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Related Concept Videos

Health Literacy01:21

Health Literacy

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Health literacy is an individual's or a community's capacity to comprehend, receive, read, and use relevant healthcare information and services. The World Health Organization (WHO, 2018) defines health literacy as the cognitive and social skills that determine the ability of individuals to gain access to, understand, and use information in ways that promote and maintain good health. As a result, the WHO helps individuals manage long-term health concerns, participate in preventative...
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Classification of Illness01:17

Classification of Illness

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The meaning of illness is individualized to each person who experiences an alteration in health. In contrast, disease is a medical term indicating a pathological change in the structure and function of the body or mind. It is a condition that has specific symptoms and boundaries.
An illness is a response to a disease in which the person's level of functioning is changed compared with a previous level. The general classification of illness includes acute and chronic.
Acute illness is severe...
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Levels of Health Promotion and Illness Prevention01:26

Levels of Health Promotion and Illness Prevention

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Health promotion allows a person to control the determinants of health, resulting in an improved health status. It enhances the quality of life and reduces premature deaths. Health promotion and illness prevention programs help people make beneficial choices to reduce the risk of disease and disabilities. There are three health promotion and illness prevention levels: primary, secondary, and tertiary prevention.
In primary prevention, actions taken before disease onset prevent the disease from...
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Models of Health Promotion and Illness Prevention I01:25

Models of Health Promotion and Illness Prevention I

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A model is a theoretical way to understand a concept or an idea. Models can overcome barriers to health regardless of diverse economic and cultural backgrounds. In addition, models make the task easier by providing different ways to approach complex issues. There are two major health promotion models: the health belief model and the health promotion model.
The health belief model (HBM) attempts to predict health-related behavior in specific belief patterns. According to the HBM, a person's...
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Models of Health Promotion and Illness Prevention II01:18

Models of Health Promotion and Illness Prevention II

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The person's health status fluctuates continually, varying from being in good health to becoming ill and returning to being healthy. To understand the concept of illness prevention, there are two models. First, the health-illness continuum model is a graphic representation of an individual's wellness. It states that a person is considered healthy in the absence of physical disease and the presence of good emotional health.
The agent-host-environment model states that disease results...
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Concepts of Health and Illness01:29

Concepts of Health and Illness

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Health is a condition of the body, mind, and spirit where an individual remains free from illness. Similarly, wellness is an active state, including living a lifestyle that promotes physical, mental, and emotional health. Physical health is critical for the overall well-being and can be affected by lifestyle, activity level, diet, and behavior. The highest attainable standard of health is a fundamental and universal human right. Consider Lisa, a fifteen-year-old born with congenital...
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Related Experiment Video

Updated: May 15, 2025

Visualization of Intensity Levels to Reduce the Gap Between Self-Reported and Directly Measured Physical Activity
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Promoting Health Literacy With Human-in-the-Loop Video Understandability Classification of YouTube Videos:

Xiao Liu1, Anjana Susarla2, Rema Padman3

  • 1Department of Information Systems, W. P. Carey School of Business, Arizona State University, Tempe, AZ, United States.

Journal of Medical Internet Research
|April 8, 2025
PubMed
Summary
This summary is machine-generated.

Developing an automated approach to assess health video understandability on YouTube significantly boosts viewer engagement. Highly understandable videos receive more views, likes, and comments, aiding experts in recommending quality patient education materials.

Keywords:
AIartificial intelligenceaugmented intelligencecotraininghuman-in-the-loopmachine learningpatient educationvideo analysisvideo understandability

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Area of Science:

  • Digital Health
  • Health Communication
  • Artificial Intelligence in Healthcare

Background:

  • Most US adults use the internet for health information, but few possess adequate health literacy.
  • A significant gap exists in understanding online health content, particularly on social media platforms like YouTube.
  • There's a critical need for automated methods to curate accessible online health information for diverse populations.

Purpose of the Study:

  • To develop an automated system for assessing patient educational video understandability using the Patient Education Materials Assessment Tool (PEMAT) criteria.
  • To evaluate how video understandability influences viewer engagement metrics.
  • To provide actionable insights for content creators and healthcare organizations to enhance engagement with online health videos.

Main Methods:

  • An augmented intelligence approach combining human expertise and machine learning was employed.
  • Patient Education Materials Assessment Tool (PEMAT) constructs were mapped to video features and expert annotations.
  • Machine learning models, including cotraining, were used to classify video understandability for diabetes-related content.

Main Results:

  • The automated system achieved high accuracy (F1-score of 0.81) in classifying video understandability.
  • Highly understandable videos demonstrated significantly higher view counts (ATE=2.55), like counts (ATE=2.95), and comment counts (ATE=3.10).
  • Medical experts recommended understandable videos more frequently (72%) compared to those ranked by YouTube's algorithm (40%).

Conclusions:

  • A scalable, human-in-the-loop algorithm was developed to assess health information understandability on YouTube.
  • The approach effectively merges expert knowledge with algorithmic capabilities to improve content engagement.
  • This tool assists medical experts in recommending educational content and guides organizations in creating better patient education materials.