Effect of Static vs. Conversational AI-Generated Messages on Colorectal Cancer Screening Intent: a Randomized Controlled Trial

Summary

The goal of this clinical trial is to assess whether messages generated by a large language model (LLM), including both static and conversational formats, can increase colorectal cancer (CRC) screening intentions among U.S. adults aged 45-75 who have never completed CRC screening. The main questions it aims to answer are:

Do personalized, AI-generated messages increase the self-reported likelihood of completing a stool-based CRC screening test within 12 months?

Do they also increase intent to undergo colonoscopy screening within 12 months?

Researchers will compare four groups: (1) no message control, (2) expert-written patient education materials, (3) a single AI-generated persuasive message, and (4) a motivational interviewing-style AI chatbot. These comparisons will help assess whether a conversational format offers added benefit over static AI or expert-generated content.

Participants will:

Be randomly assigned to one of the four study arms

Spend at least 3 minutes reading or interacting with their assigned material

Complete pre- and post-intervention surveys assessing intent to receive CRC screening

Receive messages tailored to their self-reported demographics, including age, political ideology, gender, education, community setting (urban, rural, suburb), self-reported health, and the last time they saw their PCP

Conditions

• Colorectal Cancer Control and Prevention

Interventions

BEHAVIORAL

single GPT generated message

Participants receive a single \~640-word message generated by GPT-4.1. The message is tailored to participants' self-reported demographics (age, gender, political ideology, education, urbanicity, health status, and last PCP visit). The message provides persuasive content encouraging colorectal cancer screening, emphasizing stool and colonoscopy screening options. Participants are required to read the message for a minimum of 3 minutes.

BEHAVIORAL

AI Chatbot

Participants engage in a multi-turn conversation with a GPT-4.1 chatbot trained to emulate motivational interviewing techniques. The chatbot personalizes its conversation based on each participant's demographics (age, gender, political ideology, education, urbanicity, health status, and last PCP visit). Conversations last at least 3 minutes and aim to increase participant motivation to complete colorectal cancer screening.

BEHAVIORAL

Expert-Written Patient Materials

Participants read a 642-word expert-written educational summary from the Journal of the American Medical Association's Patient Page on colorectal cancer screening. The material is designed to provide objective information about screening options and guidelines recommended by the US Preventive Services Task Force. Participants are required to read the material for at least 3 minutes.

Sponsors & Collaborators

• University of Pennsylvania

  lead OTHER

Study Design

Allocation

RANDOMIZED

Purpose

SCREENING

Masking

NONE

Model

PARALLEL

Eligibility

Min Age

45 Years

Max Age

75 Years

Sex

ALL

Healthy Volunteers

Yes

Timeline & Regulatory

Start

2025-06-11

Primary Completion

2025-06-21

Completion

2025-06-21

Countries

• United States

Study Locations