maturity levels was significant (P= 0. 001). Conclusion: It is suggested to develop a comprehensive and practical program in schools to increase the level of physical activity and skills in children in order to develop motor skills.

Background & Objective: Motor competency refers to ability of children to perform wide range of fine and gross motor activities. Children with low motor competency, might mostly face to many unsuccessful situation and may experience and develop a lots of problems in their life. The aim of this study was to investigate the effect of some selected factors including age, birth order, social status and contribution in outdoor physical activity program on motor competency of 7– 10 years old children using movement assessment battery for children– second edition (MABC2) which is a one of the most valid assessment tools for assessing motor competency. Methods: Five hundred and three (girls=244, boys=259) 7– 10 years old children from the Arak city (Markazi province, Center of Iran) were participated in this cross sectional study. Inclusion and exclusion criteria of this study were as follow; lack of any developmental, neurological and learning difficulties, which may impair their typical performances. In addition, children without demographic data were excluded from the data set. Asked from parents to fill out the demographic questionnaire (data including; age, gender, level of parents` education, birth order and sibling and level of outdoor physical activities of children). In addition, written consent of parents was obtained. After collecting demographic data, testing started. Three well experienced examiners in the field of children` motor skills performed testing. All the requirement of testing instructions based on MABC2 manual was observed. Children, having trouser and shoes, were tested individually with MABC2 in a quiet room. When testing completed, we analyzed the data. Ojari et al. (2018) reported psychometric properties of MABC2 that the properties are acceptable in Iran. The proposed 3 factors structure was confirmed and intra and interrater reliability were (0. 93– 0. 99) and (0. 45 – 0. 85) respectively. Descriptive statistic as well as multivariate analysis of variance (one– way MANOVA) were used to analyzing the data. Significant level was set at 0. 05 and all analysis was carried out using SPSS 21 for Windows (SPSS, Chicago, IL, USA). Results: multivariate ANOVA showed there was statistically signifi cant differences of factors age (F=7. 16, p<0. 001) and birth order (F=2. 621, p<0. 001), however, no statistically differences were found for the outdoor physical activity (F=1. 487, p=0. 218) and social status (F=1. 74, p=0. 158). The effect size of age and birth order were 0. 14 and 0. 016 respectively, which indicate large and negligible importance. When age increased, performance of children improved dramatically so that in most tasks 9 and 10 years old children were superior to younger children. The result of multivariate analysis also showed that statistical differences in birth order factor was only because of differences in manual dexterity sub– component. Conclusion: Age is considered as an important and effective factor on children` motor competency. MABC2 is able to differentiate age group very well. Improved coordination and performance during childhood is due to integration of sensory– motor systems. Of other factors, only the birth order showed a statistically differences, however, that was not large enough to be considered practically important. This study should be duplicated by another similar tools assessment to find out whether lack of non– statistical differences is attributed to poor influence of related factors or poor differentiate ability of MABC2.

Background: Understanding the way nurses' informatics competencies affect their mastery of professional competencies can help with providing high quality care and design contents for continuing nursing education. This study aimed to determine the association between nurses' informatics and their clinical competencies. Materials & Methods: A total of 150 nurses who met the inclusion criteria were enrolled in this descriptive study from three general public hospitals in Rafsanjan, Iran, using stratified random sampling method. Self-reporting data collection was performed applying three questionnaires of (1) personal and job characteristics, (2) the Self-Assessment of Nursing Informatics Competencies Scale (SANIC), and (3) the Competency Inventory for Registered Nurses (CIRN). Data were analyzed using SPSS 22. 0 and Kolmogorov-Smirnov, Chi-square, Pearson's correlation coefficient, and linear regression statistical tests. Results: Female nurses had higher CIRN scores than male ones (p = 0. 027). The results of the Pearson's correlation coefficient showed a moderate significant positive association between SANIC and CIRN scores (r = 0. 341, p = 0. 001). Furthermore, results of the linear regression analysis showed that about 11% of the CIRN score was associated to the SANIC score (P = 0. 001). After adjustment based on gender (p = 0. 060) and education (p = 0. 064), the correlation was not significant. Conclusion: Given the effect of gender and level of education, there was no significant association between Nursing Informatics Competencies and nurses’,competency. The level of application of informatics in nursing should be reviewed contextually.