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Mean percentage reduction in eating disorder pathology and psychometric test scores were calculated and a 95% confidence interval for this presented. This was done at a group level and for responders and non-responders respectively. Responder status was defined as >35% reduction in EDE in accordance with the previously published literature in OCD and AN (Denys et al., 2010 (link), 2020 (link); Lipsman et al., 2017 (link)). The effect of time on outcome was calculated using a two-way repeated measures ANOVA and results of the nested double-blind study were analyzed using a paired t-test. Statistical significance level was set at p < 0.05 and all analysis was completed in SPSS 28 (IBM).

An independent sample t-test, one-way analysis of variance (ANOVA) test of significance, and multiple linear regression were used to examine the relation between the demographic characteristics and variables. A Pearson correlation analysis was used to compare correlations between variables. All statistical analyses were performed using IBM SPSS 28.

To summarize the characteristics of the respondents, a descriptive analysis was conducted. The comparisons between the different groups were assessed using Chi-square and Fisher’s exact tests. In addition, multiple logistic regression analysis was used to determine any variables associated with a lack of COPD knowledge. The data was processed using IBM SPSS 28 and a p-value < 0.05 considered statistically significant.

Data analysis was performed in IBM SPSS 28 (SPSS Inc., Chicago, IL, USA) at site level. Continuous variables are presented as means and 95% confidence intervals (C.I.), while categorical variables were expressed as number of cases (n), percentages and odds ratio (OR). The associations between continuous variables and healing were analysed by simple binary logistic regression, while the associations between categorical variables and healing were analysed with the Chi-square test (χ²). The level of significance was set at 0.05.
A multiple binary logistic regression model was used to test the association between relevant variables and healing outcome, adjusting for confounding variables.
The association between alveolar defect values and categorical variables was analysed with the Mann–Whitney U test and Kruskal–Wallis test. Finally, the association between different consequences and the use of TC was assessed using a multiple binary logistic.

SPSS 28 (IBM, Chicago, IL, USA) was used to analyze all data. The Kolmogorov–Smirnov test was used to examine the distribution of data from all experiments. All data were analyzed by two-way ANOVAs (betahistine × olanzapine), followed by a post-hoc Tukey test to perform multiple comparisons. If the data did not show a normal distribution, a nonparametric Mann–Whitney U test was used. Finally, the correlation among the measurements was analyzed by Pearson’s correlation test. Statistical significance was accepted when p < 0.05. Results were presented as the mean ± SEM. GraphPad Prism 7.04 (GraphPad Software Inc., San Diego, CA, USA) was used to create all graphs in this manuscript.

SPSS 28 (IBM, Armonk, NY, USA) and MPlus 8 (Muthén & Muthén, Los Angeles, CA, USA) were used to perform data analyses. SPSS was employed for descriptive analyses of the sample and of the study variables, internal consistency with Cronbach’s α, ANOVA, and exploratory factor analysis (for both psychometric properties of the instruments and the common method bias investigation). MPlus 8 was used to test the hypothesized multilevel random intercept model, with head nurses’ WE as Level 2 (leader/group level) predictor, while Level 1 (individual level) variables (TL, JS, and nurses’ WE) were decomposed into their latent variables at the between and within levels, in order to calculate also indirect effects [80 ].

The sample size of our study was calculated assuming the 30-day appendectomy rates in both NOM groups reported in the CODA trial as reference [13 (link)]. With a statistical power of 80% and alpha = 0.025 (one side test), 284 patients (142 per group) are required to demonstrate the non-inferiority of the outNOM treatment with a non-inferiority limit of 5%.
Continuous data are reported as median and interquartile range and mean with standard deviation, while categorical data are reported as number and proportion. Categorical variables have been compared by Chi-square test and continuous variables by Mann–Witney’s U test. Variables significantly associated with the treatment choice have been identified by multiple logistic regression model. Non-inferiority of outNOM was tested evaluating the upper limit of the 97.5% confidence interval of the 30-day appendectomy risk difference. Predictors of 30-day appendectomy were evaluated with a logistic regression analysis and shown as adjusted odd ratio along with 95% confidence intervals. Long-term risk for appendectomy has been evaluated by Kaplan–Meier method and compared with the log-rank test. Statistics were performed with SPSS 28 (IBM Corp. Released 2021. IBM SPSS Statistics for Windows, Version 28.0. Armonk, NY: IBM Corp).