Spss v27

The following software was used for analysis: Calypso online platform (V8.84) [30 (link)], SPSS V.27 [31 ] (IBM Corp. Released 2020; IBM SPSS Statistics for Windows, Version 27.0. Armonk, NY: IBM Corp); and Graphpad Prism v. 5.04 (GraphPad Software, San Diego, CA, USA, www.graphpad.com accessed on 1 April 2021). Redundancy analysis (RDA) was applied to study the statistical effect of breastfeeding practices on breast milk microbiota. The differences between the groups were visualized by the discriminant of principal components analysis (DAPC) at the amplicon sequence variant (ASV) level and the Adonis test was achieved based on the Bray-Curtis distance.
T-test and Mann-Whitney analysis were used depending on data normality assessed by Kolmogorov-Smirnov and Shapiro-Wilk test (Graphpad Prism v5.04). Spearman correlations between relative abundances of bacterial and maternal age were using RStudio [32 ]. Multivariable Poisson regression models adjusted by covariables were run in SPSS V.27 to assess differential abundance at the genus levels (dependent variable), variable that consists of count data, according to pre-gestational BMI, weight gain, and breastfeeding practices (independent variable). The covariables that were used to adjust each model are specified in the description of their results.

In phase 3, the participants will be invited to complete the PBQ and MIRI before implementing the co-designed intervention (pretest). The PBQ and MIRI will be repeated after the co-designed intervention (posttest) [71 ]. The PBQ and MIRI will be completed by each mother on the same day. The amount of time between the pre- and posttest will be determined depending on the type of intervention developed. All participants will be matched to their pre- and postresponses as well as to their survey by allocating each participant a confidential code at the commencement of the study. The data will be analyzed using SPSS V.27 and presented as simple descriptive statistics. Paired t test will be used to demonstrate a change in maternal-infant bonding and responsiveness, as this test is designed to assess differences at 2 separate time points between the one group [62 ].
In addition, mothers and midwives who engage in the co-designed intervention will be provided with the purpose-designed surveys to evaluate satisfaction and experience with the intervention. The data will be analyzed using SPSS V.27 and presented as simple descriptive statistics. Simple descriptive statistics will describe, organize, and summarize the raw data, providing meaning through numerical data [62 ]. Open-ended questions will be analyzed using thematic analysis [56 ].

Continuous variables were conveyed as a mean ± standard deviation or median with an interquartile range (IQR), and categorical variables as a number and percentage. The Student’s t-test and, where applicable, the Mann–Whitney U-test and Wilcoxon signed rank test were performed to compare continuous variables. The chi-squared test was applied to compare categorical variables. A p-value of <0.05 was accepted as statistically significant. Univariate and multivariate regression analyses were performed, followed by a multivariate Cox regression analysis (SPSS v27, IBM Corp., Chicago, IL, USA) for variates associated with mortality, and the proportionality of hazard assumption using Cox regression was also tested (SPSS v27, IBM Corp., Chicago, IL, USA).

Please see Habermann et al. in 2022 for a previous description of statistical approaches in the underlying project [18 (link)]. We compared characteristics and outcomes between patients with centrally located and peripherally located tumors. When comparing baseline and SBRT characteristics, we used Pearson’s Chi-squared test and the Mann–Whitney U test (SPSS v. 27, IBM, Armonk, NY, USA). In survival analyses, the endpoints were overall survival (OS, event: patient death due to any cause), progression-free survival (PFS, event: locoregional or distant progression and patient death), local progression-free survival (LPFS, events: local progression and patient death due to any cause), and locoregional control (LRC, events: local or regional relapse). The survival times were calculated from the first day of SBRT. We used Cox regression analysis (SPSS v. 27, IBM, Armonk, NY, USA). Additionally, the Kaplan–Meier curves with log-rank statistics were generated using the plugin, KMWin v 1.53 [20 (link)]. p-values < 0.05 were considered statistically significant.

Multivariate statistical analysis was performed using SIMCA-P+ v.16.0.1 (Umetrics, Umeå, Sweden), and a PLS-DA score plot was used to visualize differences between sample groups. The differences between the experimental data were compared using one-way analysis of variance (ANOVA) with Duncan’s test (p < 0.05) using SPSS v.27.0 (SPSS Inc., Chicago, IL, USA). Pearson correlation coefficients between metabolites, sensory qualities, and functional properties were calculated and visualized through heatmaps created using GraphPad Prism 9.0 (GraphPad, San Diego, CA, USA).