Predicting post treatment client satisfaction between behavioural activation for depression delivered either in-person or via home-based telehealth

Abstract

Introduction: Treatment engagement, adherence, cancellations and other patient-centric data are important predictors of treatment outcome. But often these data are only examined retrospectively. In this investigation, we analysed data from a clinical trial focused on innovative delivery of depression treatment to identify which patients are likely to prefer either in-home or in-person treatment based on pre-treatment characteristics. Methods: Patient satisfaction was assessed in a trial of individuals with depression treated using identical behavioural activation therapy protocols in person or through videoconferencing to the home (N = 87 at post treatment: 42 in-person and 45 in-home participants). The Client Satisfaction Questionnaire was administered at the end of the treatment. A Tobit regression model was used to assess moderation using treatment assignment. Regression lines were generated to model treatment satisfaction as a function of treatment assignment and to identify whether and where the groups intersected. We examined the distributions of the contributing moderators to the subsets of participants above and below the intersection point to identify differences. Results: While no significant differences in patient satisfaction were observed between the two groups, or between patients receiving treatment by different providers, baseline characteristics of the sample could be used to differentiate those with a preference for traditional, in-office care from those preferring in-home care. Discussion: Participants who were more likely to prefer in-home care were characterized by larger proportions of veterans and lower-ranked enlisted service members. They also had more severe symptoms at baseline and less formal education. Understanding client reactions when selecting treatment modality may allow for a more satisfying patient experience.