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Uncovering the Top Nonadvertising Weight Loss Websites on Google: A Data-Mining Approach

. 2024 Dec 11 ; 4 () : e51701. [epub] 20241211

Language English Country Canada Media electronic

Document type Journal Article

Links

PubMed 39661980
PubMed Central PMC11669867
DOI 10.2196/51701
PII: v4i1e51701
Knihovny.cz E-resources

BACKGROUND: Online weight loss information is commonly sought by internet users, and it may impact their health decisions and behaviors. Previous studies examined a limited number of Google search queries and relied on manual approaches to retrieve online weight loss websites. OBJECTIVE: This study aimed to identify and describe the characteristics of the top weight loss websites on Google. METHODS: This study gathered 432 Google search queries collected from Google autocomplete suggestions, "People Also Ask" featured questions, and Google Trends data. A data-mining software tool was developed to retrieve the search results automatically, setting English and the United States as the default criteria for language and location, respectively. Domain classification and evaluation technologies were used to categorize the websites according to their content and determine their risk of cyberattack. In addition, the top 5 most frequent websites in nonadvertising (ie, nonsponsored) search results were inspected for quality. RESULTS: The results revealed that the top 5 nonadvertising websites were healthline.com, webmd.com, verywellfit.com, mayoclinic.org, and womenshealthmag.com. All provided accuracy statements and author credentials. The domain categorization taxonomy yielded a total of 101 unique categories. After grouping the websites that appeared less than 5 times, the most frequent categories involved "Health" (104/623, 16.69%), "Personal Pages and Blogs" (91/623, 14.61%), "Nutrition and Diet" (48/623, 7.7%), and "Exercise" (34/623, 5.46%). The risk of being a victim of a cyberattack was low. CONCLUSIONS: The findings suggested that while quality information is accessible, users may still encounter less reliable content among various online resources. Therefore, better tools and methods are needed to guide users toward trustworthy weight loss information.

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Uncovering the Top Nonadvertising Weight Loss Websites on Google: A Data-Mining Approach

. 2024 Dec 11 ; 4 () : e51701. [epub] 20241211

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