Statistical Analysis

Data were analyzed using Statistica 8.0 (StatSoft, USA) software. The Kolmogorov-Smirnov test was undertaken to demonstrate that data were normally distributed. Comparisons between groups on demographic, questionnaire and neuropsychological measures were performed using one-way analyses of variance (ANOVA). Gender distribution was analyzed using χ2 test. For temporal discounting tasks, we assessed which of three different models (linear, hyperbolic and exponential) fit the data better by focusing on R² scores⁶⁰. Next, the rate at which the subjective value of a reward decays with delay was assessed through two indices: the area under the empirical discounting curve (AUC)⁶¹ and the slope of the regression line between subjective value and time intervals. In more detail, a negative slope value means that subjective values decrease as time delays increase, while a positive slope value means the opposite. A slope value equal to zero means that the participant’s subjective value is the same for each delay. Thus, higher scores on this index indicate lower discounting.

A repeated-measures analysis of variance (ANOVA) on AUC values was performed with Task (Food/Money) as a within-subjects variable and Group (high PS/medium PS/low PS) as a between-subjects variable. The same analysis was performed on the slope values. In the Liking task, a repeated-measures ANOVA on rating scores was performed with type of food (high-calorie/low-calorie) as a within-subjects variable and Group (high PS/medium PS/low PS) as a between-subjects variable. In the concurrent task, the rate at which participants are willing to work for snack foods was assessed through two indices: the number of key presses for the snack option for each schedule (FR2/FR4/FR8/FR16/FR32) and the individual slope, representing the trend of participants’ effort. Comparisons among groups in this task were performed using Mann–Whitney U-test.