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

August 13, 2026 updated by: University of Michigan Rogel Cancer Center

Feasibility, Usability, and Acceptability of an AI-Powered MASCC Supportive Care Platform Among Young Adults With Cancer

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.

Study Overview

Status

Not yet recruiting

Conditions

Intervention / Treatment

Study Type

Interventional

Enrollment (Estimated)

30

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Locations

  • United States
    • Michigan
      • Ann Arbor, Michigan, United States, 48109
        • University of Michigan Rogel Cancer Center
        • Contact:
        • Principal Investigator:
          • Robert Knoerl

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult

Accepts Healthy Volunteers

No

Description

Inclusion Criteria:

  • 18 - 39 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

Exclusion Criteria:

  • Completed cancer treatment more than three years ago

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Supportive Care
  • Allocation: N/A
  • Interventional Model: Single Group Assignment
  • Masking: None (Open Label)

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Experimental: Supportive care (AI-powered supportive care chatbot)
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: Survey Administration
Ancillary studies
Other: Interview
Ancillary studies
Other: Artificial Intelligence-based Intervention
Interact with AI-powered supportive care chatbot
Other Names:
  • AI Intervention
  • AI-based Intervention

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Acceptability of AI-powered supportive care chatbot
Time Frame: At end of intervention, assessed up to 12 weeks
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
Time Frame: Up to 12 months
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
Time Frame: During intervention use, assessed up to 12 weeks
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
Time Frame: Up to 12 weeks
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
Time Frame: At end of intervention, assessed up to 12 weeks
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
Time Frame: At baseline, 4 weeks, and/or 12 weeks
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
Time Frame: At baseline
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
Time Frame: At end of intervention, assessed up to 12 weeks
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

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

University of Michigan Rogel Cancer Center

Investigators

  • Principal Investigator: Robert Knoerl, University of Michigan Rogel Cancer Center

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Estimated)

October 1, 2026

Primary Completion (Estimated)

October 1, 2028

Study Completion (Estimated)

October 1, 2028

Study Registration Dates

First Submitted

July 30, 2026

First Submitted That Met QC Criteria

August 13, 2026

First Posted (Actual)

August 19, 2026

Study Record Updates

Last Update Posted (Actual)

August 19, 2026

Last Update Submitted That Met QC Criteria

August 13, 2026

Last Verified

July 1, 2026

More Information

Terms related to this study

Additional Relevant MeSH Terms

Other Study ID Numbers

  • UMCC 2026.025
  • NCI-2026-05454 (Registry Identifier: CTRP (Clinical Trial Reporting Program))
  • HUM00288074 (Other Identifier: University of Michigan Rogel Cancer Center)

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

YES

IPD Plan Description

De-identified participant data will be shared with other researchers upon reasonable request and execution of a data transfer agreement.

IPD Sharing Time Frame

After publication of results and within 7 years after study completion.

IPD Sharing Access Criteria

De-identified participant data will be shared with other researchers upon reasonable request and execution of a data transfer agreement.

IPD Sharing Supporting Information Type

  • STUDY_PROTOCOL
  • SAP
  • ICF
  • ANALYTIC_CODE
  • CSR

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

product manufactured in and exported from the U.S.

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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