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Spss win version 23.0

Manufactured by IBM

SPSS/WIN (version 23.0) is a statistical software package developed by IBM. It provides tools for data analysis, data management, and data visualization. The software is used for a variety of statistical procedures, including regression analysis, factor analysis, and cluster analysis.

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Lab products found in correlation

2 protocols using spss win version 23.0

1

Factors Influencing Nurse Retention Intention

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We conducted data collection from 1 to 31 August 2022. After obtaining permission to collect data from the head of the nursing department of the institution, a researcher or trained research assistant visited the participant in the ward and explained and distributed the questionnaire with written consent.
It took about 15 to 20 min to fill out the questionnaire and the completed questionnaire was collected in a sealed state. The study participants were offered small gifts.
The collected data were analyzed using the IBM SPSS/WIN (version 23.0) statistical program. As a result of confirming the normality of each variable, the absolute value of skewness was 0.14~0.83, which was two or less, and the absolute value of kurtosis was 0.24~0.66, which was seven or less. The data for this study turned out to be normal. We used descriptive statistics for the subjects’ general characteristics and degree of variables. We conducted an independent t-test, one-way ANOVA, and a post hoc analysis with the Scheffé test to determine the difference in the retention intention according to the general characteristics. We used Pearson’s correlation coefficient for the correlation between variables and conducted hierarchical multiple regression analysis to identify the factors influencing retention intention.
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2

Diabetes Self-management and Glycemic Control

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The collected data were analyzed using SPSS/WIN version 23.0 (Armonk, NY: IBM Corp). Descriptive statistics were used for the participants’ general characteristics, health literacy, self-efficacy, self-management, and HbA1c levels.
Before conducting data analysis, a Shapiro–Wilk test was performed to assess the normality of variable values. The results indicated that the assumption of normal distribution was not met. Therefore, to analyze the differences in HbA1c levels according to the participants’ general characteristics, the data were analyzed using either the Mann–Whitney U-test or Kruskal–Wallis test, with the post hoc test being conducted through the Mann–Whitney U-test. To control for the increased risk of Type I errors associated with multiple comparisons, a Bonferroni correction was applied. The adjusted alpha level for significance was set at 0.05 divided by the number of comparison groups. Moreover, Spearman’s rank correlation analysis was used to determine the correlation between the participants’ health literacy, self-efficacy, self-management, and HbA1c levels.
As the final step of the analysis, we sought to analyze the variable, HgA1c level, by categorizing it into two groups: the normal HbA1c group and the increased HbA1c group. To examine the relationships between HbA1c level and other variables, we applied the binary logistic regression analysis method.
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