Colorectal Cancer
Conditions
Brief summary
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.
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.
Interventions
BEHAVIORALHigh 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.
BEHAVIORALLow 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.
BEHAVIORALNon-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.
BEHAVIORALText-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.
Sponsors
National Center for Advancing Translational Sciences (NCATS)
University of Florida
Study design
Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
SCREENING
Masking
DOUBLE (Subject, Investigator)
Masking description
Participants will be blind to condition. Investigators will be blind to which participants will be assigned to which interventions.
Intervention model description
A 4-arm randomized experimental message design.
Eligibility
Sex/Gender
ALL
Age
45 Years to 75 Years
Healthy volunteers
No
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
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Intention to Talk to Doctor About Colorectal Cancer Screening | Immediately after the intervention, up to 1 hour | 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. |
Countries
United States
Participant flow
Participants by arm
| Arm | Count |
|---|---|
| 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.
Text-only: 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. | 107 |
| 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.
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. | 214 |
| 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.
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. | 212 |
| 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.
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. | 218 |
| Total | 751 |
Baseline characteristics
| Characteristic | Non-Dialectal | Total | Text-only | High Dialectal | Low Dialectal |
|---|---|---|---|---|---|
| Age, Categorical <=18 years | 0 Participants | 0 Participants | 0 Participants | 0 Participants | 0 Participants |
| Age, Categorical >=65 years | 50 Participants | 174 Participants | 32 Participants | 38 Participants | 54 Participants |
| Age, Categorical Between 18 and 65 years | 168 Participants | 577 Participants | 75 Participants | 176 Participants | 158 Participants |
| Race (NIH/OMB) American Indian or Alaska Native | 0 Participants | 0 Participants | 0 Participants | 0 Participants | 0 Participants |
| Race (NIH/OMB) Asian | 0 Participants | 0 Participants | 0 Participants | 0 Participants | 0 Participants |
| Race (NIH/OMB) Black or African American | 218 Participants | 751 Participants | 107 Participants | 214 Participants | 212 Participants |
| Race (NIH/OMB) More than one race | 0 Participants | 0 Participants | 0 Participants | 0 Participants | 0 Participants |
| Race (NIH/OMB) Native Hawaiian or Other Pacific Islander | 0 Participants | 0 Participants | 0 Participants | 0 Participants | 0 Participants |
| Race (NIH/OMB) Unknown or Not Reported | 0 Participants | 0 Participants | 0 Participants | 0 Participants | 0 Participants |
| Race (NIH/OMB) White | 0 Participants | 0 Participants | 0 Participants | 0 Participants | 0 Participants |
| Region of Enrollment United States | 218 participants | 751 participants | 107 participants | 214 participants | 212 participants |
| Sex: Female, Male Female | 110 Participants | 376 Participants | 54 Participants | 104 Participants | 108 Participants |
| Sex: Female, Male Male | 108 Participants | 375 Participants | 53 Participants | 110 Participants | 104 Participants |
Adverse events
| Event type | EG000 affected / at risk | EG001 affected / at risk | EG002 affected / at risk | EG003 affected / at risk |
|---|---|---|---|---|
| deaths Total, all-cause mortality | 0 / 107 | 0 / 214 | 0 / 212 | 0 / 218 |
| other Total, other adverse events | 0 / 107 | 0 / 214 | 0 / 212 | 0 / 218 |
| serious Total, serious adverse events | 0 / 107 | 0 / 214 | 0 / 212 | 0 / 218 |
Outcome results
Primary
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.
Time frame: Immediately after the intervention, up to 1 hour
| Arm | Measure | Value (MEAN) | Dispersion |
|---|---|---|---|
| Text-only | Intention to Talk to Doctor About Colorectal Cancer Screening | 11.42 units on a scale | Standard Deviation 3.43 |
| High Dialectal | Intention to Talk to Doctor About Colorectal Cancer Screening | 11.31 units on a scale | Standard Deviation 3.55 |
| Low Dialectal | Intention to Talk to Doctor About Colorectal Cancer Screening | 11.87 units on a scale | Standard Deviation 3.27 |
| Non-Dialectal | Intention to Talk to Doctor About Colorectal Cancer Screening | 11.42 units on a scale | Standard Deviation 3.38 |