A Sociolinguistic-enabled Web Application to Develop Precision Health Intervention for African Americans

This pilot study will explore the preliminary efficacy of a colorectal cancer (CRC) screening intervention delivered by Virtual Human Agents (VHAs). Seven hundred fifty participants aged 45 to 75 will be recruited through Qualtrics panels. The study examines how different levels of dialectal linguistic features willingness to be screened for colorectal cancer. Participants will be randomly assigned to interact with one of four VHA conditions: a VHA using non-dialectal linguistic features, a VHA with a low level of dialectal linguistic features integrated, a VHA with a high level of dialectal linguistic features integrated, or a text-only control condition. Following the interaction, participants will complete survey measures to assess perceived willingness to be screened.

Study Overview

• Status: Completed
• Conditions: Colorectal Cancer
• Intervention / Treatment: Behavioral: Text-only; Behavioral: High Dialectal; Behavioral: Low Dialectal; Behavioral: Non-Dialectal

Detailed Description

African Americans experience significant health inequities, including higher morbidity and mortality rates due to colorectal cancer (CRC) compared to White Americans. While the causes of these disparities are complex, regular screening can help reduce them. However, adherence to CRC screening guidelines remains low, particularly among African Americans.

One strategy to reduce CRC screening disparities is using strategic communication interventions to promote the fecal immunochemical test (FIT). FIT is a low-cost, non-invasive screening method that alleviates common patient barriers to CRC screening and is as effective as colonoscopy in reducing CRC incidence and mortality.

Tailored messaging interventions have been shown to improve CRC screening rates. However, two critical questions must be addressed before implementing tailored screening interventions within healthcare systems: (1) To what extent must message content be tailored to be effective? and (2) How can participants be effectively engaged?

This study builds upon an existing project that utilizes mobile Virtual Human Technology (VHT) to deliver tailored CRC screening messages. Virtual Human Agents (VHAs) provide a unique opportunity to customize communication strategies, including linguistic adaptation, to align with patient preferences. Such interventions can help mitigate CRC screening barriers such as cultural mismatch and low self-efficacy.

This study investigates explicitly the role of dialectal linguistic features in shaping willingness to be screened for CRC. The pilot study is exploratory in nature and seeks to examine the following aim: To assess how tailoring the dialectal variety of VHA speech affects willingness to be screened for CRC.

We aim to recruit 750 participants, each of whom will interact with a VHA that varies in speech style across four conditions: (1) non-dialectal linguistic features, (2) a low-level integration of dialectal linguistic features, (3) a high-level integration of dialectal linguistic features, or (4) a voiceless, text-only control. Following the interaction, participants will assess the VHA's credibility using survey-based measures.

• Study Type: Interventional
• Enrollment (Actual): 751
• Phase: Not Applicable

Contacts and Locations

Study Locations

• United States
  • Florida
    • Gainesville, Florida, United States, 32611
      • Qualtrics

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 45 years to 75 years (Adult, Older Adult)
• Accepts Healthy Volunteers: No

Description

Inclusion Criteria:

• Out of guidelines for colorectal cancer screening
• No fecal immunochemical test within the last 12 months
• No colonoscopy within the last ten years)

Exclusion Criteria:

• Must meet inclusion criteria

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Screening
• Allocation: Randomized
• Interventional Model: Parallel Assignment
• Masking: Double

Number of Arms

4

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Active Comparator: Text-only; A virtual health assistant that will consist of photos of the computer-generated doctor with text that will guide participants through the interaction. No voice will accompany the photos or text.	Behavioral: Text-only; A virtual health assistant that will consist of photos of the computer-generated doctor with text that will guide participants through the interaction. No voice will accompany the photos or text.
Experimental: High Dialectal; A virtual health assistant that will consist of an interactive computer-generated doctor with voice that used high dialectal variation that will guide participants through the interaction.	Behavioral: High Dialectal; A virtual health assistant that will consist of an interactive computer-generated doctor with voice that used high dialectal variation that will guide participants through the interaction.
Experimental: Low Dialectal; A virtual health assistant that will consist of an interactive computer-generated doctor with voice that used low dialectal variation that will guide participants through the interaction.	Behavioral: Low Dialectal; A virtual health assistant that will consist of an interactive computer-generated doctor with voice that used low dialectal variation that will guide participants through the interaction.
Experimental: Non-Dialectal; A virtual health assistant that will consist of an interactive computer-generated doctor with voice that used no dialectal variation that will guide participants through the interaction.	Behavioral: Non-Dialectal; A virtual health assistant that will consist of an interactive computer-generated doctor with voice that used no dialectal variation that will guide participants through the interaction.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Intention to Talk to Doctor About Colorectal Cancer Screening	Measure: Intention to talk to a doctor about colorectal cancer screening. Construct: Behavioral intention to communicate Item: The virtual appointment made me want to discuss colon cancer screening options with my doctor. Participants will respond using three 5-point Likert scales that will be summed. The total score ranges from 3 to 15, with higher scores indicating a greater intention to discuss colorectal cancer screening with a healthcare professional. Mean scores closer to 3 reflect lower intention, while mean scores closer to 15 reflect higher intention.	Immediately after the intervention, up to 1 hour

Collaborators and Investigators

• Sponsor: University of Florida
• Collaborators: National Center for Advancing Translational Sciences (NCATS)
• Investigators: Principal Investigator: Kevin Tang, PhD, University of Florida; Principal Investigator: Janice Krieger, PhD, Mayo Clinic of Jacksonville

Study record dates

Study Major Dates

• Study Start (Actual): June 29, 2021
• Primary Completion (Actual): December 18, 2023
• Study Completion (Actual): December 18, 2023

Study Registration Dates

• First Submitted: January 8, 2021
• First Submitted That Met QC Criteria: January 8, 2021
• First Posted (Actual): January 12, 2021

Study Record Updates

• Last Update Posted (Actual): April 18, 2025
• Last Update Submitted That Met QC Criteria: April 17, 2025
• Last Verified: April 1, 2025

More Information

Terms related to this study

• Additional Relevant MeSH Terms: Neoplasms by Site; Neoplasms; Intestinal Diseases; Gastrointestinal Neoplasms; Digestive System Neoplasms; Digestive System Diseases; Gastrointestinal Diseases; Intestinal Neoplasms; Rectal Diseases; Colonic Diseases; Colorectal Neoplasms
• Other Study ID Numbers: IRB202001790-N; UL1TR001427 (U.S. NIH Grant/Contract)

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No