Clinical trial NCT06891495: Evaluating an AI-Generated Health Podcast
Official title: Feasibility and Validity Assessment of an AI-Generated Health Podcast: A Pilot Observational Study
Study type: OBSERVATIONAL
Overall status: RECRUITING
Conditions: Public Health
Artificial Intelligence
Feasibility Studies
Lead sponsor: Qassim University
Sponsor class: OTHER
First posted: 2025-03-24
Enrollment: 30
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Observational model: OTHER
Time perspective: OTHER
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.

Brief summary: 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.

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.

Eligibility criteria: 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

Primary outcomes:
measure: Content Validity Index (CVI) of the Adapted Questionnaire
timeFrame: From 7th February 2025 to 25th February 2025
measure: Internal Consistency Reliability of the Adapted Questionnaire
timeFrame: From 7th February 2025 to 25th February 2025
measure: Public Perception Score of the AI-Generated Health Podcast
timeFrame: From 27th February 2025 to 15th April 2025
measure: Domain-Specific Evaluation Scores of the AI-Generated Health Podcast
timeFrame: From 27th February 2025 to 15th April 2025
Secondary outcomes:
Other outcomes:
Locations:
city: Al Kharj
country: Saudi Arabia
facility: College of Applied Medical Sciences
state: Al Qassim
Study officials:
affiliation: Qassim University
name: Shiva Shankar Bugude, MDS
role: PRINCIPAL_INVESTIGATOR
References:
citation: Loeb S, Sanchez Nolasco T, Siu K, Byrne N, Giri VN. Usefulness of podcasts to provide public education on prostate cancer genetics. Prostate Cancer Prostatic Dis. 2023 Dec;26(4):772-777. doi: 10.1038/s41391-023-00648-4. Epub 2023 Jan 21.
citation: Alarcon R, Blanca MJ. Development and Psychometric Properties of the Questionnaire for Assessing Educational Podcasts (QAEP). Front Psychol. 2020 Nov 23;11:579454. doi: 10.3389/fpsyg.2020.579454. eCollection 2020.
citation: Leite PL, Torres FAF, Pereira LM, Bezerra AM, Machado LDS, Silva MRFD. Construction and validation of podcast for teen sexual and reproductive health education. Rev Lat Am Enfermagem. 2022 Oct 3;30(spe):e3706. doi: 10.1590/1518-8345.6263.3706. eCollection 2022.