Washington University School of Medicine
St Louis, Missouri, 63110, United States
Location status: Recruiting
Location contact
Brian D Carpenter, Ph.D.
SUB_INVESTIGATOR
Jessica Hahne, MA, MPH
CONTACT
Jessica Hahne, MA, MPH
PRINCIPAL_INVESTIGATOR
NCT Number: NCT07226934
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.
Interested in participating?
Request Info18 year–99 year
All sexes
Interventional
Not applicable
St Louis, Missouri, 63110, United States
Location status: Recruiting
Brian D Carpenter, Ph.D.
SUB_INVESTIGATOR
Jessica Hahne, MA, MPH
CONTACT
Jessica Hahne, MA, MPH
PRINCIPAL_INVESTIGATOR
Healthy volunteers accepted: No
Only the study team can determine whether someone qualifies for participation.
Eligibility Criteria as determined by Electronic Health Record (EHR) Screening:
Eligibility Criteria as determined by subsequent recruitment phone call or In-person approach after a clinic appointment:
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).
Other names: AI-Generated, Personalized Question Prompt List
Time frame: Appointment 1 (pre-intervention) and appointment 2 (post-intervention) (estimated to be 12 weeks)
Time frame: Appointment 1 (pre-intervention) and appointment 2 (post-intervention) (estimated to be 12 weeks)
Time frame: Appointment 1 (pre-intervention) and appointment 2 (post-intervention) (estimated to be 12 weeks)
Time frame: Appointment 1 (pre-intervention) and appointment 2 (post-intervention) (estimated to be 12 weeks)
Time frame: Appointment 1 (pre-intervention) and appointment 2 (post-intervention) (estimated to be 12 weeks)
Contact information is provided by the study sponsor or research team.
Washington University School of Medicine
Other
Feasibility and Preliminary Efficacy of GPT-QPL: An AI-Generated, Personalized Question Prompt List Intervention for Patients With Hematologic Cancers
OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.
View the official ClinicalTrials.gov record (opens in a new tab)This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.
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