The Appalachia Mind Health Initiative (AMHI): a pragmatic randomized clinical trial of adjunctive internet-based cognitive behavior therapy for treating major depressive disorder among primary care patients.

BACKGROUND: Major depressive disorder (MDD) is a leading cause of disease morbidity. Combined treatment with antidepressant medication (ADM) plus psychotherapy yields a much higher MDD remission rate than ADM only. But 77% of US MDD patients are nonetheless treated with ADM only despite strong patient preferences for psychotherapy. This mismatch is due at least in part to a combination of cost considerations and limited availability of psychotherapists, although stigma and reluctance of PCPs to refer patients for psychotherapy are also involved. Internet-based cognitive behaviorial therapy (i-CBT) addresses all of these problems. METHODS: Enrolled patients (n = 3360) will be those who are beginning ADM-only treatment of MDD in primary care facilities throughout West Virginia, one of the poorest and most rural states in the country. Participating treatment providers and study staff at West Virginia University School of Medicine (WVU) will recruit patients and, after obtaining informed consent, administer a baseline self-report questionnaire (SRQ) and then randomize patients to 1 of 3 treatment arms with equal allocation: ADM only, ADM + self-guided i-CBT, and ADM + guided i-CBT. Follow-up SRQs will be administered 2, 4, 8, 13, 16, 26, 39, and 52 weeks after randomization. The trial has two primary objectives: to evaluate aggregate comparative treatment effects across the 3 arms and to estimate heterogeneity of treatment effects (HTE). The primary outcome will be episode remission based on a modified version of the patient-centered Remission from Depression Questionnaire (RDQ). The sample was powered to detect predictors of HTE that would increase the proportional remission rate by 20% by optimally assigning individuals as opposed to randomly assigning them into three treatment groups of equal size. Aggregate comparative treatment effects will be estimated using intent-to-treat analysis methods. Cumulative inverse probability weights will be used to deal with loss to follow-up. A wide range of self-report predictors of MDD heterogeneity of treatment effects based on previous studies will be included in the baseline SRQ. A state-of-the-art ensemble machine learning method will be used to estimate HTE. DISCUSSION: The study is innovative in using a rich baseline assessment and in having a sample large enough to carry out a well-powered analysis of heterogeneity of treatment effects. We anticipate finding that self-guided and guided i-CBT will both improve outcomes compared to ADM only. We also anticipate finding that the comparative advantages of adding i-CBT to ADM will vary significantly across patients. We hope to develop a stable individualized treatment rule that will allow patients and treatment providers to improve aggregate treatment outcomes by deciding collaboratively when ADM treatment should be augmented with i-CBT. TRIAL REGISTRATION: ClinicalTrials.gov NCT04120285 . Registered on October 19, 2019.

Integrating Stakeholder Engagement With Claims-Based Research on Health Insurance Design and Bipolar Disorder.

Researchers increasingly recognize that stakeholder involvement enhances research relevance and validity. However, reports of patient engagement in research that relies on administrative records data are rare. The authors' collaborative project combined quantitative and qualitative studies of costs and access to care among U.S. adults with employer-sponsored insurance. The authors analyzed insurance claims to estimate the impacts on enrollee costs and utilization after patients with bipolar disorder were switched from traditional coverage to high-deductible health plans. In parallel, in-depth interviews explored people's experiences accessing treatment for bipolar disorder. Academic investigators on the research team partnered with the Depression and Bipolar Support Alliance (DBSA), a national advocacy organization for people with mood disorders. Detailed personal stories from DBSA-recruited volunteers informed and complemented the claims analyses. Several DBSA audience forums and a stakeholder advisor panel contributed regular feedback on study issues. These multiple engagement modes drew inputs of varying intensity from diverse community segments. Efforts to include new voices must acknowledge individuals' distinct interests and barriers to research participation. Strong engagement leadership roles ensure productive communication between researchers and stakeholders. The involvement of people with direct experience of care is especially necessary in research that uses secondary data. Longitudinal, adaptable partnerships enable colearning and higher-quality research that captures the manifold dimensions of patient experiences.