What is Search Bias in a systematic review?

People frequently assume that search engines provide search results neutrally and without bias because of their automated activities. This perception, however, is incorrect. Like any other media organization, search engines intentionally regulate their users’ experiences, which skews search results. Finally, some observers argue that search engine bias is a flaw that must be addressed by regulation. 

Bias in research is a systematic error that leads to the recognition of study findings and conclusions without considering the likelihood of unfair or misleading presentation. Bias may enter the research process at any point, from deciding on a study question to determining how to assess your results and choosing which findings to publish. 

Search engines help users acquire relevant search results from the vast amount of material on the Internet. GSE generates individualized profiles of its consumers for targeted advertising services by gathering data about them. This semantic search capability enables GSE to discern the meaning of confusing phrases in a query. In a subtle way, this subjective significance-increasing process may influence people to specific ideas and opinions. 

Although there are several strategies for identifying bias in primary research, there are far fewer for assessing bias in systematic reviews. Since 2007, the AMSTAR checklist has been the most widely used instrument for assessing the quality of systematic reviews. ROBIS (risk of bias in systematic reviews), a newer method, analyzes bias inside a systematic review using a domain-based approach. ROBIS’s developers characterize their target audience as authors of systematic review overviews (review of studies), those who generate evidence-based guidelines, and systematic review authors who want to assess the risk of bias inside their review. 

References 

Mikolajewicz, Nicholas, and Svetlana V. Komarova. “Meta-analytic methodology for basic research: a practical guide.” Frontiers in physiology 10 (2019): 203.