A Response Quality Model for Online Health Communities Research-in-Progress

It has been reported that about 113 million Americans has looked for health information on the internet. Patient safety can therefore be very easily compromised if the advice/information that people receive is incorrect. Particularly in case of a chronic and debilitating disease like Parkinson’s disease, patients are very vulnerable to false information. Spread of misinformation can be a serious deterrent to information system use. However, the literature has been weak in linking the prevalence of misinformation on online social networks to the factors contributing to misinformation. This study seeks to reduce this gap by exploring the factors impacting the extent of misinformation in online social networking forum. Our findings show that the quality of a response is affected by clarity of the thread question, cumulative information quality and the users ’ potential for making useful contributions. The results from this study provide practical suggestions to reduce misinformation on social networks. IS in Healthcar