This study is a descriptive research study conducted to identify factors that affect children of Korean mothers the coronavirus disease 2019 (COVID-19) preventive health behavior. It was confirmed that knowledge of COVID-19, maternal confidence, and risk perception of COVID-19 infection were related to the Preventive health behaviors of COVID-19 of Korean mothers with children. The subjects of this study were 191 mothers residing in Korea and raising children under the age of 5, and data were collected through an online questionnaire. We used the Google platform to fill out a questionnaire and collect data using a network sampling method from mothers who voluntarily participated in a survey at an online community meeting of mothers with young children. The collected data were analyzed using descriptive statistics, factor analysis, t-test, Pearson's correlation analysis, and multiple regression analysis using IBM SPSS statistics 21.0 program. Preventive health behaviors of COVID-19 factor 1 are positively correlated with: mothers' COVID-19 knowledge (r = 0.192, p < 0.01), confidence in infant care knowledge(r = 0.179, p < 0.05), and satisfaction with the role of mother(r = 0.351, p < 0.001). Negatively correlated with: unacceptable risk perception(r = -0.222, p< 0.01). Preventive health behaviors of COVID-19 factor 2 are positively correlated with: mothers' COVID-19 knowledge (r = 0.166, p < 0.05), confidence in infant care knowledge(r = 0.179, p < 0.05), and satisfaction with the role of mother(r = 0.338, p < 0.001). Negatively correlated with: unacceptable risk perception(r = -0.205, p < 0.01). To strengthen COVID-19 preventive health behavior of Korean mothers with young children, it is suggested that education programs should be developed to provide accurate knowledge, increase maternal confidence, and improve the risk perception of COVID-19 infection.
IBM SPSS Statistics 21.0
Methods: In this observational study, 127 students who started their summer internship in Antalya Education and Research Hospital were given a one-day theoretical phlebotomy training in accordance with the Venous Blood Sampling Guidelines. After the theoretical training, phlebotomy applications of 10 students who were working in the field of out-patient blood sampling were observed both with and without their knowledge. A comprehensive checklist related to phlebotomy was created by the trainers in Antalya Education and Research Hospital and the observers answered each question as yes or no. For the statistical analysis, IBM SPSS Statistics 21.0 was used.
Metode: Ova opservaciona studija je uključila 127 studenata koji su započeli letnje stažiranje u Obrazovno-istraživačkoj bolnici u Antaliji. Navedeni studenti su prošli jednodnevno teorijsko usavršavanje iz flebotomije, a u skladu sa Smernicama za uzimanje uzoraka venske krvi. Nakon teorijske obuke, sprovedeno je praćenje primene procedura uzimanja uzoraka krvi kod 10 studenata koji su uzimali uzorke krvi u dnevnoj bolnici, i to sa ili bez njihovog znanja o tome. Treneri u Obrazovno-istraživačkoj bolnici u Antaliji su sačinili sveobuhvatnu listu pitanja, a studenti su na svako pitanje odgovorili sa da ili ne. Za statističku analizu korišćen je program IBM SPSS Statistics 21.0.
R Essentials for Statistics or Modeler on GitHubR Essentials enables using R within SPSS Statistics or Modeler. Each SPSS product and version has a different R Essentials, so choose the right download for your version. Download the version for your platform and follow the installation instructions. Be sure to read the installation instructions. You must download and install the appropriate R version from the R CRAN site before installing the Essentials.Get R Essentials for SPSS StatisticsGet R Essentials for SPSS ModelerFor legacy editions of R Essentials go here Python and .NET Essentials for SPSS StatisticsThe Python Essentials for Statistics versions 22 and later are fully integrated with the main Statistics installation. They are no longer a separate item. You can install additional extension commands or update ones already installed from the Utilities menu within Statistics. The .NET plugins for versions 22 and later (Windows only) remains a separate download from the site where you download Statistics. It is also included on the physical media. Use the table below as a guide for different versions of SPSS Statistics.Important: Support for the .NET Plugin is deprecated starting with IBM SPSS Statistics 25. The .NET Plugin is supported only in versions prior to version 25. For version 25, and all subsequent releases (including Subscription), you can build the .NET Plugin functionality via the Programmability SDK package. IBM no longer provides the .NET Plugin installer or corresponding support.Version of SPSS StatisticsExplanationLink to download for Windows (if applicable)SubscriptionPython Essentials is fully integrated with the main installation. Please go to SDK website to find more information about .NET plug-inLink for SDKVersion 25 and laterPython Essentials is fully integrated with the main installation. Please go to SDK website to find more information about .NET plug-inLink for SDKVersions 22,23,24Python Essentials is fully integrated with the main installation. Download .NET plug-in from the site where you download Statistics.Link for .NET plug-inVersion 21Python Essentials and .NET Plug-in are available for download NOTE: They are compatible with Statistics 21.0.0, 21.0.0.1 and 21.0.0.2.Link for downloadVersion 20Python Essentials and .NET Plug-in are available for download NOTE: if you have the 20.0.0.0 or 20.0.0.1 version of the Essentials installed, you must uninstall it before installing this update.Link for downloadVersion 19Python Essentials and .NET Plug-in are available for download NOTE: They are compatible with Statistics 19.0.0, 19.0.0.1, and 19.0.0.2.Link for downloadVersion 18Python Essentials and .NET Plug-in are available for download NOTE: They are compatible with Statistics 18.0.2 and 18.0.3.#SPSSStatistics
SPSS provides data analysis for descriptive and bivariate statistics, numeral outcome predictions and predictions for identifying groups. The software also provides data transformation, graphing and direct marketing features.
Patients and Methods: In this study, we examined the relationship between; neutrophil to lymphocyte ratio (NLR), mean platelet volume (MPV) and C-reactive protein (CRP)/albumin values at the time of hospital admission with mortality in 75 HD patients diagnosed with COVID-19. All analyses were conducted using IBM SPSS Statistics 21.0 and MS-Excel 2010 software.
Descriptive, cross-sectional, correlation study carried out in an initial education center in Santa Elena, Ecuador, during 2016. The study population consisted of 125 parent-schoolchild binomials, the school children aged between three and five years. The observational method and the survey were used. The variables studied wereage, eating habits, school level, food acquisition, weight, height. The software IBM-SPSS-Statistics-21.0 was used for data analysis. The results were expressed in average, median, mode, standard deviation, maximum and minimum values. For the comparison between the groups, the Anova test of independent samples and the chi-square test were used, considering p bellow 0.05significant. To compare the nutritional status, the concordance and Kappa index were analyzed, considering a good value as being higher or equal than 0.80.
The measured index values were compared using IBM SPSS Statistics 21.0 (IBM Corp., Armonk, NY, USA) to calculate the means and standard deviations of the dental plaque removal rates of the artificial tooth surface of the bracket electric toothbrush, electric toothbrush, and manual toothbrush. Cronbach a was required found to be 0.176 times higher than that of 3the three items in order to see assess the changes in the measured index values were compared using IBM SPSS to calculate the means and standard deviations of the dental plaque removal rates of the artificial tooth surface of the orthodontic bracket electric toothbrush, electric toothbrush, and manual toothbrush. Cronbach a was required found to be 0.176 times higher than that of 3 the three items in order to see assess the changes in the dental hygiene after brushing with an electric toothbrush, an electric toothbrush, and a manual toothbrush. the three toothbrushes. One-way ANOVA was used to analyze the removal rate of differences in the dental plaque artificial tooth surface bacteria between removal rates among the fixed three types of toothbrushes, electric toothbrush, and manual toothbrush using. IBM SPSS Statistics 21.0 (IBM Corp., Armonk, NY, USA) was used for statistical analysis. Significance was set at p
The descriptive statistics of this experiment were a bracket electric toothbrush, a standard electric toothbrush, and a manual toothbrush. The amount of artificial plaque disclosing agent that remained on the tooth surfaces after brushing was 1.16750.36 for the fixed orthodontic bracket electric toothbrush, 2.51000.73 for the electric toothbrush, and 2.7525 0.79 for the manual toothbrush (Table 1).
The distribution of the variables including the age, nativethiol, disulphide, total thiol levels, and hematoma volumes of the patients was examined using the Shapiro-Wilks test. The mean standard deviation values were given for those variables with normaldistributions. In the presentation of the descriptive statistics of thevariables with abnormal distribution, the median value (interquartilerange [IQR]) was used. In addition the minimum and maximumvalues for each variable were specified and n (%) was used forcategorical variables as hematoma localisation. 2ff7e9595c
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