Evaluating an AI-Generated Health Podcast
Trial statusRecruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
Age18+
SponsorQassim University
About this trial
This study aims to explore a new way of delivering health information using an AI-generated podcast. The podcast, created with Google NotebookLM, uses verified content from the American Academy of Periodontology website to provide easy-to-understand information on gum health and prevention.
The goal is to determine whether this AI-generated podcast is a useful, engaging, and clear tool for educating the general public about health topics. Traditional health podcasts often feature expert interviews and can be lengthy, which sometimes limits their appeal and accessibility. By using AI to generate the podcast, investigator hope to offer a more standardized and concise presentation that avoids technical jargon.
To evaluate the podcast, investigator developed a questionnaire based on the Questionnaire for Assessing Educational Podcasts (QAEP). This questionnaire was adapted to better suit a non-specialist audience and covers four key areas: how easy the podcast is to access and use, the design and structure of the podcast, the clarity and completeness of the content, and the podcast's value as a learning tool.
Before using this questionnaire with the general public, investigator sent it to 10 experts in dentistry, public health, and communication for their review and feedback. Their input helped us make minor modifications to ensure the questionnaire is both clear and scientifically sound. After these revisions, investigator conducted a pilot study with 30 members of the general public who listened to the podcast and completed the questionnaire.
This study will assess the feasibility and validity of using an AI-generated podcast as a health education tool. The results will help determine if this approach can effectively improve public understanding of health information and may guide the future design of digital health communication strategies.
Eligibility criteria
This trial accepts healthy volunteersQualifiers
Licensed professionals and recognized experts in relevant fields such as dentistry, public health, and health communication
Minimum of 5 years of professional experience in their respective fields
Prior involvement in healthcare education, research, or digital health communication
Willingness to review and provide detailed feedback on the adapted questionnaire
Disqualifiers
Professionals without formal training or relevant expertise in the specified fields
Individuals with conflicts of interest that might compromise the objectivity of their evaluations
Experts who are unable to commit the necessary time to provide thorough feedback
Adults aged 18 years or older
Trial population
Expert Group: Approximately 10 professionals from fields such as dentistry, public health, and health communication. Their extensive experience and academic backgrounds ensure rigorous content and reliability validation of the questionnaire, making it scientifically robust for assessing AI-generated health podcasts. General Public Group: Around 30 individuals from diverse demographic backgrounds (age, gender, education) representing the target audience. They will evaluate the AI-generated podcast on gum health and prevention using the validated questionnaire, providing insights into the podcast's accessibility, clarity, and educational impact.
Trial design
Design model
Other
Time perspective
Other
Treatments tested in this trial
Expert Evaluation of Adapted Questionnaire
Other interventionThis intervention involves inviting a group of subject matter experts-including dental specialists, public health professionals, and communication experts-to evaluate the adapted questionnaire. The questionnaire, derived from the Questionnaire for Assessing Educational Podcasts (QAEP) and tailored for assessing an AI-generated health podcast, covers four dimensions: Access and Use, Design and Structure, Content Adequacy, and Value as an Aid to Learning. Experts will complete a structured online survey (via Google Form) to rate each item's clarity, relevance, and necessity. Their feedback is integral to refining and validating the instrument prior to its use with the general public.
AI-Generated Health Podcast Evaluation
Other interventionParticipants in this group will first listen to a 4-minute AI-generated health podcast on gum health and prevention. The podcast was produced using Google NotebookLM and is based on publicly available information from the American Academy of Periodontology, with appropriate source credit. After listening, participants will complete a validated questionnaire (administered via Google Form) that assesses the podcast's accessibility, design, content adequacy, and educational value. This intervention is designed to measure public perception, engagement, and overall feasibility of using AI-generated podcasts as an educational tool for health communication.
Treatment groups
30 Participants
are divided into 2 treatment groupsGroup A: Expert Validation Group2 interventions
Group B: General Public Cohort2 interventions
Trial outcomes
Primary outcomes
1
Content Validity Index (CVI) of the Adapted Questionnaire
Description: This outcome measure evaluates the content validity of the questionnaire adapted from QAEP, as determined by expert ratings. The Content Validity Index (CVI) quantifies the proportion of experts who rate questionnaire items as relevant or highly relevant. Unit of Measure: Score on a scale from 0 to 1, where scores above 0.78 indicate acceptable content validity
Time frame
From 7th February 2025 to 25th February 20252
Internal Consistency Reliability of the Adapted Questionnaire
Description: This outcome measure assesses the internal consistency reliability of the adapted questionnaire using Cronbach's Alpha coefficient, which measures how closely related the items are as a group. Unit of Measure: Cronbach's Alpha coefficient on a scale from 0 to 1, where values above 0.7 indicate acceptable reliability
Time frame
From 7th February 2025 to 25th February 20253
Public Perception Score of the AI-Generated Health Podcast
Description: This outcome measure assesses the general public's overall perception of the AI-generated health podcast using the validated questionnaire. Unit of Measure: Composite score on a 5-point Likert scale (1-5), where 1 represents "Strongly Disagree" and 5 represents "Strongly Agree"
Time frame
From 27th February 2025 to 15th April 20254
Domain-Specific Evaluation Scores of the AI-Generated Health Podcast
Description: This outcome measure assesses the general public's evaluation of specific domains of the AI-generated health podcast, including accessibility, design, content adequacy, and educational value. Unit of Measure: Mean scores for each domain on a 5-point Likert scale (1-5), where 1 represents "Strongly Disagree" and 5 represents "Strongly Agree"
Time frame
From 27th February 2025 to 15th April 2025Sponsors and contacts
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Source ClinicalTrials.gov