AI-Powered Chatbot vs Traditional Education for Mouth Cancer Awareness

Overseen By Tamas Gal, Ph.D

Age: 18+

Sex: Any

Trial Phase: Academic

Sponsor: Virginia Commonwealth University

Disqualifiers: Physical or mental incapacity, minors, prisoners, others

No Placebo Group All trial participants will receive the active study treatment (no placebo)

Compensation: Varies

Number of Visits: Unknown

60 Participants Needed

Trial Summary

Will I have to stop taking my current medications?

The trial information does not specify whether you need to stop taking your current medications.

What data supports the effectiveness of the treatment AI-powered Chatbot vs Traditional Education for Mouth Cancer Awareness?

Research shows that automated educational interventions, like those using voice technologies for diabetes education, can significantly improve knowledge and self-care practices. This suggests that AI-powered chatbots could similarly enhance awareness and understanding of mouth cancer. ^{1 2 3 4 5}

Is the AI-powered chatbot safe for use in healthcare settings?

Research on AI chatbots in healthcare, such as those for hereditary cancer risk and medication guidance, suggests they are generally safe for use, focusing on user experience and information accuracy. ^{6 7 8 9 10}

How does the AI-powered chatbot treatment for mouth cancer awareness differ from traditional education?

The AI-powered chatbot treatment is unique because it uses artificial intelligence to provide interactive and personalized education, potentially increasing engagement and understanding, unlike traditional education methods that may not be as interactive or tailored to individual needs. ^{4 5 11 12 13}

What is the purpose of this trial?

To evaluate the impact of AI-powered chatbot interactions versus traditional educational handouts on increasing participants' knowledge of oral cancer and its prevention

Research Team

Tamas Gal, Ph.D

Principal Investigator

Virginia Commonwealth University

Eligibility Criteria

This trial is for individuals from minority groups who are interested in learning about oral cancer prevention. Specific eligibility criteria have not been provided, so it's best to contact the study organizers for detailed requirements.

Inclusion Criteria

Identify as African American as defined by the US Census

Participants must be able to read, speak, and write in English

Exclusion Criteria

Prisoners

I am physically and mentally able to participate in the research.

I am unable to give consent for medical procedures.

Timeline

Screening

Participants are screened for eligibility to participate in the trial

2-4 weeks

Intervention

Participants receive either traditional educational handouts or engage with an AI-powered chatbot to enhance oral cancer awareness

3 months

Baseline and post-intervention assessments

Follow-up

Participants are monitored for retention rates, knowledge improvement, and acceptability of interventions

3 months

Treatment Details

Interventions

• AI-powered Chatbox
• Traditional Education

Trial Overview The trial aims to compare the effectiveness of an AI-powered chatbot with traditional educational handouts in raising awareness and knowledge about oral cancer and its prevention among participants.

Participant Groups

Group I: Engaging with an AI-powered Chatbot Experimental Treatment 1 Intervention

AI-powered chatbox designed specifically for oral cancer education. The chatbot is programmed to provide accurate information on oral cancer risks, symptoms, preventive measures, and the importance of regular dental check-ups.

Group II: Traditional Educational Materials Active Control 1 Intervention

Receiving oral cancer educational materials (handouts from trusted sources such as the Centers for Disease Control (CDC) and American Cancer Association (ACA) and other reliable health education resources.

Who Is Running the Clinical Trial?

Virginia Commonwealth University

Lead Sponsor

Trials

732

Recruited

22,900,000+

American Association for Cancer Education

Collaborator

Trials

2

Recruited

240+

Findings from Research

In a study involving 95,166 patients, 64.2% engaged with a clinical chatbot designed to assess hereditary cancer risk, with 89.4% completing the risk assessment, indicating high acceptability and usability of the tool.

The chatbot identified that 25% of users met the criteria for genetic testing for hereditary cancer syndromes, and among those tested, 5.6% had a pathogenic variant, demonstrating its effectiveness in triaging high-risk patients for further evaluation.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Hereditary Cancer Risk Using a Genetic Chatbot Before Routine Care Visits. Nazareth, S., Hayward, L., Simmons, E., et al.[2023]

A study evaluating responses to 200 medication-use questions found that a medication database provided more clinically correct, complete, safe, and useful answers than an AI chatbot, with 97% of questions answered by the database compared to 80% by the chatbot.

While the chatbot's clinical correctness was comparable to the database at 85%, it lagged behind in completeness (65%), safety (71%), and usefulness (68%), indicating a need for further improvements in chatbot technology for reliable clinical use.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Evaluation of inpatient medication guidance from an artificial intelligence chatbot. Beavers, J., Schell, RF., VanCleave, H., et al.[2023]

The pilot version of the Rosa chatbot, developed over two years with input from patients and healthcare professionals, aims to assist breast and ovarian cancer patients in understanding genetic BRCA testing, highlighting the importance of user-centered design in health technology.

Despite initial challenges with AI matching user questions to answers, the final version of the chatbot significantly expanded its database and received positive feedback from users regarding its layout and trustworthiness, indicating potential for real-world application in healthcare settings.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Ask Rosa - The making of a digital genetic conversation tool, a chatbot, about hereditary breast and ovarian cancer. Siglen, E., Vetti, HH., Lunde, ABF., et al.[2022]

ChatGPT provided correct answers to 71.9% of questions about obstructive sleep apnea, indicating it can be a useful tool for patient education, regardless of the type of prompting used.

Prompting for statistics and references significantly improved the quality of responses, with 96.1% of those answers including references, while patient-friendly prompts resulted in simpler language suitable for patients, maintaining an acceptable grade level for medical information.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Evaluating ChatGPT responses on obstructive sleep apnea for patient education. Campbell, DJ., Estephan, LE., Mastrolonardo, EV., et al.[2023]

References

1. United States pubmed.ncbi.nlm.nih.gov

Evaluation of a Diabetes Education Call Center intervention. [2007]

2. Germany pubmed.ncbi.nlm.nih.gov

Interactive technologies and videotapes for patient education in cancer care: systematic review and meta-analysis of randomised trials. [2018]

3. United States pubmed.ncbi.nlm.nih.gov

Oral cancer knowledge and examination experiences among North Carolina adults. [2019]

4. Brazil pubmed.ncbi.nlm.nih.gov

Distance learning course improves primary care dentists' diagnosis and self-efficacy in the management of oral lesions. [2022]

5. United States pubmed.ncbi.nlm.nih.gov

The influence of patient education by the dental hygienist: acceptance of the fluorescence oral cancer exam. [2016]

6. United States pubmed.ncbi.nlm.nih.gov

Hereditary Cancer Risk Using a Genetic Chatbot Before Routine Care Visits. [2023]

7. United States pubmed.ncbi.nlm.nih.gov

Usability Testing of a Web-Based Decision Aid for Breast Cancer Risk Assessment Among Multi-Ethnic Women. [2022]

8. England pubmed.ncbi.nlm.nih.gov

Evaluation of inpatient medication guidance from an artificial intelligence chatbot. [2023]

9. Ireland pubmed.ncbi.nlm.nih.gov

Ask Rosa - The making of a digital genetic conversation tool, a chatbot, about hereditary breast and ovarian cancer. [2022]

10. United States pubmed.ncbi.nlm.nih.gov

Evaluating ChatGPT responses on obstructive sleep apnea for patient education. [2023]

11. Switzerland pubmed.ncbi.nlm.nih.gov

Using a Virtual Patient via an Artificial Intelligence Chatbot to Develop Dental Students' Diagnostic Skills. [2022]

12. United States pubmed.ncbi.nlm.nih.gov

Utilizing ChatGPT-4 for Providing Information on Periodontal Disease to Patients: A DISCERN Quality Analysis. [2023]

13. United States pubmed.ncbi.nlm.nih.gov

Qualitative exploration of digital chatbot use in medical education: A pilot study. [2022]