An online analysis: Do websites focus on IUD insertion pain and management?
Description
Data Set Guide Search Terms: “IUD”, “Intrauterine Device”, “Copper IUD”, “Paragard”, “Hormonal IUD”, “Mirena”, “Skyla IUD”, “Liletta”, “Kyleena” across Google, Bing, and Yahoo. Data Set 1: First 25 search results from Google for each search term. Data Set 2: First 25 search results from Bing for each search term. Data Set 3: First 25 search results from Yahoo for each search term. Data Set 4: Combined dataset of all URLs collected across Google, Bing, and Yahoo Data Set 5: Master dataset including all collected URLs, with identification and removal of duplicates and application of exclusion criteria. Data Set 6: Final dataset after exclusion criteria, analyzed in Qualtrics for presence of IUD insertion pain and readability metrics. Data Set 7: Subset of URLs that mention IUD insertion pain, analyzed in Qualtrics for JAMA benchmark criteria and reported pain management strategies. Data Set 8: Subset of URLs that mention IUD insertion pain, analyzed using readability assessment tools.
Files
Steps to reproduce
1. Perform searches on Google, Bing, and Yahoo using the following terms: “IUD”, “Intrauterine Device”, “Copper IUD”, “Paragard”, “Hormonal IUD”, “Mirena”, “Skyla IUD”, “Liletta”, and “Kyleena.” 2. For each search term and search engine, record the first 25 search results (URLs) on Zotero, a research management tool. 3. Combine all results into a master dataset (up to 75 URLs per search term). 4. Remove duplicate URLs across all search engines. 5. Apply exclusion criteria: -- Marketing or promotional pages -- Non-English websites -- Non-text or inaccessible content -- Websites with continuous scrolling or multiple embedded articles 6. The remaining URLs form the final dataset for analysis. 7. Analyze all included websites for: -- Presence and context of pain (categorized as pre-insertion, during insertion, during removal, and post-insertion) --Pain management strategies (categorized as NSAIDs, lidocaine or other local anesthetic agents, and “other,” with specific tracking of the “other” category) 8. Assess readability by entering each website URL into Readable (Readable.com) to obtain: --Simple Measure of Gobbledygook (SMOG) Index --Flesch-Kincaid Grade Level (FKGL) 9. Evaluate transparency using the Journal of the American Medical Association (JAMA) benchmark criteria, including authorship, attribution, disclosure, and currency.