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Differences in Fear and Negativity Levels Between Formal and Informal Health-Related Websites: Analysis of Sentiments
Abigail Paradise Vit1, Avi Magid1,2
1Department of Information Systems, The Max Stern Yezreel Valley College, Emek Yezreel, Israel.
Journal of Medical Internet Research
|August 9, 2024
Summary
Formal health websites, despite their credibility, were found to have higher levels of fear and negativity compared to informal sites. This suggests a need for more positive online health information to improve public engagement and trust.
Area of Science:
- Health Informatics
- Natural Language Processing
- Public Health Communication
Background:
- Public health-related web searches are common and can influence health decisions, potentially leading to anxiety and self-diagnosis.
- Searches often focus on critical conditions like cancer, cardiovascular diseases, and infectious diseases.
- Both formal and informal health websites can evoke negative emotions such as fear.
Purpose of the Study:
- To investigate differences in fear and negativity levels between formal and informal health-related websites.
- To assess the emotional impact of online health information sources on the public.
Main Methods:
- Collected and classified 1448 unique health-related websites into formal (534) and informal (914) categories.
- Utilized three transformer models to evaluate fear and negativity in website content.
- Employed t-tests to statistically compare fear and negativity levels between formal and informal websites.
Main Results:
- Formal websites exhibited statistically significant higher levels of fear (mean 0.388 vs. 0.366) compared to informal websites.
- Negativity levels were also significantly higher on formal websites (mean 0.657 vs. 0.636) than on informal ones.
- Analysis included 1820 result pages from formal and 1494 from informal websites.
Conclusions:
- The findings indicate that formal health websites may inadvertently induce more fear and negativity.
- Enhancing the positivity of text on formal health websites could boost credibility and public adherence to recommendations.
- Recommends using natural language processing (NLP) tools to pre-screen health content for a more positive dissemination.
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