Abstract
OBJECTIVES: Digital mental health interventions have shown promise for alleviating various forms of psychopathology, including depression and anxiety. However, the mechanisms of such interventions remain largely unexplored. The purpose of this study was to investigate a potential mechanistic process through which one hybrid digital mental health intervention (i.e., the Digital Clinic) might operate. We hypothesized that emotion regulation (ER) self-efficacy at the treatment midpoint may mediate the relationship between alliance (i.e., therapeutic alliance and digital alliance) and outcome (i.e., co-morbid symptoms of depression and anxiety) at the treatment endpoint. METHODS: Data used in this study came from the Digital Clinic, a brief transdiagnostic telehealth treatment program augmented by a dual-purpose digital phenotyping and intervention smartphone app. Recruited primarily from primary care, participants were 82 adults (73% White, 64% cisgender women, mean age 41) receiving outpatient treatment in the northeastern United States. All constructs were measured with validated scales, including The Working Alliance Inventory-Short Revised (WAI-SR) for therapeutic alliance, the Digital Working Alliance Inventory (DWAI) for digital alliance, the PROMIS Self-Efficacy for Managing Emotions Short Form scale for ER self-efficacy, and the Patient Health Questionnaire Anxiety-Depression Scale (PHQ-ADS) for co-morbid symptoms of depression and anxiety. RESULTS: Significant reductions in co-morbid symptoms of depression and anxiety and significant increases in ER self-efficacy were found from baseline to treatment endpoint. Therapeutic and digital alliance at the midpoint each predicted reductions in co-morbid symptoms of depression and anxiety at the endpoint through ER self-efficacy, controlling for baseline scores. CONCLUSIONS: Findings suggest that ER self-efficacy may be a proximal predictor of clinical improvement that may be enhanced by therapeutic and digital alliance. Future controlled research is essential to improve knowledge of the mechanisms of digital mental health interventions and to enhance their effectiveness.