AI-DBT For Serious Illness

NCT07748312 | Not Yet Recruiting Phase 1

• 2 other identifiers: Pro20260009881U54AG093230-01
• Study Type: interventional
• Target: 80
• Locations: 0 countries
• Sites: N/A

Brief Summary

Lay / General Audience Summary Many older adults living with serious illnesses experience high levels of emotional distress, including anxiety, sadness, fear, and feeling overwhelmed. These feelings often worsen as illness progresses and can make physical symptoms harder to manage, reduce quality of life, and increase the use of medications. Unfortunately, many people with serious illness cannot access mental health care because there are not enough providers, services are hard to reach, appointments are physically exhausting, or care is not available in their language. This study will test a new way of delivering emotional support that does not require in-person therapy. The program teaches practical coping skills that help people manage strong emotions and stress. These skills are delivered through short videos and daily supportive check-ins using an automated phone or text system that people can use from home. The system is available in many languages and can be used on basic mobile phones, making it accessible to a wide range of patients. We will enroll older adults with serious illnesses such as cancer, heart disease, lung disease, or kidney disease who are experiencing emotional distress. Participants will be randomly assigned to receive either their usual medical care alone or usual care plus the new skills program. We will examine whether people find the program easy to use, helpful, and acceptable, and whether it improves their confidence in managing difficult emotions and reduces distress. The goal of this project is to develop a low-burden, widely accessible way to support emotional well-being for people living with serious illness. If successful, this approach could expand access to mental health support for patients who currently have few options.

Conditions

Serious Illness; Distress, Emotional; Distress

Keywords

serious illness; mental health; AI; DBT; distress

Outcome Measures

Primary Outcomes (3)

• Acceptability

  Acceptability will be measured quantitatively using the Acceptability of Intervention Measure and Intervention Appropriateness Measure

  8 weeks

• Feasibility

  Feasibility is defined by the number of unique videos watched. If a participant watches 9 or more of the 14 videos, engagement will be achieved.

  8 weeks

• Preliminary efficacy

  DBT ways of Coping Checklist

  8 weeks

Secondary Outcomes (3)

• depressive symptoms

  8 weeks

• anxiety

  8 weeks

• psychological distress

  8 weeks

Study Arms (2)

control

NO INTERVENTION

Usual Care Control Condition: Participants randomized to the usual care condition will continue to receive all medical and psychosocial services routinely available to them through their existing care teams (e.g., primary care, oncology, cardiology, nephrology, palliative care, social work). Variation in usual care across clinical contexts is an expected and intentional feature of this study. AI-DBT is designed as an additive intervention that can be layered onto existing care, regardless of diagnosis or setting.

intervention

EXPERIMENTAL

The skills component of the intervention consists of 14 skills-based videos, available in English and Spanish, that are each under 5 minutes. These videos were adapted in prior research programs to be more suitable to older adults and adults with medical comorbidities. Two videos will be sent to participants per week via text message. In addition to the videos, Angel, the constrained-AI DBT skills chatbot, will check in with participants every day to collect daily-diary data and inquire if a participant is interested in a coaching session. We have also designed an orientation to the program based on protocols by the Center for Research and Education on Aging and Technology Enhancement72,73 and the Technology Acceptance Model. The intervention will be introduced during a phone call by a trained research assistant with two booster phone calls.

Behavioral: AI DBT

Interventions

AI DBT BEHAVIORAL

The skills component of the intervention consists of 14 skills-based videos, available in English and Spanish, that are each under 5 minutes. These videos were adapted in prior research programs to be more suitable to older adults and adults with medical comorbidities. Two videos will be sent to participants per week via text message. In addition to the videos, Angel, the constrained-AI DBT skills chatbot, will check in with participants every day to collect daily-diary data and inquire if a participant is interested in a coaching session. We have also designed an orientation to the program based on protocols by the Center for Research and Education on Aging and Technology Enhancement72,73 and the Technology Acceptance Model. The intervention will be introduced during a phone call by a trained research assistant with two booster phone calls.

intervention

Eligibility Criteria

• Age: 60 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

Sponsors & Collaborators

• Rutgers, The State University of New Jersey: lead
• University of Colorado Denver - Anschutz Medical Campus (UCD-AMC): collaborator

MeSH Terms

Conditions

Psychological Well-Being

Condition Hierarchy (Ancestors)

Personal Satisfaction; Behavior

Central Study Contacts

Jared Khan

CONTACT

(914) 861-5158; khanjj@sph.rutgers.edu

Study Design

• Study Type: interventional
• Phase: phase 1
• Allocation: RANDOMIZED
• Masking: DOUBLE
• Who Masked: PARTICIPANT, OUTCOMES ASSESSOR
• Purpose: TREATMENT
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Assistant Professor

Study Record Dates

• First Submitted: July 29, 2026
• First Posted: August 5, 2026
• Study Start (Estimated): October 1, 2026
• Primary Completion (Estimated): February 1, 2028
• Study Completion (Estimated): May 15, 2028
• Last Updated: August 5, 2026

Record last verified: 2026-08

Data Sharing

• IPD Sharing: Will share
• Shared Documents: STUDY PROTOCOL, SAP, CSR, ANALYTIC CODE
• Access Criteria: at study termination all data will be deidentified and shared with the Ascent Data Repository at the University of Colorado.