Spss software 23

All statistical analyses were performed using the SPSS software 23.0 (IBM, Chicago, IL, USA). All data were presented as mean ± S.D (standard deviation). Comparison of multiple groups was performed by one-way analysis of variance (ANOVA), and intergroup comparison was conducted by the LSD test. The Escape latency in the Morris water maze test was analyzed using ANOVA. P < 0.05 was considered statistically significant.

Continuous data are reported as median ± interquartile range (IQR) or mean ± standard deviation (SD). Patients served as their own control, and pre- and postoperative data were compared using the two-tailed, paired Student’s t test. Categorical demographic and baseline variables are reported as proportions or frequencies, and compared using Wilcoxon test for continuous outcomes and McNemar’s test for paired samples. A p value < 0.05 was considered statistically significant. Parameters of the univariate analysis with p < 0.05 were included in a multivariate logistic regression test to determine what independent variables might predict the clinical success of the surgical procedure. A p value < 0.05 was considered statistically significant. Statistical analyses were performed using SPSS software 23.0 (IBM, Armonk, New York, U.S.).

We expressed continuous variables as mean and measures of dispersion (standard deviation; SD). We reported categorical variables as a percentage. For analysis, we categorized the variables based on (a) gender (male/female), (b) age (≤43 or >43 years), (c) initial BMI (<40 or ≥40 kg/m²), (d) procedure type (restrictive or malabsorptive techniques), (e) PA status (inactive or minimally active/active), (f) MedDiet adherence level (low adherence ≤ 6 and medium–high adherence > 6 points), (g) depression status (none or minimal and mild–severe), and (h) %TBWL (≤25% vs. 25.1–39.9% vs. ≥40%). Bivariate analyses of proportionality of distribution of categorical variables Chi-square test (χ²). For continuous variables, we used the Kolmogorov–Smirnov test to check that the variables were normally distributed. For comparisons of normally distributed variables, we used the T-Student test or ANOVA. For comparisons of non-normally distributed variables, we used the Mann–Whitney or Kruskal–Wallis tests.
We performed multivariable regression analysis to study the relationship between changes in PSC and MSC scores as dependent variables and age, gender, %TBWL, changes in PA, depression status, and initial summary component values as independent variables.
We performed statistical analysis using IBM SPSS Software 23.0. p < 0.05 was considered significant.

Statistical analyses were performed using SPSS Software (23.0) (IBM, New York, USA). The level of significance was calculated by means of the chi-square-test (Χ² test). The level of significance was set at α = 0.05.

Comparative statistical analyses between the PBT group and DBT group were performed in SPSS software 23.0 (IBM Company, Chicago, United States). Measurement data were expressed as mean ± standard deviation. Unpaired t test was used for comparisons between the two groups. Count data were analyzed using χ2 test. Statistical significance was set at p < 0.05.

Data were analyzed using IBM SPSS software 23.0(IBM Corp., Armonk, NY, USA). The mean, standard deviation, skewness, kurtosis, and reliability (Cronbach’s alpha) of each item were computed using SPSS 23.0. Normality of the data was tested with skewness and kurtosis, and the reliability of the items was determined by Cronbach’s alpha. Additionally, correlation analysis (Pearson’s correlation coefficient), model fit (comparative fit index (CFI), root mean square error of approximation (RMSEA), standardized root mean square residual (SRMR)), and path analyses among the variables were conducted using AMOS 23.0 (Build 1607, IBM Corp., Armonk, NY, USA).