*2.4. Statistical Methods*

Statistical analysis was conducted in R using the meta, metaphor, and dmetar packages. We followed the guide published by Harrer et al. to conduct the analysis [30]. A random-effects model was employed for the meta-analysis to account for differences in study populations. We used the DerSimonian–Laird estimator for τ2 (variance of true effect magnitude distributions), as it is the most widely used estimator. The studies included in the quantitative analysis used different depression rating scales. Therefore, we computed standardized mean differences so that the studies could be compared. We also calculated heterogeneity (I2) of the studies in R. The differential efficacies of the various stimulation targets were compared with mixed-effects meta-regression. R was used to generate funnel plots and conduct Egger's test. Means are presented with their corresponding standard deviations. A *p*-value < 0.05 was considered statistically significant.
