The data were analyzed using SPSS/WIN version 25.0. The status of the inpatients with scabies by provider type was calculated by frequency and percentage, and the general and treatment characteristics of the inpatients with scabies were analyzed using the chi-square test (χ2 test). The statistical significance level for the data was set at p < 0.05.
Spss win version 25
Manufactured by IBM
Sourced in United States
SPSS WIN version 25.0 is a statistical software package designed for data analysis. It provides a comprehensive set of tools for data management, analysis, and reporting. The software is widely used in academic, research, and business settings.
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Lab products found in correlation
5 protocols using spss win version 25
1
Scabies Inpatient Management Analysis
2
Factors Affecting Adolescent Obesity in Urban and Rural Areas
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In this study, out of 62,323 students in the sample school, students who answered incorrectly or who did not participate were excluded, and a total of 60,040 students were analyzed. None of the variables in this study had missing values and a normal distribution was assumed. The data were analyzed using SPSS WIN version 25.0 (SPSS Inc., Chicago, IL, USA), and the significance level of the statistics was set to p < 0.05. To compare the demographic characteristics, the socioeconomic characteristics, health behavior, and health education of urban and rural adolescents, frequency analysis and χ2-test were performed. Besides this, Pearson correlation analysis was performed on all variables to analyze the correlation between variables. In this study, after analyzing differences in demographic characteristics, socioeconomic characteristics, health behavior, and health education, a multinominal logistic regression analysis was performed with only significant p < 0.05 data. Multinominal logistic regression analysis was performed to identify the factors affecting obesity in urban and rural areas, and the significance level was set to p < 0.05. Furthermore, we performed a multinominal logistic regression analysis to determine the effect of each variable with all variables calibrated for overweight.
3
Factors Influencing Nurses' COVID-19 Infection Control
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Data analysis was conducted using SPSS WIN version 25.0. First, participant characteristics and levels of variables were analyzed using descriptive statistics. The normality test was verified by the Shapiro–Wilk test, skewness, and kurtosis. Second, the differences in infection control practices according to general characteristics were analyzed using the t-test and one-way analysis of variance. A Mann–Whitney test was used if normality was not tested. Finally, a multiple regression analysis was performed to identify the factors that affected nurses’ COVID-19 infection control practices.
4
Examining Couples' Health Behaviors in COVID-19
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Data were analyzed using SPSS Win version 25.0 and AMOS version 25.0 programs (IBM Corp, Armonk, NY, USA). Descriptive statistics were used to summarize the sample characteristics and the study variables. We used structural equation modeling using path analysis to test actor and partner effects of fear of COVID-19, depression, PTG, and marital adjustment on the HPB of couples. The correlations between the variables were analyzed using Pearson’s correlation coefficient. To verify the dyadic modeling, chi-square test (χ2), χ2/df, Standard Root Mean Squared Residual (SRMR), Tucker-Lewis Index (TLI), Comparative Fit Index (CFI), and Root Mean Square Error of Approximation (RMSEA) were used. In this study, a good model fit [53 (link)] was defined by the following criteria: SRMR < 0.08, RMSEA ≤ 0.06, and CFI and TLI ≥ 0.95.
5
Evaluating COVID-19 Knowledge and Confidence
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The collected data were analyzed using SPSS/WIN Version 25.0 (IBM Corporation, Armonk, NY, USA). Participants’ general characteristics were analyzed with descriptive statistics. Homogeneity in general characteristics was tested using the χ²-test and Fisher’s exact test. Baseline normality of the dependent variables was analyzed using the Kolmogorov–Smirnova test. For COVID-19 knowledge that fulfilled the pre-normality assumption of dependent variables for the experimental and control groups, an independent t-test was used to evaluate the effectiveness of the program. Practice confidence, clinical decision-making confidence, and anxiety that failed to fulfill the normality assumption was subjected to the Mann–Whitney U test, a nonparametric test, to evaluate the effectiveness of the program.
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