Statistical Analysis
inversion transformation
The data analyses were performed using SPSS Statistics version 21 (IBM Corporation, Armonk, New York) and RStudio (version 1.1.447; R version 4.0.4). All analyses were performed with a two-tailed significance level of A 2 condition (conditioned versus control) × 2 group (healthy versus patient) multivariate analysis of variance was used to compare the groups on the baseline characteristics: age, body mass index, baseline glucose, insulin and C-peptide values, and baseline hunger.The lmer function of the nlme package in R (R Core Team, 2013) was used for the liner mixed-effects model analyses. Mixed-effects models were applied to the data that included repeated measures (glucose, insulin, C-peptide, hunger, and approach-avoidance task). In all models, the intercept was allowed to vary randomly across participants.The multilevel structure of the data was defined by measurement time (level 1) nested in participants (level 2). Parameters were estimated using the full-maximum likelihood procedure. In all models, the intercept was allowed to vary randomly across participants. Random slopes did not improve the fit of the models, and therefore, they were removed from the final analysis. The assumption of linearity was checked for each model by plotting the model residuals versus the predictor, and visually inspecting the plots. Homogeneity of variance was checked by the Levene test. Each model was also checked for the normal distribution of its residuals by looking at QQ plots created with Lattice package. In case of violation of any of the assumptions, the data were transformed. The following variables were transformed because of the violation of the homogeneity of variance and nonnormal distribution of the residuals: logarithmic transformation was applied to glucose levels on day 2 and C-peptide levels on day 1 and day 2, the square root transformation was applied to the insulin levels on day 2, and inversion transformation was applied to the reaction time in the approach-avoidance task.To examine the effects of intranasal insulin administration on blood glucose levels on day 1, a mixed model was performed with day 1 glucose levels as a dependent variable, condition (conditioned versus control), group (healthy versus patient), measurement time (0, 15, 30, 45, 60, 75, or 90 minutes after the first spray administration), baseline glucose levels (measured before the first spray administration), and the interactions between these variables as predictors. To examine the effects of conditioning on blood glucose levels, the same mixed-models analysis was performed but with the measures of day 2. The same analyses were run with insulin, C-peptide, and hunger for each day separately to investigate whether intranasal insulin and conditioning affected these measures. In case an interaction factor was significant, separate models were run for either two groups (healthy and patients) or conditions (conditioned and control), depending on which of the factors was included in this interaction. All mixed models were repeated with sex as a predictor in an exploratory analysis to investigate whether sex affected the relationships between the variables. The effect sizes (Cohen To examine whether intranasal insulin and conditioning affected the approach tendencies toward food, two mixed models were performed. The first model included condition (conditioned versus control), groups (patient versus healthy), day (1 versus 2), stimulus type (food versus object), movement type (pull versus push), and the interaction between these factors as predictors and reaction time as a dependent variable. The second model included the same predictors but movement force as a dependent variable.A 2 condition (conditioned versus control) × 2 group (healthy versus patient) factorial analysis of variance was used to compare the groups on food consumption during the bogus test: analyses were run separately for day 1 and day 2 with calories eaten as an outcome measure.A 2 condition (conditioned versus control) × 2 group (healthy versus patient) factorial analysis of variance was used to compare the groups on their memory scores (immediate recall, learning, percentage forgetting). As three separate memory outcomes were used in the analysis, Bonferroni corrections were applied and To evaluate success of the blinding, 