People are increasingly searching for health information from online sources such as question-and-answer (Q&A) services. The health information obtained this way can have significant impacts on people’s health decisions and lives, but what constitutes a helpful answer in the medical domain remains insufficiently explored. While prior studies examining antecedents of readers’ helpfulness evaluation of answers have focused primarily on the independent impacts of content and source characteristics, we propose a content-context congruence perspective with a focus on the role of congruence between an answer’s content and the answer’s contextual cues. Specifically, we leverage the unique setting of medical Q&A sites to identify two types of critical contextual cues — the language attributes (i.e., concreteness and emotional intensity) of the question’s content, and the acuteness of the disease to which the question is related. Building on the priming literature and construal-level theory, we hypothesize that an answer will be perceived more helpful if the language attributes of the answer’s content are congruent with those of the preceding question, and if they are congruent with the disease’s acuteness. Analyses of a unique data set from WebMD Answers provide empirical evidence for our theoretical model. This research deepens our understanding of readers’ value judgment of online medical information, demonstrates the importance of considering the congruence of content with contextual cues, and opens up exciting opportunities for future research to explore the role of content-context congruence in all varieties of user-generated content. Our findings also provide direct practical implications for knowledge contributors and Q&A sites.

中文翻译：

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医学问答网站中的词语不止：内容上下文一致的观点

人们越来越多地从诸如问答（Q＆A）服务之类的在线资源中搜索健康信息。通过这种方式获得的健康信息可能会对人们的健康决定和生活产生重大影响，但在医学领域构成有用答案的问题仍未得到充分探索。虽然先前的研究检查读者对答案的帮助评价的先行条件的研究主要集中在内容和来源特征的独立影响上，但我们提出了内容-上下文一致性观点，重点是答案的内容与答案的上下文线索之间的一致性作用。具体来说，我们利用医疗问答网站的独特设置来识别两种关键的上下文提示-语言属性（即 问题内容的具体性和情感强度，以及与该问题有关的疾病的严重性。基于入门文献和解释学水平的理论，我们假设，如果答案内容的语言属性与上一个问题的语言属性一致，并且与疾病的严重性相一致，则认为该回答会更有帮助。WebMD Answers对独特数据集的分析为我们的理论模型提供了经验证据。这项研究加深了我们对读者对在线医学信息价值判断的理解，表明了考虑内容与上下文提示的一致性的重要性，并为以后的研究探索了内容-上下文一致性在各种用户中的作用提供了令人兴奋的机会。生成的内容。