Clinical Research Directory

Unmute's CARE Framework: A Novel Approach to Strengthen the Therapeutic Alliance and Reduce Treatment Disparities

Aim 1: Expand and adapt the CARE framework to train providers to cultivate a strong early alliance with patients who do not share their background (e.g., mismatched dyads). Aim 2: Establish the feasibility, acceptability, and preliminary effectiveness of the adapted CARE framework in mismatched dyads involving 8 providers and 40 patients receiving 15 sessions of teletherapy. The goal of this clinical trial is to learn if a new CARE intervention works to improve the cultural fit of psychotherapy for diverse populations, even when the therapist and patient do not share the same cultural background. We will refine and test the intervention with a sample of therapists working with Asian American participants receiving short-term individual psychotherapy delivered online. The main questions the study aims to answer are: * Does the CARE framework, adapted for and delivered by therapists specifically trained to work with patients who do not share their background (e.g., mismatched dyads), improve treatment engagement and retention? * Is the CARE framework associated with a) the development of a positive therapeutic relationship between mismatched patient-therapist dyads and b) significant improvements in participants' presenting problems? Participants will: * Receive up to 15 weekly sessions of individual psychotherapy * Complete different online surveys after every session and on a monthly basis

Utilizing Embodied Artificial Intelligence (AI) for the Development of Digital Cognitive Behavioral Therapy (CBT) for Depression in Virtual Reality (VR)

Depression is a prevalent mental disorder characterized by pervasive low mood, diminished interest or pleasure, and a range of cognitive and physical symptoms. According to the World Health Organization (WHO), depression is a leading cause of disability worldwide, affecting approximately 280 million individuals of all ages. In spite of the widespread occurrence and negative consequences linked to depression, fewer than 30% of individuals with common mental disorders sought assistance from mental health services in the previous year due to reasons such as, high-cost and stigma. Cognitive behavioral therapy (CBT) is the gold-standard and evidence-based intervention for various mental health disorders, including depression, anxiety, and its effectiveness has been widely proven. With the recent advancement in AI and other relevant technologies, the use of digital CBT has become possible. Indeed, a recent systematic review demonstrated a comparable effectiveness of traditional CBT and digital CBT, after controlling the moderators (e.g., intervention duration, and adherence). While digital CBT has achieved impressive performance, the majority of them utilized web-based or app-based platforms. Therefore, one of the disadvantages of such digital CBT is the lack of interaction between (digital) therapists and clients. Additionally, lower adherence to digital interventions was observed, indicating the need for briefer sessions, such as single-session integrated CBT (SSI-CBT), for digital interventions. SSI-CBT involves a collaborative effort between the therapist and the client, aimed at assisting the client in accomplishing their desired outcome within a single session. It is understood that additional support is accessible if required. A recent study using SSI-CBT demonstrated promising results of its effectiveness in reducing depression and anxiety, which can last for two months. To further generalize the application of digital interventions, a more interactive virtual therapist utilizing a brief CBT-based intervention approach is desired. This study will evaluate the effectiveness of virtual CBT therapist for reducing depression symptoms, compared to a waitlist control group. Based on previous research, it is expected that a virtual CBT therapist can significantly reduce the depression symptoms at both post-intervention and one-month follow-up.