Anxiety Paid Clinical Trials in Massachusetts

Approximately 30% of children will experience an anxiety disorder, making anxiety the most common mental health problem among children in the United States. However, few children receive treatment and even our most effective anxiety treatments leave up to half of children in need of additional intervention. Despite the well-established role of parent anxiety in transmitting and maintaining child anxiety, the lack of data on specific parent mechanisms underlying the intergenerational transmission of anxiety is a critical barrier to informing novel targets of personalized treatments. Consistent with NIMH's Strategic Plan, Objective 2.2 to understand risk factors and behavioral indicators of mental illness across the lifespan and to identify novel intervention targets based on knowledge of psychological mechanisms, the current study focuses on interpretation bias, the tendency to perceive threat in ambiguous situations. The overall objective of this project is to empirically test a theoretical model of the intergenerational transmission of anxiety focused on parent interpretation bias as a root cause. Our specific aims are to test theorized effects of parent interpretation bias on (1) parent behavior and (2) child interpretation bias and (3) evaluate potential moderators to refine theories of intergenerational transmission of anxiety and inform future personalized interventions. Our central hypothesis is that parent interpretation bias influences child interpretation bias through its effects on maladaptive, anxiety-promoting parenting behaviors, such as accommodation and modeling of avoidant coping. To test this hypothesis, we will randomize 300 parents of children ages 7-12 to complete four weeks of a smartphone delivered interpretation bias manipulation vs. a self-assessment smartphone app condition. The interpretation bias intervention teaches parents to interpret ambiguous situations in a non-threatening manner via quick, repeated practice and corrective feedback. Before and after completing their randomly assigned condition, parent-child dyads will complete self-report and behavioral tasks designed to elicit anxiety-promoting behaviors from parents depending upon their interpretation of the ambiguous situation (speech and puzzle tasks). Parents will also complete Ecological Momentary Assessment (EMA) of parenting behaviors to capture the time course of effects. Finally, we will examine downstream effects of the interpretation manipulation on child interpretation bias at pre- and post- visits. We will test moderators (e.g., parent anxiety and gender) to refine theories of intergenerational transmission of anxiety and inform future personalized interventions. The long-term goal of this work is to inform personalized, mechanism-focused interventions to improve mental health outcomes for anxious children and their parents. Future studies will translate knowledge gained from this project into a scalable treatment that can be implemented entirely remotely via smartphone thereby increasing access to care Read Less

TRIAGE-Psych is a survey study designed to assess potential participants' eligibility to screen for industry-sponsored psychiatry clinical trials. Read Less

The purpose of this study is to test the feasibility and efficacy of intervening with 2-year-old children with elevated temperamental Fear and/or Shyness or 3-year-old children with elevated anxiety and their parents, using a parent-child Cognitive Behavioral Therapy (CBT) protocol to reduce anxiety disorders and maintain reduced anxiety at one-year follow-up. Before the COVID-19 pandemic, study visits and treatment sessions were conducted in office. Now all visits and treatment sessions are conducted remotely. Read Less

There are few treatment options available for patients once they have failed standard psychopharmacological therapy for generalized anxiety disorder. Existing brain stimulation methods such as rTMS fail to target deep brain structures associated with anxiety disorders; structures such as the amygdala. In this double-blind sham-controlled clinical trial, the investigators propose to establish baseline severity of anxiety in 48 patients, then deliver eight treatments over four sessions of focused ultrasound stimulation to the amygdala. Anxiety severity will be assessed using standard psychometric scales after each session, and at follow-ups. Read Less

Digital mental health interventions are a cost-effective and efficient approach to expanding the accessibility and impact of psychological treatments; however, little guidance exists for selecting the most effective program for a given individual. In the proposed study, decision rules will develop for selecting the digital program that is most likely to be the optimal intervention for each user. These treatment recommendations can be implemented in the context of large healthcare delivery systems to improve the delivery of digital mental health interventions at scale. The overarching aim of the current study is to better understand for whom and how leading digital interventions work in a large healthcare setting. The study builds on the existing literature and follows expert recommendations by using machine learning (ML) methods to develop precision treatment rules (PTRs) for three leading digital interventions for emotional disorders (e.g., anxiety, depression, and related mental health disorders). Specifically, ML methods will be used to develop PTRs to optimize clinical outcomes and associated intervention engagement. This study will leverage a unique partnership between Boston University (BU), SilverCloud Health (SC)--a leading provider of digital mental health care--and Kaiser Permanente (KP)--one of America's leading health care providers. A clinical trial (RCT) will be conducted to evaluate the relative effectiveness of three distinct empirically supported digital mental health interventions (from SC's existing library of programs) in a sample recruited from KP primary care and other clinical settings. Data from this trial will be used to develop theoretically and empirically informed, reliable selection algorithms for managing treatment delivery decisions. Algorithms will be validated in a separate "holdout" dataset by examining whether allocation to predicted optimal treatment is associated with superior outcomes compared to allocation to a non-optimal treatment. The role of user engagement will be determined, and other mechanisms in treatment outcome. Read Less

The collection of patient self-report and diagnostic data will allow us to examine the efficacy of the treatment delivered in the McLean Anxiety Mastery Program. Using data gathered through routine clinical care, the investigators seek to explore whether patients in treatment show improvements from admission to discharge, compared to patients on the waitlist, and whether these gains are maintained three months post-discharge. The following are included as examples of some of the study's hypotheses. Read Less