Background: Therapeutic alliance has been well established as a robust predictor of face-to-face psychotherapy outcomes. Although initial evidence positioned alliance as a relevant predictor of internet intervention success, some conceptual and methodological concerns were raised regarding the methods and instruments used to measure the alliance in internet interventions and its association with outcomes. Objective: The aim of this study was to explore the alliance-outcome association in a guided internet intervention using a measure of alliance especially developed for and adapted to guided internet interventions, showing evidence of good psychometric properties. Methods: A sample of 223 adult participants with moderate depression received an internet intervention (ie, Deprexis) and email support. They completed the Working Alliance Inventory for Guided Internet Intervention (WAI-I) and a measure of treatment satisfaction at treatment termination and measures of depression severity and well-being at termination and 3- and 9-month follow-ups. For data analysis, we used two-level hierarchical linear modeling that included two subscales of the WAI-I (ie, tasks and goals agreement with the program and bond with the supporting therapist) as predictors of the estimated values of the outcome variables at the end of follow-up and their rate of change during the follow-up period. The same models were also used controlling for the effect of patient satisfaction with treatment. Results: We found significant effects of the tasks and goals subscale of the WAI-I on the estimated values of residual depressive symptoms (γ02=−1.74, standard error [SE]=0.40, 95% CI −2.52 to −0.96, t206=−4.37, P<.001) and patient well-being (γ02=3.10, SE=1.14, 95% CI 0.87-5.33, t198=2.72, P=.007) at the end of follow-up. A greater score in this subscale was related to lower levels of residual depressive symptoms and a higher level of well-being. However, there were no significant effects of the tasks and goals subscale on the rate of change in these variables during follow-up (depressive symptoms, P=.48; patient well-being, P=.26). The effects of the bond subscale were also nonsignificant when predicting the estimated values of depressive symptoms and well-being at the end of follow-up and the rate of change during that period (depressive symptoms, P=.08; patient well-being, P=.68). Conclusions: The results of this study point out the importance of attuning internet interventions to patients’ expectations and preferences in order to enhance their agreement with the tasks and goals of the treatment. Thus, the results support the notion that responsiveness to a patient’s individual needs is crucial also in internet interventions. Nevertheless, these findings need to be replicated to establish if they can be generalized to different diagnostic groups, internet interventions, and supporting formats.
Research Areas and Centers
- Academic Focus: Center for Brain, Behavior and Metabolism (CBBM)