Abstract
Background
Despite the growing accessibility of web-based information related to spinal cord stimulation (SCS), the content and quality of commonly encountered websites remain unknown.
Objective
This study aimed to assess the content and quality of web-based information on SCS.
Methods
This qualitative study was prospectively registered in Open Science Framework. Google Trends was used to identify the top trending, SCS-related search queries from 2012 to 2022. Top queried terms were then entered into separate search engines. Information found on websites within the first 2 pages of results was extracted and assessed for quality using the DISCERN instrument, the Journal of the American Medical Association benchmark criteria, and the Health on the Net Foundation code of conduct certification. Website readability and SCS-related information were also assessed.
Results
After exclusions, 42 unique sites were identified (scientific resources: n=6, nonprofit: n=12, for-profit: n=20, news or media: n=2, and personal or blog: n=2). Overall, information quality was moderate (DISCERN). Few sites met all the Journal of the American Medical Association benchmark criteria (n=3, 7%) or had Health on the Net Foundation certification (n=7, 16%). On average, information was difficult to read, requiring a 9th- to 10th-grade level of reading comprehension. Sites described SCS subcategories (n=14, 33%), indications (n=38, 90%), contraindications (n=14, 33%), side effects or risks (n=28, 66%), device considerations (n=25, 59%), follow-up (n=22, 52%), expected outcomes (n=31, 73%), provided authorship details (n=20, 47%), and publication dates (n=19, 45%). The proportion of for-profit sites reporting authorship information was comparatively less than other site types (n=3, 15%). Almost all sites focused on surgically implanted SCS (n=37, 88%). On average, nonprofit sites contained the greatest number of peer-reviewed reference citations (n=6, 50%). For-profit sites showed the highest proportion of physician or clinical referrals among site types (n=17, 85%) indicating implicit bias (ie, auto-referral).
Conclusions
Overall, our findings suggest the public may be exposed to incomplete or dated information from unidentifiable sources that could put consumers and patient groups at risk.