Spss version 22.0 j for windows

Manufactured by IBM

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SPSS Version 22.0 J for Windows is a statistical software package developed by IBM. It provides tools for data analysis, data management, and report generation. The software is designed to work on the Windows operating system.

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SPSS 22.0 J for Windows SPSS version 22.0 for Windows SPSS for Windows version 22.0 SPSS 22.0.0.0 for Windows SPSS 22.0 for Windows SPSS version 22.0 Windows SPSS 22 for Windows SPSS 22.0 Windows 22.0 for Windows SPSS 22.0 version

5 protocols using spss version 22.0 j for windows

Antenatal Depression Risk Factors Analysis

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We performed two stratified analyses in which the participants were classified into two groups: “primipara and multipara” and “participants with a history psychiatric treatment and participants without a history of psychiatric treatment”. Hence, primipara means those who delivered the first offspring while participating in this study; multipara means those who had delivered once or more before participating in this study. The variables that were analyzed included risk factors for antenatal depression that were reported in our previous study [16 (link)].
Data were reported as “the mean (standard deviation)”. Statistical significance was set at p < 0.05, and all data analyses were performed using SPSS version 22.0 J for Windows (SPSS Inc., Tokyo, Japan).

Tachibana Y., Koizumi N., Akanuma C., Tarui H., Ishii E., Hoshina T., Suzuki A., Asano A., Sekino S, & Ito H. (2019). Integrated mental health care in a multidisciplinary maternal and child health service in the community: the findings from the Suzaka trial. BMC Pregnancy and Childbirth, 19, 58.

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COVID-19 Psychological Distress and Workplace Bullying

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We analyzed participants who answered all the questions. Partial correlation coefficients (prs) were calculated among variables adjusting for sex, age, marital status, and educational attainment.
Multiple linear regression analyses were used to examine the association between any COVID-19 related bullying or patient aggression and psychological distress adjusting for fear and worry about COVID-19 infection, work-related stressors, occupation, sex, age, marital status, and educational attainment. We conducted a similar multiple linear regression to examine the association between any workplace bullying related to COVID-19 or any aggression by customers/patients related to COVID-19, separately, and psychological distress, adjusting for fear and worry about COVID-19 infection, work-related stressors, sex, age, marital status, and educational attainment. In addition, stratified analysis among health care professionals who were living in areas with the national emergency announcement for COVID-19 and those who were living the other prefectures was conducted to test the interaction of living area. All analyses were conducted using SPSS version 22.0 J for Windows (SPSS, Tokyo, Japan).

Asaoka H., Sasaki N., Kuroda R., Tsuno K, & Kawakami N. (2021). Workplace Bullying and Patient Aggression Related to COVID-19 and its Association with Psychological Distress among Health Care Professionals during the COVID-19 Pandemic in Japan. The Tohoku journal of experimental medicine, 255(4).

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Statistical Analysis of Long-Term Outcomes

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Statistical analysis was performed using IBM SPSS Version 22.0 J for Windows (IBM Corp., Armonk, NY, USA). The chi-squared test, Fischer’s exact test, Mann–Whitney U test, Kruskal–Wallis test, and logistic regression analysis were used, as appropriate. Long-term outcomes were analyzed using the Kaplan–Meier method with the log-rank test and Cox proportional hazards regression model. Data are expressed as the median [interquartile range (IQR)] unless otherwise stated. P-values < 0.05 (two-tailed) indicate statistically significant differences.

Tanaka T., Suda K., Shibasaki S., Serizawa A., Akimoto S., Nakauchi M., Matsuoka H., Inaba K, & Uyama I. (2024). Safety and feasibility of minimally invasive gastrectomy following preoperative chemotherapy for highly advanced gastric cancer. BMC Gastroenterology, 24, 74.

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Statistical Comparison of Experimental Groups

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Values were expressed as the mean ± SE. Differences between the groups were determined using the unpaired t-test. SPSS version 22.0 J for Windows (IBM Japan, Tokyo, Japan) was used for all statistical analyses. The null hypothesis was rejected at the 0.05 level of probability.

Sato A., Sato S., Omori G, & Koshinaka K. (2022). Effects of Thiamin Restriction on Exercise-Associated Glycogen Metabolism and AMPK Activation Level in Skeletal Muscle. Nutrients, 14(3), 710.

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Analyzing the Impact of Older Adult Density on Life Satisfaction

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We analyzed Studies 1 and 2 in the same manner. The effect of area-level number of older adults per 100 residents on LSIA scores was analyzed using linear mixed-effect modeling. All analyses were computed using restricted maximum likelihood estimation in SPSS version 22.0J for Windows (IBM Japan Ltd., Tokyo, Japan).
First, we examined the unconditional association between the area-level number of older adults per 100 residents and LSIA scores without controlling for the area-and individual-level covariates, except for LSIA scores at baseline (T1) in the longitudinal analysis in Study 2 (Model 1). Second, the area-level SES condition and population density were added to the first model to examine the conditional association between the area-level number of older adults per 100 residents and LSIA scores (Model 2). In the next two models, we sequentially added the individual-level core variables (Model 3) and other individual covariates in addition to the core covariates (Model 4) as the fixed effect variables. In all models, intercepts of fixed (individual) and random (area) effects were included. In this study, p values less than 0.05 (two-tailed) were interpreted as being statistically significant for all analyses.

Saito T., Sugisawa H., Harada K, & Kai I. (2016). Population aging in local areas and subjective well-being of older adults: Findings from two studies in Japan. Bioscience trends, 10(2).

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