View clinical trials related to Anxiety Disorders and Symptoms.
Filter by:This project addresses the disproportionate morbidity and mortality associated with mental and behavioral health problems in American Indian and Alaska Native communities. Access to culturally competent and effective behavioral health services is limited in many of these communities. The investigators aim to address this gap by testing the effectiveness of a trans-diagnostic secondary prevention program, Family Spirit Strengths (FSS) that can be embedded within home visiting services. The FSS program is a skills-based program that incorporates elements of evidence-based practice, the Common Elements Treatment Approach (CETA), and materials informed and developed based on an Indigenous advisory group. The FSS program aims to help participants build self-efficacy and coping skills, as well as build stronger connections to others, the participants' community, and cultural resources. The investigators will use a randomized controlled trial, whereby half of the participants will receive FSS and the other half will receive an evidence-based nutrition education program. The investigators' study is grounded in participatory processes and led by a team of Indigenous and allied researchers.
Anxiety and anxiety-related disorders frequently co-occur with alcohol use problems resulting in an enormous humanitarian and economic cost to society. The proposed research will use digital technology to examine person-specific risk factors predicting problematic alcohol use in individuals vulnerable to anxiety and anxiety-related disorders and will use this information to design a personalized intervention for individuals seeking psychological treatment. Results from this research will integrate output from novel and innovative digital technology methods into psychotherapy, advancing research on personalized treatment and prevention efforts.
This study aims to assess a mobile iPhone app called MAYA for use in middle-aged and older adults with anxiety or mood disorders. The MAYA app is designed to teach coping skills for anxiety and depression that are drawn from cognitive behavioral therapy. Participants will be asked to use the app for at least two days a week, 20 minutes on each day, for six weeks. Participants will have weekly check-ins as well as longer assessments at the beginning of the study, week 3, week 6 (end of treatment), and week 12 (follow up). During assessments, participants will answer brief questionnaires designed to assess their symptoms and impressions of the app. The main hypotheses of the study are that participants will complete most of the assigned sessions and that they will rate their impressions of the app highly. The secondary hypotheses are that symptoms of depression and anxiety will decrease with use of the MAYA app.
This study aims to compare the effectiveness of a standard mobile iPhone cognitive behavioral therapy program to a personalized mobile iPhone cognitive behavioral therapy program that introduces new skills over a shorter period of time. Participants will use the Maya app for two days per week, at least 20 minutes per day, for six weeks. Assessments will include a weekly check in with a member of the research team, questionnaires, and optional magnetic resonance imaging (MRI) and electroencephalographic (EEG) recordings at the beginning and end of the 6-week intervention. The investigators think that that the less burdensome personalized program will be just as effective at improving symptoms of anxiety and depression as the general program.
This study is exploring an animated learning resource that could be used online to promote mental health. It is computer based and delivered in a single session, lasting 30 minutes. It teaches young people about thoughts, feelings, personality and the brain, it includes ideas about "mindsets" - or beliefs about the brain - which may be helpful in day-to-day life. The investigators will use social media to recruit 14-18-year-olds to take part in our research. They will be randomly put into one of two groups - either a group who receive the online session first or a group who receive the session later (at the end of the study). The animated learning resource aims to promote and protect mental health. The investigators predict it might have some benefits for emotional wellbeing, though the investigators do not know for certain. Young people who take part might learn something new or find it rewarding to know they have been part of research which could be used to help promote mental health. It is important to know that this is a research study and not a form of treatment for mental health problems.
The study aims to evaluate the effectiveness of the transdiagnostic program Super Skills for Life (SSL). This protocol targets children aged 8 to 12 with emotional problems (anxiety, depression, low self-esteem, and lack of social skills). SSL consists of eight sessions targeting common risk factors for internalizing disorders such as cognitive distortions, avoidance, emotional management, low self-esteem, social skills deficits, and coping strategies. The present research focuses on assessing the effectiveness of SSL applied online (through a virtual platform).
Super Skills for Life (SSL) is a transdiagnostic cognitive-behavioral protocol developed for children aged 6 to 12 with anxiety and comorbid problems (e.g., depression, low self-esteem, and lack of social skills). SSL consists of eight sessions targeting common risk factors for internalizing disorders such as cognitive distortions, avoidance, emotional management, low self-esteem, social skills deficits and coping strategies. The aim of the study is to investigate the comparative effectiveness of SSL in its traditional and computerized versions on internalizing symptoms in Spanish children between 8 and 12 years of age.
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 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).
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.