The impact of imperfect user rating strategies on Health-related Laymen-evaluated Platforms

Health-related Laymen-evaluated Platforms (HLEPs) are online health-related Q&A platforms (OHQPs), and have become a dominant unofficial channel for patients seeking medical advice in China. This research raises the issue of whether the design features of HLEPs (e.g., lay evaluators, swift turnaround, and non-existing search and peer rating functions) are rendering them intrinsically inefficient in medical consulting. By analyzing online patients’ evaluations of medical advice using natural language processing over 3M Chinese texts over six months and comparing those to independent offline doctors’ evaluations using 13k online answers, I found that over 2/3 of the time patients settled for suboptimal medical advice, possibly due to confirmation biases and selective information adoption.