An Artificial Intelligence-Powered Supportive Care Chatbot to Address the Supportive Care Needs of Young Adult Cancer Survivors

NCT07772596 | Not Yet Recruiting DMC

• 3 other identifiers: UMCC 2026.025NCI-2026-05454HUM00288074
• Study Type: interventional
• Target: 30
• Locations: 1 country
• Sites: 1

Brief Summary

This clinical trial studies whether an artificial intelligence (AI)-powered supportive care chatbot is helpful for addressing the supportive care needs of young adult cancer survivors. Young adult cancer survivors often experience ongoing and distressing symptoms following treatment, including extreme tiredness and lack of energy, anxiety, and difficulty sleeping. Young adult cancer survivors report a variety of strategies to self-manage these symptoms; however, there remains a gap in targeted interventions focused on the needs in young adult survivors. The AI-powered supportive care chatbot is designed to provide evidence-based information on supportive care for young adult cancer survivors. Users interact with the chatbot by entering free-text questions or selecting from predefined topics to receive tailored educational responses related to supportive care across the cancer continuum, including treatment effects, symptom management, care transitions, and life after cancer. The AI-powered supportive care chatbot may be an effective way to help address the supportive care needs of young adult cancer survivors.

Conditions

Hematopoietic and Lymphatic System Neoplasm; Malignant Solid Neoplasm

Outcome Measures

Primary Outcomes (8)

• Acceptability of AI-powered supportive care chatbot

  Acceptability will be supported if mean scores on the Acceptability E-Scale are ≥ 4 (on a 5-point scale). Will be described (i.e., means, medians, standard deviations, and ranges) at the post-intervention time point.

  At end of intervention, assessed up to 12 weeks

• Demand of AI-powered supportive care chatbot

  Demand will be demonstrated by successful recruitment of the target sample (N=30) within 12 months.

  Up to 12 months

• Implementation of AI-powered supportive care chatbot

  Implementation will be assessed by engagement with the chatbot, defined as ≥ 70% of participants reporting at least one use per week during the initial 4-week period, rather than a fixed duration of use, given the self-directed nature of the intervention. Will be described (i.e., means, medians, standard deviations, and ranges) weekly. Given the pilot nature of the study, no hypothesis testing or formal comparisons will be conducted.

  During intervention use, assessed up to 12 weeks

• Retention

  Retention will be considered feasible if ≥ 80% of participants complete 4-week assessments, and ≥ 50% elect to continue to the optional extended use period.

  Up to 12 weeks

• Usability of AI-powered supportive care chatbot

  Usability will be supported if mean System Usability Scale scores are ≥ 70, indicating acceptable usability. Will be described (i.e., means, medians, standard deviations, and ranges) at the post-intervention time point.

  At end of intervention, assessed up to 12 weeks

• Patient Reported Outcomes Measurement Information System measure

  Will be summarized using descriptive statistics (e.g., means, medians, standard deviations, and ranges) at each time point. Changes over time (baseline, post-intervention, as applicable) will be examined descriptively.

  At baseline, 4 weeks, and/or 12 weeks

• Digital Health Literacy Scale

  Will be summarized using descriptive statistics (e.g., means, medians, standard deviations, and ranges) at the baseline time point. The Digital Health Literacy Scale is a 0 to 12 point score (based on 3 items), with higher scores indicating greater digital health care literacy.

  At baseline

• Interview themes and subthemes

  The audio-recorded interviews will be transcribed verbatim by a professional transcription company and verified for accuracy by another study team member. The finalized transcripts will be imported into NVivo 12 (QSR International Pty Ltd). Inductive content analysis will be used to analyze the interview transcripts. Two study team members will review the transcripts and the interview guide to create an initial list of codes. Three transcripts will be independently coded using the initial codebook. After three interviews are coded, two study team members will meet to resolve any coding discrepancies and to revise the codebook further. The same process will be repeated after three more interviews are coded. After the codebook is finalized, one study team member will code the remaining interviews. Subsequently, the study team will meet as a group to review the transcripts in their entirety, making sense of the data and generating potential major themes and subthemes.

  At end of intervention, assessed up to 12 weeks

Study Arms (1)

Supportive care (AI-powered supportive care chatbot)

EXPERIMENTAL

Patients interact with AI-powered supportive care chatbot in a self-directed manner for 4 weeks. Following the initial 4-week use period, patients choose to either continue to use the chatbot for an additional 8 weeks or conclude study participation.

Other: Artificial Intelligence-based Intervention; Other: Interview; Other: Survey Administration

Interventions

Artificial Intelligence-based Intervention OTHER

Interact with AI-powered supportive care chatbot

Also known as: AI Intervention, AI-based Intervention

Supportive care (AI-powered supportive care chatbot)

Interview OTHER

Ancillary studies

Supportive care (AI-powered supportive care chatbot)

Survey Administration OTHER

Ancillary studies

Supportive care (AI-powered supportive care chatbot)

Eligibility Criteria

• Age: 18 Years - 39 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64)

You may qualify if:

• years old
• Able to speak/read English
• Completed primary cancer treatment (e.g., surgery, radiation, chemotherapy, immunotherapy) at least one month prior to the time of consent. Although, participants will be eligible if they are receiving maintenance treatments
• Report at least one moderate to severe symptom, side effect, or supportive care concern from cancer or its treatment
• Able to access Wi-Fi/internet
• Willing to complete surveys electronically

You may not qualify if:

• Completed cancer treatment more than three years ago

Sponsors & Collaborators

• University of Michigan Rogel Cancer Center: lead

Study Sites (1)

University of Michigan Rogel Cancer Center

Ann Arbor, Michigan, 48109, United States

Location

MeSH Terms

Interventions

Interviews as Topic

Intervention Hierarchy (Ancestors)

Data Collection; Epidemiologic Methods; Investigative Techniques; Health Care Evaluation Mechanisms; Quality of Health Care; Health Care Quality, Access, and Evaluation; Public Health; Environment and Public Health

Study Officials

• Robert Knoerl

  University of Michigan Rogel Cancer Center

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Robert Knoerl

CONTACT

734-764-8617; rjknoerl@med.umich.edu

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: NA
• Masking: NONE
• Purpose: SUPPORTIVE CARE
• Intervention Model: SINGLE GROUP
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: July 30, 2026
• First Posted: August 19, 2026
• Study Start: October 1, 2026
• Primary Completion (Estimated): October 1, 2028
• Study Completion (Estimated): October 1, 2028
• Last Updated: August 19, 2026

Record last verified: 2026-07

Data Sharing

• IPD Sharing: Will share
• Shared Documents: STUDY PROTOCOL, SAP, ICF, CSR, ANALYTIC CODE
• Time Frame: After publication of results and within 7 years after study completion.
• Access Criteria: De-identified participant data will be shared with other researchers upon reasonable request and execution of a data transfer agreement.

Locations

US (1)