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| ID | Type | Description | Link |
|---|---|---|---|
| UL1TR001427 | U.S. NIH Grant/Contract | View source |
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| Name | Class |
|---|---|
| National Center for Advancing Translational Sciences (NCATS) | NIH |
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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.
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.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Text-only | Active Comparator | 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. |
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| High Dialectal | Experimental | 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. |
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| Low Dialectal | Experimental | 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. |
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| Non-Dialectal | Experimental | 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. |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| High Dialectal | Behavioral | 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. |
| 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 |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Affiliation | Role |
|---|---|---|
| Janice Krieger, PhD | Mayo Clinic of Jacksonville | Principal Investigator |
| Kevin Tang, PhD | University of Florida | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Qualtrics | Gainesville | Florida | 32611 | United States |
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| ID | Title | Description |
|---|---|---|
| FG000 | 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. |
| FG001 | 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. |
| FG002 | 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. |
| FG003 | 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. |
| Title | Milestones | Reasons Not Completed | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Overall Study |
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| ID | Title | Description |
|---|---|---|
| BG000 | 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. |
| Units | Counts |
|---|---|
| Participants |
|
| Title | Description | Population Description | Parameter Type | Dispersion Type | Unit of Measure | Calculate Percentage | Denominator Units Selected | Denominators | Classes |
|---|---|---|---|---|---|---|---|---|---|
| Age, Categorical | Count of Participants |
| Type | Title | Description | Population Description | Reporting Status | Anticipated Posting Date | Parameter Type | Dispersion Type | Unit of Measure | Calculate Percentage | Time Frame | Units Analyzed | Denominator Units Selected | Arm/Group Information | Denominators | Classes | Analyses | |||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 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. | Posted | Mean | Standard Deviation | units on a scale | Immediately after the intervention, up to 1 hour |
|
Adverse event data were collected for 2 weeks.
During the study, 751 participants were monitored/assessed for other (non-serious) adverse events, but none were observed.
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| ID | Title | Description | Deaths (Affected) | Deaths (At Risk) | Serious Events (Affected) | Serious Events (At Risk) | Other Events (Affected) | Other Events (At Risk) |
|---|---|---|---|---|---|---|---|---|
| EG000 | 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. |
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| Title | Organization | Phone | Extension | |
|---|---|---|---|---|
| Dr. Janice Krieger | Mayo Clinic of Jacksonville | 904-953-6160 | krieger.janice@mayo.edu |
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| Type | Includes Protocol | Includes SAP | Includes ICF | Document Label | Document Date | Document Uploaded Date | Document File Name |
|---|---|---|---|---|---|---|---|
| Prot_SAP | Yes | Yes | No | Study Protocol and Statistical Analysis Plan | Jul 27, 2023 | Aug 26, 2024 | Prot_SAP_000.pdf |
| ICF | No | No | Yes | Informed Consent Form | Nov 1, 2023 | Jul 16, 2024 | ICF_001.pdf |
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| ID | Term |
|---|---|
| D015179 | Colorectal Neoplasms |
| ID | Term |
|---|---|
| D007414 | Intestinal Neoplasms |
| D005770 | Gastrointestinal Neoplasms |
| D004067 | Digestive System Neoplasms |
| D009371 | Neoplasms by Site |
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A 4-arm randomized experimental message design.
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Participants will be blind to condition. Investigators will be blind to which participants will be assigned to which interventions.
| Low Dialectal | Behavioral | 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. |
|
| Non-Dialectal | Behavioral | 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. |
|
| Text-only | Behavioral | 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. |
|
| BG001 | 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. |
| BG002 | 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. |
| BG003 | 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. |
| BG004 | Total | Total of all reporting groups |
| Participants |
|
| Sex: Female, Male | Count of Participants | Participants |
|
| Race (NIH/OMB) | Count of Participants | Participants |
|
| Region of Enrollment | Number | participants |
|
| OG001 | 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. |
| OG002 | 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. |
| OG003 | 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. |
|
|
| 0 |
| 107 |
| 0 |
| 107 |
| 0 |
| 107 |
| EG001 | 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. | 0 | 214 | 0 | 214 | 0 | 214 |
| EG002 | 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. | 0 | 212 | 0 | 212 | 0 | 212 |
| EG003 | 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. | 0 | 218 | 0 | 218 | 0 | 218 |
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| D009369 | Neoplasms |
| D004066 | Digestive System Diseases |
| D005767 | Gastrointestinal Diseases |
| D003108 | Colonic Diseases |
| D007410 | Intestinal Diseases |
| D012002 | Rectal Diseases |