Evaluating an AI-Generated Health Podcast

March 22, 2025 updated by: Dr Shiva Shankar Bugude, Qassim University

Feasibility and Validity Assessment of an AI-Generated Health Podcast: A Pilot Observational Study

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.

Study Overview

Detailed Description

Background and Rationale Recent advances in digital media have underscored the potential of podcasts as an innovative medium for disseminating healthcare information. Traditional health podcasts, while valuable, often suffer from limitations such as lengthy duration, inconsistent quality, and the use of complex medical jargon that may hinder public understanding. In contrast, artificial intelligence (AI)-driven content generation offers an opportunity to create concise, standardized, and accessible audio content. This study leverages Google NotebookLM to generate a podcast on gum health and prevention using publicly available information from the American Academy of Periodontology (AAP). By doing so, the research aims to explore whether an AI-generated health podcast can effectively enhance public health literacy.

Objectives

The primary objective of this pilot study is to evaluate the feasibility and validity of an AI-generated health podcast as an educational tool for the general public. Specific objectives include:

  1. Questionnaire Development: Develop and validate a structured questionnaire-adapted from the Questionnaire for Assessing Educational Podcasts (QAEP)-that captures public perceptions regarding podcast accessibility, design, content adequacy, and educational value.
  2. Reliability and Validity Testing: Assess the reliability and content validity of the newly developed questionnaire through expert evaluation and statistical analysis.
  3. Public Evaluation of Podcast Quality: Assess the general public's perceptions of the AI-generated health podcast, focusing on its accessibility, design, content quality, and overall educational value, using the validated questionnaire.

Study Design and Methods

This study is designed as a prospective, observational feasibility pilot. It consists of two phases:

Phase 1: Instrument Development and Expert Validation A questionnaire was developed using QAEP as a benchmark and then refined based on feedback from 10 experts (including dental, public health, and communication specialists). Statistical analyses (Cronbach's Alpha, Content Validity Index, and Exploratory Factor Analysis) were conducted to ensure the tool's reliability and validity.

Phase 2: Public Pilot Evaluation The validated questionnaire was administered via an online Google Form to 30 general public participants. Demographic data-including age, gender, educational background, and English audio comprehension-were collected to contextualize the findings.

Study Type

Observational

Enrollment (Estimated)

30

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

  • Name: Shiva Shankar Bugude, MDS
  • Phone Number: +966531476028
  • Email: S.ggg@qu.edu.sa

Study Contact Backup

Study Locations

    • Al Qassim
      • Al Kharj, Al Qassim, Saudi Arabia, 58883
        • Recruiting
        • College of Applied Medical Sciences
        • Contact:
          • Shiva Shankar Bugude, MDS
          • Phone Number: +966531476028
          • Email: S.ggg@qu.edu.sa

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

Yes

Sampling Method

Non-Probability Sample

Study 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.

Description

Expert Group

Inclusion Criteria:

  • 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
  • Ability to complete the survey in English

Exclusion Criteria:

  • 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

General Public Group

Inclusion Criteria:

  • Adults aged 18 years or older
  • Individuals fluent in English
  • Access to a digital audio device and an internet connection to listen to the podcast and complete the survey
  • Consent to participate in the study

Exclusion Criteria:

  • Individuals with significant hearing impairments that might hinder the ability to comprehend the audio content
  • Healthcare professionals or individuals with advanced training in dentistry or health communication
  • Persons who have participated in similar educational podcast studies previously

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort
Intervention / Treatment
Expert Validation Group
This group comprises approximately 10 subject matter experts-including dental specialists, public health professionals, and communication experts-who are engaged in evaluating and refining the adapted questionnaire. Their feedback on clarity, relevance, and content validity is used to ensure that the measurement tool is scientifically robust before its deployment in the subsequent phase of the study.
This 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.
Participants 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.
General Public Cohort
This group includes approximately 30 participants from the general public representing diverse ages, genders, and educational backgrounds. Participants in this cohort will listen to the AI-generated health podcast (focused on gum health and prevention) and then complete the validated questionnaire to assess the podcast's accessibility, design, content adequacy, and educational value.
This 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.
Participants 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.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Content Validity Index (CVI) of the Adapted Questionnaire
Time Frame: From 7th February 2025 to 25th February 2025

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

From 7th February 2025 to 25th February 2025
Internal Consistency Reliability of the Adapted Questionnaire
Time Frame: From 7th February 2025 to 25th February 2025

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

From 7th February 2025 to 25th February 2025
Public Perception Score of the AI-Generated Health Podcast
Time Frame: From 27th February 2025 to 15th April 2025

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"

From 27th February 2025 to 15th April 2025
Domain-Specific Evaluation Scores of the AI-Generated Health Podcast
Time Frame: From 27th February 2025 to 15th April 2025

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"

From 27th February 2025 to 15th April 2025

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Investigators

  • Principal Investigator: Shiva Shankar Bugude, MDS, Qassim University

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

February 7, 2025

Primary Completion (Estimated)

April 15, 2025

Study Completion (Estimated)

May 20, 2025

Study Registration Dates

First Submitted

March 17, 2025

First Submitted That Met QC Criteria

March 17, 2025

First Posted (Actual)

March 25, 2025

Study Record Updates

Last Update Posted (Actual)

March 26, 2025

Last Update Submitted That Met QC Criteria

March 22, 2025

Last Verified

March 1, 2025

More Information

Terms related to this study

Other Study ID Numbers

  • QassimU5

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

UNDECIDED

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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