JOURNAL (INTERNATIONAL) Comparing Medical Term Usage Patterns of Professionals and Search Engine and Community Question Answering Service Users in Japan: Log Analysis
Kazuya Taira (Shiga Univ. Med.), Taichi Murayama (NAIST), Sumio Fujita, Mikiko Ito (Shiga Univ. Med.), Kei Kamide (Osaka Univ.), Eiji Aramaki (NAIST)
Journal of Medical Internet Research (JMIR)
April 13, 2020
Background: Despite increasing opportunities for acquiring health information online, discussion of the specific words used in searches has been limited. Objective: This study clarifies health information sought by Japanese netizens. Methods: This study analyzed the data from one of the most popular domestic search engines (Yahoo! JAPAN Search) and the most popular domestic community question answering (CQA) service (Yahoo! Chiebukuro). We compared the frequency of 100 clinical words appearing in the clinical case reports of medical professionals (“clinical frequency”) with their frequency in Yahoo! JAPAN Search (“search frequency”) search logs and questions posted to Yahoo! Chiebukuro (“question frequency”). Subsequently, the Spearman correlation was used to quantify association patterns between the three search categories. Additionally, user information (sex and age) in search frequency associated with registration were extracted and discussed. Conclusions: The search and question frequencies were similar, but search and clinical frequencies had a discrepancy. Lowclinical frequency words related to diseases such as hypothyroidism and ulcerative colitis had high search frequencies, whereas those related to symptoms such as pain, slight fever, and numbness had high question frequencies. Moreover, high search frequency words include designated intractable diseases such as “ulcerative colitis”; patients with this condition are less than 0.1% of the national population. Therefore, information needs regarding major diseases are not necessarily high, and minor diseases that users seek more frequently should be valued. Some characteristic words for certain age groups were observed (e.g., 20-40 years: “cancer”; 40-60 years: diagnoses and diseases identified in health examinations; 60-70 years: diseases with late adulthood onset and “death”). In conclusion, information providers should be aware of clinical frequency and users’ medical information gaps should be bridged.