Are there unique facets of therapeutic alliance for users of digital mental health interventions? An examination with the eHealth Therapeutic Alliance Inventory

Therapeutic alliance (TA) is a well-established predictor of clinical outcomes in traditional psychotherapy. However, its association with outcomes in eHealth interventions has been inconsistent, which might be due to the absence of measurements specifically designed to capture TA in eHealth settings. The eHealth Therapeutic Alliance Inventory (ETAI) incorporates conventional as well as unique eHealth TA subscales, enabling to examine the contribution of new facets of TA beyond traditional concepts. This study investigates the predictive contribution of eHealth TA subscales compared to conventional TA subscales on clinical outcomes and evaluates the concurrent criterion validity of the ETAI. The study was conducted within the framework of a randomized controlled trial involving a 10-week digital parent training program aimed at addressing child disruptive behaviors. Parents were randomly assigned to either an enhanced-quality or a standard-quality program. Parents from 68 families completed the ETAI at five weeks' post-program initiation and at the post-intervention phase. The primary outcome was the improvement in child behavior, measured by the Eyberg Child Behavior Inventory. Positive Pearson correlations were found between all ETAI subscales covering unique eHealth TA aspects, measured at the 5-week time-point, and improvement in child behavior at post-intervention (r_s ≥ 0.23, p_s < 0.03). The conventional TA subscale showed no significant Pearson correlation with improvement in child behavior. When examining the unique contributions of ETAI-subscales to explain the improvement in child behavior, only ETAI-Perceived Emotional Investment subscale was found to have a unique contribution (β = 0.29, p = 0.019). In addition, scores on most ETAI subscales were significantly higher among parents using the enhanced-quality program compared with the standard program (Cohen's d_s > 0.48), reinforcing ETAI's criterion validity. The development of TA scales that incorporates unique eHealth TA subscales show initial promise in predicting outcomes. Further research is needed to better understand how different factors of eHealth TA relate to clinical outcomes across diverse clinical targets and programs.