Hematopoietic and Lymphatic System NeoplasmNCT07772596
An Artificial Intelligence-Powered Supportive Care Chatbot to Address the Supportive Care Needs of Young Adult Cancer Survivors
A study testing Artificial Intelligence-based Intervention, Interview and Survey Administration in people with Hematopoietic and Lymphatic System Neoplasm and Malignant Solid Neoplasm, run by University of Michigan Rogel Cancer Center at 1 site in United States.
Trial 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. Read more about this study
- Who is it for?
- Ages 18 to 39 years
- Conditions the study is for
- Hematopoietic and Lymphatic System Neoplasm, Malignant Solid Neoplasm
- What is being tested?
- Artificial Intelligence-based Intervention, Interview and Survey Administration
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 30 participants
- Where
- 1 siteUnited States
- Study dates
- 15 Sep 2026to Sep 2028
- Phase
- Interventional
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 39 years
- All sexes
- No healthy volunteers
- Adult
Who may be able to join
- 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
Who cannot join
- Completed cancer treatment more than three years ago
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
United States1 site, 1 recruiting
- Recruiting
University of Michigan Rogel Cancer Center
Ann Arbor, Michigan, 48109
Robert Knoerl, 734-764-8617, rjknoerl@med.umich.edu
Robert Knoerl
About this study
Official title: 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.
- Being tested
- Artificial Intelligence-based Intervention, Interview, Survey Administration
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Artificial Intelligence-based InterventionOther
Also called AI Intervention, AI-based Intervention
Interact with AI-powered supportive care chatbot
InterviewOther
Ancillary studies
Survey AdministrationOther
Ancillary studies
| Study group | Role | What they receive |
|---|---|---|
| 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. Receives: Other: Artificial Intelligence-based Intervention; Other: Interview; Other: Survey Administration |
What is being measured
The primary outcome is the main question the study is designed to answer.
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.
Measured: 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.
Measured: 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.
Measured: 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.
Measured: 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.
Measured: 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.
Measured: 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.
Measured: 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.
Measured: At end of intervention, assessed up to 12 weeks
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted19 Aug 2026
- Study start15 Sep 2026
- Primary completionSep 2028 (estimated)
- Study completionSep 2028 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Hematopoietic and Lymphatic System NeoplasmStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Supportive care
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Enrolment
- 30 participants (estimated)
Sponsor and investigators
- Lead sponsor
- University of Michigan Rogel Cancer Center
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
- Investigators
- Robert Knoerl, Principal investigator, University of Michigan Rogel Cancer Center
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07772596
- Sponsor's protocol ID
- UMCC 2026.025
- Other IDs
- NCI-2026-05454, HUM00288074
- Status last verified
- Oct 2026
- First submitted
- 30 Jul 2026
- Last updated
- 15 Oct 2026
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Yes: De-identified participant data will be shared with other researchers upon reasonable request and execution of a data transfer agreement.
Study at a glance
From the registry record, last updated by the sponsor on 15 Oct 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Feasibility, Usability, and Acceptability of an AI-Powered MASCC Supportive Care Platform Among Young Adults With Cancer
- ClinicalTrials.gov ID
- NCT07772596
- Acronym / sponsor ID
- UMCC 2026.025
- Study type
- Interventional
- Recruitment status
- Recruiting
- Enrolment
- 30 participants (estimated)
- Lead sponsor
- University of Michigan Rogel Cancer CenterUniversity, hospital or other
- Study start
- 15 Sep 2026 (actual)
- Primary completion
- Sep 2028 (estimated)
- Study completion
- Sep 2028 (estimated)
- First posted
- 19 Aug 2026 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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 design
- Primary purpose
- Supportive care
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Supportive care (AI-powered supportive care chatbot) | Experimental | Other: Artificial Intelligence-based Intervention, Other: Interview, Other: Survey AdministrationPatients 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. |
Who may qualify
- Ages
- 18 to 39 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult
Key inclusion criteria (6 listed)
- 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
Key exclusion criteria (1 listed)
- Completed cancer treatment more than three years ago
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Artificial Intelligence-based InterventionAlso: AI Intervention, AI-based InterventionInteract with AI-powered supportive care chatbot | Other | Supportive care (AI-powered supportive care chatbot) |
| InterviewAncillary studies | Other | Supportive care (AI-powered supportive care chatbot) |
| Survey AdministrationAncillary studies | Other | Supportive care (AI-powered supportive care chatbot) |
Primary outcome
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.
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.
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.
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.
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.
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.
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.
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.
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 15 Oct 2026.
- Individual participant dataSharing planned: Yes. De-identified participant data will be shared with other researchers upon reasonable request and execution of a data transfer agreement.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Robert Knoerl principal investigator
University of Michigan Rogel Cancer Center
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Artificial Intelligence-based Intervention, Interview and Survey Administration in people with Hematopoietic and Lymphatic System Neoplasm and Malignant Solid Neoplasm, run by University of Michigan Rogel Cancer Center at 1 site in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 6 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 15 Oct 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United States. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Robert Knoerl (734-764-8617, rjknoerl@med.umich.edu), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Acceptability of AI-powered supportive care chatbot (time frame: At end of intervention, assessed up to 12 weeks). The study lists 8 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 15 Oct 2026.