2.4. Statistical Analysis
weight gain, weight loss
Statistical analyses were conducted with IBM SPSS (version 28) with statistical significance defined at The changes within and between intervention conditions (SELF, MOD-PA, HIGH-PA) for weight, physical activity, dietary intake, and scales of the Three-Factor Eating Inventory were analyzed using a separate one-way analysis of covariance (ANCOVA) for each variable. The ANCOVAs controlled for the baseline value of the variable being analyzed, self-identified biological sex, and self-identified race/ethnicity. Significant main effects for comparisons of intervention conditions (SELF, MOD-PA, HIGH-PA) were probed with pairwise comparisons. A similar approach was implemented for the analysis of percent weight change with the ANCOVA controlling for self-identified biological sex and self-identified race/ethnicity. The statistical significance of the change for each intervention condition was evaluated using the 95% confidence interval (95% CI), with a 95% CI not including zero deemed to be statistically significant.Subjects were categorized based on the change in weight from baseline to 6 months. Categories include weight gain (WT-GAIN: weight gain of >3% of baseline weight), weight stability (WT-STABLE: weight change of ±3% of baseline weight), and weight loss (WT-LOSS: weight loss > 3% of baseline weight). The criterion of a 3% change in weight to define the categories is based on prior studies that have used this to define weight stability [