View clinical trials related to Anxiety Disorders.
Filter by:Taking prescription opioids for pain together with benzodiazepines for the treatment of anxiety disorders is not recommended by the U.S. Food and Drug Administration (FDA) because of the elevated risk of serious complications, including fatal overdose. However, this concurrent prescription use continues to be prevalent, likely due to the high comorbidity between pain and anxiety disorders. Efforts are urgently needed to reduce benzodiazepine use among patients taking opioids. Cognitive behavioral therapy (CBT) is a first-line treatment for anxiety disorders, and represents a safer and more effective treatment for anxiety disorders compared to benzodiazepines. The proposed study aims to make minor adaptations to a CBT protocol to facilitate benzodiazepine tapering and to then conduct a 2-arm randomized clinical trial with primary care patients who receive benzodiazepine and opioid prescriptions. Participants will be randomized to receive a telehealth-delivered intervention consisting of a gentle, 12-week benzodiazepine taper (BZT) with either CBT or a health education control (HE). Participants will be assessed at baseline, several points throughout treatment, at post-treatment, and at a 2-month follow-up assessment on benzodiazepine use, opioid use, and anxiety symptoms. Should CBT + BZT outperform HE + BZT, this intervention could make a significant impact by reducing major consequences of concurrent use of opioids and benzodiazepines, including mortality.
The R61 will include two CBD dose levels vs placebo (PBO) and examine potential engagement with two primary targets in a 3-week randomized controlled trial design. Willing and eligible subjects will be randomized to one of three randomized double-blind treatments (n = 20 each group): 1) CBD 800 mg (400 mg twice daily), 2) CBD 400 mg (200 mg twice daily), or 3) PBO twice daily for three weeks. Participation is estimated at approximately 1 month from end of screening to endpoint for the primary R61 study period. This includes screening, baseline, week 2 stress task, Week 3 2-day imaging paradigm, and clinical safety assessments at weeks 2 and 3.
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.
This is a randomized effectiveness/implementation trial comparing a 24-week neurology-based collaborative care intervention to usual neurology care among 60 adults with epilepsy.
This study is a clinical trial that evaluates what drives patient engagement and tests the impact of two strategies-automated motivational push messaging and coach support-to improve engagement with an evidence-based mobile app intervention for depression and/or anxiety.
The present study examines whether a self-help app can reduce symptoms of social anxiety disorder.
This study aims to pilot a world-first intervention, a mental health intervention augmented for children indicated with developmental language disorder (DLD). It serves as a proof-of-concept of how existing observational studies on these topics at the Centre for Research in Child Development (c.f. Tran-Sen; Gibber) can be translated into interventions. Mental health problems here are defined as anxiety type problems of social anxiety, specific phobia, separation anxiety and generalised anxiety. DLD is defined as a marked difficulty in oral language in the absence of biomedical causes (Bishop et al., 2017). This randomised pilot answers three uncertainties in preparation for a future definitive randomised control trial (RCT).
Perinatal Mood and Anxiety Disorders (PMADs) encompass a range of mental health disorders that occur during pregnancy and up to one year postpartum. Approximately 13% of women experience PMADs. This rate doubles for those with adverse perinatal outcomes (APO) and triples in Black women. Recent research points to racism as one significant source of these health disparities. Cultural adaptations to improve communication with providers decrease rates of depression in minority patients as well as improve adherence to treatment, insight and alliance. Discrimination stress and worries about experiencing medical consequences are thought to increase systemic inflammation, a mechanism known to drive mental and physical symptoms. Inflammation has been implicated in both PMADs and APO, suggesting a shared underlying etiology. Evidence from our work suggests that inflammation contributes to the pathophysiology of PMADs. The proposed pilot randomized control trial will allow the investigators to build on promising preliminary results and identify whether our culturally relevant mobile Health (mHealth) intervention is effective in improving outcomes among Black pregnant women randomized to the intervention compared to a control group. The culturally relevant modules include building communication and self-advocacy skills and provide a support network. The primary objective of this research is to provide guidance for clinical care of Black women during the perinatal period, with the goal to improve mental health and physical health outcomes. A secondary goal is to examine novel inflammatory signatures that change as a function of the intervention to reduce PMADs in this population. As inflammation may be diagnostic of PMADs, identification of its role may shed light of potential intervention targets and provide critical knowledge to improve women's long-term health. PMAD symptoms will be assessed prospectively in 150 Black pregnant women, half of whom will be randomized to receive the culturally relevant mHealth intervention. The investigators hypothesize that women in the intervention group will have reduced rates of PMADs and APOs, an increase in adherence to mental health treatment and will report increased self-advocacy skills, increased communication with providers, and reduced levels of discrimination related stress. Participants will also have improved biological risk indicators including lower circulating C-reactive protein and a transcription profile of differentially expressed inflammatory genes, marked by a decreased activity of inflammatory transcription factors from blood spots. Given the high burden of both PMADs and APOs among Black mothers and the numerous consequences on maternal and child outcomes, it is imperative that investigators develop and implement effective interventions, and test the biological mechanisms that might drive these effects. This work is interdisciplinary, building on a network of community advocates to implement a novel mHealth intervention informed by real world experiences designed to enhance self-advocacy, reduce stress and prevent adverse outcomes
The current study examines the effectiveness of the StayFine app for relapse prevention of anxiety or depressive disorders in youth using a randomized controlled trial. In addition, ecological momentary assessment (EMA) is used to explore fluctuations in emotions, psychological factors as predictor of the intervention effect and potential differential mechanisms of change. A total of 254 healthy youths remitted from an anxiety and/or depressive disorder, aged 13-21 years old, will be recruited for the study. Participants will be randomized to either 1) use the StayFine app exclusively for monitoring, or 2) use the StayFine app for monitoring and interventions supported by an expert patient. Stratification blocks are of random size and depend on previous episodes (1/2/3 or more) and previous treatment (yes/no). The intervention is based on the well-established Preventive Cognitive Therapy (PCT) for relapse prevention for adults and Cognitive Behavioral therapy adapted for the relapse prevention phase, both supplemented for anxiety and adolescents. In both conditions adolescents monitor their symptoms five times in three years and feedback and treatment advice is given in case of relapse. The primary outcome will be time to relapse. Secondary outcomes are (core) symptoms of depression and anxiety, number and duration of relapses, global functioning and quality of life. Mediators and moderators will be explored. Exploratory endpoints are monitoring and wearable outcomes.
This study will aim to test whether specific neural circuitry changes, proposed on the basis of a neurocognitive model of anxiety, are a mechanism of action for Cognitive Behavioural Therapy (CBT) interventions. This study aims to provide a theoretical model of the neurobiological mechanisms of CBT's therapeutic effect, where there currently is none, and potentially allow for more targeted/specific approaches to anxiety disorders following the identification of key CBT mechanisms. The ultimate aim is to improve the efficacy of CBT, and more generally, psychological interventions for anxiety disorders.