Fig. 2: SHAP values for Aim 1: main outcome.

SHAP values for each moderator and the corresponding binary value key table. Features with positive SHAP values contribute positively to the outcome, while those with negative values have a negative effect. Blue indicates lower values for each moderator, whereas red indicates higher values. When the values are binary, the original coding determines classification to “lower” and “higher”. For instance, the “diagnosis” (method) feature was coded as “1” for clinical evaluations and “2” for self-report questionnaires; therefore, clinical evaluations are shown in blue, and self-report questionnaires are in red. Thus, the graph indicates that participants with clinical diagnoses are expected to gain more improvement than those with sub-clinical symptom levels. However, this moderator’s overall importance for prediction is minimal, as indicated in Fig. 1. For continuous values, color coding is also continuous without clear cut-offs. See Fig. 1 for the abbreviations of all moderators.