Recruiting

AI-Generated Prompts

Sponsor:

Washington University School of Medicine

Code:

NCT07226934

Conditions

Lymphoma

Multiple Myeloma

Eligibility Criteria

Sex: All

Age: 18 - 70+

Healthy Volunteers: Not accepted

Interventions

GPT-QPL

Study Details

Brief summary:

The goal of this study is to evaluate the feasibility and preliminary efficacy of an artificial intelligence (AI)-generated personalized question prompt list (a list of suggested questions to ask during outpatient appointments) for patients with hematologic cancers. The intervention will involve tailoring a standardized prompt to patients' individual characteristics and concerns. This prompt will then be used to ask Washington University's (WashU) HIPAA compliant ChatGPT to generate personalized question lists for outpatient appointments. Analyses will assess the impact of personalized QPLs on patients' question-asking behavior; communicative self-efficacy; and self-reported amount and satisfaction with information obtained about their disease and its treatment. Sub-analyses will explore patterns in questions generated by WashU ChatGPT. Patients will also provide feedback pertaining to the perceived helpfulness and ease-of-use of WashU-ChatGPT-generated question lists, as well as their attitudes and intentions regarding use of AI chatbots and whether they would engage in pre-appointment AI-assisted question brainstorming independently in the future.

Conditions

Lymphoma

Multiple Myeloma

Study ID

NCT07226934

Start date

Dec 26, 2025

Status verified date

Oct, 2026

Completion date

Dec 31, 2026

Anticipated

Primary completion date

Dec 31, 2026

Anticipated

Eligibility Criteria

Eligibility Criteria

Sex: All

Age: 18 - 70+

Healthy Volunteers: Not accepted

Eligibility Criteria as determined by Electronic Health Record (EHR) Screening:

  • Documented diagnosis of lymphoma, as defined by ICD-10 codes C81-C88 or multiple myeloma, as defined by ICD codes C90.0-C90.02
  • Has a scheduled follow-up appointment at a participating outpatient oncology clinic within the next month. Participating clinics include:

  • Dr. David Russler-Germain: Outpatient Lymphoma Clinic
  • Dr. Michael Slade: Outpatient Multiple Myeloma Clinic
  • Dr. Dilan Patel: Outpatient Lymphoma Clinic
  • Undergoing infusion or injection-based systemic therapy intended to cure or manage the disease, as opposed to regimens delivered solely for palliative purposes, at a frequency of once every 1-4 weeks.

  • For eligible patients with lymphoma, this includes, but is not limited to, commonly prescribed treatment combinations such as R-CHOP (Rituximab, Cyclophosphamide, Doxorubicin/Hydroxydaunorubicin, Vincristine, and Prednisone) for Non-Hodgkin Lymphoma, or ABVD (Adriamycin/Doxorubicin, Bleomycin, Vinblastine, and Dacarbazine) for Hodgkin Lymphoma-both regimens that are frequently administered every three weeks
  • For patients with multiple myeloma, eligibility will include patients in the "induction" phase of chemotherapy treatment, which frequently requires patients to come in for outpatient appointments once every four weeks as well as patients in a maintenance phase of treatment that otherwise requires them to attend outpatient appointments at a frequency of every one to four weeks
  • Between the ages of 18-99 at enrollment (Patients older than 99 will be excluded so that the study team is able to elicit questions from WashU ChatGPT using a standardized prompt that describes the patient's age only as specifically as a 10-year decade range (i.e., "I am a patient in my 20's, 30's, 40's, etc. Patients who are 18 or 19 years old will be described in the following manner: "I am a young adult patient in my late teens").
  • Able to consent to medical care independently (does not have a legally authorized representative or documented diagnosis of cognitive impairment)

Eligibility Criteria as determined by subsequent recruitment phone call or In-person approach after a clinic appointment:

  • Does not have visual impairments or English literacy limitations that would interfere with ability to engage in an intervention that requires being able to read material on an electronic device and on paper and communicate aloud during appointments with health care providers, based on patient self-report
  • Able to use email (consent form will be distributed electronically through DocuSign and associated emails), based on successful completion of electronic informed consent

Study Design

Enrollment

40 participants

Anticipated

Intervention Model

Single group

Primary purpose

Health Services Research

Interventions and Outcome Measures

Arms

experimental: GPT-QPL: An AI-Generated, Personalized Question Prompt List

Participants will complete surveys at appointment 1 (pre-intervention) and after being provided the AI-Generated, Personalized Question Prompt List at appointment 2 (post-intervention).

Interventions

GPT-QPL

A research team member will generate a QPL that is personalized to the patient's demographics (from EHR screening and Baseline Demographic Survey) and concerns (from Distress Thermometer Problem Checklist and Interview).

Primary outcome measure

  • Changes in communicative self-efficacy [ Time Frame: Appointment 1 (pre-intervention) and appointment 2 (post-intervention) (estimated to be 12 weeks) ]

Central Contacts and Locations

Central contacts

Jessica Hahne, MA, MPH

314-935-6173hahne.j@wustl.edu

Locations

Washington University School of Medicine

Recruiting

St Louis, Missouri, United States, 63110

Contacts

Jessica Hahne, MA, MPH

314-935-6173hahne.j@wustl.edu

Principal Investigator:

Jessica Hahne, MA, MPH

More Information

Sponsor

Washington University School of Medicine

Last update posted

Oct 8, 2026

Last verified

Oct, 2026

Keywords

  • Generative Artificial Intelligence
  • Healthcare
  • Cancer
  • Communication

Trial information was received from ClinicalTrials.gov and was last updated on 2026-10-24. This information was provided to ClinicalTrials.gov by Washington University School of Medicine on 2026-10-08. Recruitment status is synced daily from ClinicalTrials.gov and may not reflect the sponsor's current status. Confirm during your call.