300 Participants Needed

Computer-Animated Character for Understanding Medical Illustrations

Recruiting at 1 trial location
TB
Overseen ByTimothy Bickmore, PhD
Age: 18+
Sex: Any
Trial Phase: Academic
Sponsor: Northeastern University
No Placebo GroupAll trial participants will receive the active study treatment (no placebo)

What You Need to Know Before You Apply

What is the purpose of this trial?

This trial explores how well people understand medical illustrations with the assistance of a computer-animated character, known as an Embodied Conversational Agent (ECA). The study tests whether viewing this character on a regular computer screen or in virtual reality improves understanding and reduces anxiety compared to reading independently. It suits individuals who speak English or Spanish fluently and have adequate vision to read educational materials. Participants will either use a computer-animated guide in 2D or 3D or read without digital assistance. As an unphased trial, this study provides a unique opportunity to contribute to innovative research that could enhance patient education and reduce anxiety.

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 prior data suggests that this computer-animated character is safe for understanding medical illustrations?

Research has shown that using animated helpers on computer screens, known as 2D embodied conversational agents (ECAs), is generally safe. Studies have found no major safety concerns when these agents discuss health topics. Similarly, researchers have examined 3D ECAs, used in virtual reality, for their role in training and health education, with no significant safety issues reported. Both types of ECAs help people understand and engage with health information, indicating they are well-tolerated and safe for use in studies like this one.12345

Why are researchers excited about this trial?

Researchers are excited about the use of Embodied Conversational Agents (ECAs) because they could transform how patients understand medical information. Unlike traditional methods, which rely on static text and images, ECAs provide interactive, personalized explanations, making complex medical concepts easier to grasp. The trial explores two unique formats: a 2D version on a computer monitor and an immersive 3D experience in virtual reality. These innovative approaches aim to enhance patient comprehension and engagement, potentially leading to better health outcomes.

What evidence suggests that the Embodied Conversational Agent is effective for understanding medical illustrations?

Studies have shown that digital assistants, known as Embodied Conversational Agents (ECAs), greatly enhance how people understand and engage with healthcare information. Research indicates that ECAs help people learn more and even improve their quality of life. These digital assistants excel at explaining complex information in an easy-to-understand manner by offering interactive and personalized explanations. In this trial, participants will experience either a 2D or 3D version of these assistants, both of which have increased user interest and serve as useful tools for explaining medical images. Although specific data on reducing anxiety is limited, the engaging nature of ECAs suggests they might help by making information easier to grasp.12367

Who Is on the Research Team?

TB

Timothy Bickmore, PhD

Principal Investigator

Northeastern University

Are You a Good Fit for This Trial?

This trial is for adults over 18 who speak English or Spanish fluently, can consent on their own, and have good enough vision (with glasses if needed) to read educational documents. There are no specific exclusion criteria listed.

Inclusion Criteria

Has adequate corrected vision to read patient education documents
I can make my own medical decisions.
I am over 18 years old.

Exclusion Criteria

Not applicable.

Timeline for a Trial Participant

Screening

Participants are screened for eligibility to participate in the trial

1-2 weeks

Treatment

Participants engage with patient education documents using different methods: unaided, with a 2D ECA, or with a 3D ECA in virtual reality

30 minutes
1 session (in-person or virtual)

Follow-up

Participants are assessed for knowledge, anxiety, satisfaction, reading effort, and acceptability after the session

30 minutes
1 session (in-person or virtual)

What Are the Treatments Tested in This Trial?

Interventions

  • Embodied Conversational Agent (ECA)
Trial Overview The study tests an Embodied Conversational Agent (ECA), a computer-animated character that explains medical illustrations. It compares understanding with the ECA against self-explanation and also looks at the difference between viewing the ECA on a computer versus in virtual reality.
How Is the Trial Designed?
3Treatment groups
Experimental Treatment
Active Control
Group I: ECA-3DExperimental Treatment1 Intervention
Group II: ECA-2DExperimental Treatment1 Intervention
Group III: CONTROLActive Control1 Intervention

Find a Clinic Near You

Who Is Running the Clinical Trial?

Northeastern University

Lead Sponsor

Trials
103
Recruited
72,600+

Boston University

Collaborator

Trials
494
Recruited
9,998,000+

Tufts Medical Center

Collaborator

Trials
264
Recruited
264,000+

Published Research Related to This Trial

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.
Evaluation of inpatient medication guidance from an artificial intelligence chatbot.Beavers, J., Schell, RF., VanCleave, H., et al.[2023]
A focus group study involving 12 women with previous cesareans and 8 prenatal providers evaluated an Embodied Conversational Agent (ECA) designed to assist in decision-making about birth options, revealing that both groups found the ECA could effectively provide information and support during consultations.
Participants noted that while the ECA appeared somewhat 'robot-like,' improvements in its visual appeal and clarity regarding its role in the decision-making process are necessary for better integration into patient care.
The Perspectives of Women and Their Health-Care Providers Regarding Using an ECA to Support Mode of Birth Decisions.Chinkam, S., Steer-Massaro, C., Herbey, I., et al.[2022]

Citations

Embodied Conversational Agents for Chronic DiseasesRegarding effectiveness-related outcomes, improvements in behavior, knowledge, symptoms, and quality of life were observed in the reviewed studies, whereas ...
Embodied Conversational Agents for Chronic DiseasesThis scoping review aims to identify the current practice in the development and evaluation of ECAs for chronic diseases.
Trustworthy Embodied Conversational Agents for HealthcareThe ECA collects data and provides recommendations based on expert personnel knowledge and procedures, while ensuring appropriate treatment of patients' data ...
Design Features of Embodied Conversational Agents in ...Embodied conversational agents (ECAs) are gaining interest to elicit user engagement and stimulate actual use of eHealth applications.
Conversational agents in healthcare: a systematic reviewThe only RCT evaluating the efficacy of a conversational agent found a significant effect in reducing depression symptoms (effect size d = 0.44, p = .04).
Embodied Conversational Agents for Chronic DiseasesFor example, 3% (1/36) of the studies reported that an agent with 2D animation would blink her eyes every 10 seconds and move her mouth for ...
Towards Embodied Conversational Agents for Reducing ...These affective barriers can severely impair cognitive performance—leading to poorer outcomes, diminished self-efficacy, and avoidance behaviors ...
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