ABSTRACT
Information literacy is a set of individual skills and abilities to accurate identifying, accessing, using, evaluating and reviewing of information resources. Since this skills improved the student capabilities to retrieval, management and use of information; nowadays, it is considered as one of the most importantcriterion fortheevaluation of students by forums. This study is a descriptive and analytical applied survey. The systematized samples were 103 students in paramedical sciences faculty Shahid Beheshti University of medical sciences in 3 level: undergraduate [BA], master [MA] and PhD students who were studying during 2011-2012.The data collection tool is the questionnaire which published by ACRL and based on information literacy standards. This questionnaire has 55 item arranged in Likert scale. Results shows that the information literacy level in all studentwas50 % lower than the level expected of ACRL standards except Ph.D. students in basic science and MA students in medical library and information science. The level of information literacy in PhD and MA students was significantly higher than BA students while the graduate students level was not significantly different
ABSTRACT
Many commonly used statistical methods require that the population distribution be nearly normal. Unfortunately, in some papers the one-sample Kolmogorov-Smirnov test has been used for testing normality while the assumptions of applying this test are not satisfied. To conduct this test, it is assumed that the population distribution is fully specified. In practical situation where the mean and SD of population distribution is not specified in advance, one can use a modification of the K-S test for checking the normality assumption which is called, Lilliefors test. In this paper, we explain the method of computing this test with some common statistical softwares such as SPSS, S-PLUS, R and StatXact and utilize a dermatology dataset from Skin Research Center of Shohada-e-Tajrish hospital to illustrate how the use of the one-sample K-S [with the mean and SD estimated from the sample] instead of its modification can be misleading in practice. We also use Monte Carlo simulation to compare the approximate power of the one-sample K-S test [with the estimated population mean and SD] with Lilliefors test in some common specified continuous distributions. The result indicates that one should not use the one-sample K-S test for assessing the normality assumption in practical situation
ABSTRACT
Hypothermia is an important determinant of survival in newborns, especially among low-birth-weight ones. Prolonged hypothermia leads to edema, generalized hemorrhage, jaundice and ultimately death. This study was undertaken to examine the factors affecting transition from hypothermic state in neonates. The study consisted of 439 neonates hospitalized in NICU of Valiasr in Tehran, Iran in 2005. The neonates' rectal temperature was measured immediately after birth and every 30 minutes afterwards, until neonates passed hypothermia stages. In order to estimate the rate of transition from neonatal hypothermic state, we used multistate Markov models with two covariates, birth weight and environmental temperature. We also used R package to fit the model. Estimated transition rates from severe hypothermia and mild hypothermia were 0.1192 and 0.0549 per minute, respectively. Weight had a significant effect on transition from hypothermia to normal condition [95% CI: 0.1364-0.4165, P<0.001]. Environmental temperature significantly affected the transition from hypothermia to normal stage [95% CI: 0.0439-0.4963, P<0.001]. The results of this study showed that neonates with normal weight and neonates in an environmental temperature greater than 28°C had a higher transition rate from hypothermia stages. Since birth weight at the time of delivery is not under the control of medical staff, keeping the environmental temperature in an optimum level could help neonates to pass through the hypothermia stages faster
Subject(s)
Humans , Infant, Newborn , Birth Weight , Temperature , Body Temperature Changes , Markov Chains , Intensive Care Units, NeonatalABSTRACT
Investigation of the web impact factor and analysis of the web links belong to webometric studies. A high impact factor, accompanied by more frequent links to a particular website, can indicate greater influence and better accessibility of that particular site. In this regard, bearing in mind the significance of medical universities' web sites for education and research, the current study compared and analyzed their impact factors, their web links and web pages, using AltaVista search engine. The investigation included different ranks of medical universities, commonly referred to as type 1, type 2 and type 3 universities in Iran. The median was used as a measure of central tendency of the scores. The search engines of AltaVista were adopted on 26 February 2010 to collect the data. According to the results, in terms of indexed pages, Shahid Baheshti of type 1, Guilan of type 2, and Shahrekord of type 3 universities had the best records. Regarding web links, medical universities of Iran, Kermanshah and Lorestan, from type 1, type 2 and type 3 universities had the best records and, in terms of impact factor, universities of Ahvaz [type 1], Zahedan [type 2], and Fessa [type 3] manifested the greatest influence. As the results imply, the universities are expected to pay more attention to webometric issues; they are also recommended to allocate more budget to enhance their web pages