Evidence map›Paper›PMID 32281938›Full record

ArticleJournal of medical Internet research2020

Comparing Medical Term Usage Patterns of Professionals and Search Engine and Community Question Answering Service Users in Japan: Log Analysis.

Kazuya Taira, Taichi Murayama, Sumio Fujita, Mikiko Ito, Kei Kamide, Eiji Aramaki

Open access · goldAbstract read
In one paragraph

Article in Journal of medical Internet research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.5field-weighted citation impact, top 25% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 6 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 3 institutions in 1 country.

Kazuya TairaDepartment of Public Health Nursing, Shiga University of Medical Science, Otsu, Shiga, Japan.ORCID 0000-0002-1560-5454
Taichi MurayamaSocial Computing Laboratory, Nara Institute of Science and Technology, Ikoma, Japan.ORCID 0000-0003-1148-711X
Sumio FujitaYahoo Japan Corporation, Tokyo, Japan.ORCID 0000-0002-1282-386X
Mikiko ItoDepartment of Public Health Nursing, Shiga University of Medical Science, Otsu, Shiga, Japan.ORCID 0000-0002-8289-9077
Kei KamideDivision of Health Science, Osaka University, Osaka, Japan.ORCID 0000-0003-1720-2218
Eiji AramakiSocial Computing Laboratory, Nara Institute of Science and Technology, Ikoma, Japan.ORCID 0000-0003-0201-3609
Nara Institute of Science and Technology · JPShiga University of Medical Science · JPOsaka Health Science University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDespite increasing opportunities for acquiring health information online, discussion of the specific words used in searches has been limited.

objectiveThe aim of this study was to clarify the medical information gap between medical professionals and the general public in Japan through health information-seeking activities on the internet.

methodsSearch and posting data were analyzed from one of the most popular domestic search engines in Japan (Yahoo! JAPAN Search) and the most popular Japanese community question answering 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) logs and questions posted to Yahoo! Chiebukuro (question frequency). The Spearman correlation coefficient was used to quantify association patterns among the three information sources. Additionally, user information (gender and age) in the search frequency associated with each registered user was extracted.

resultsSignificant correlations were observed between clinical and search frequencies (r=0.29, P=.003), clinical and question frequencies (r=0.34, P=.001), and search and question frequencies (r=0.57, P<.001). Low-frequency words in clinical frequency (eg, "hypothyroidism," "ulcerative colitis") highly ranked in search frequency. Similarly, "pain," "slight fever," and "numbness" were highly ranked only in question frequency. The weighted average of ages was 34.5 (SD 2.7) years, and the weighted average of gender (man -1, woman +1) was 0.1 (SD 0.1) in search frequency. Some words were specifically extracted from the search frequency of certain age groups, including "abdominal pain" (10-20 years), "plasma cells" and "inflammatory findings" (20-30 years), "DM" (diabetes mellitus; 30-40 years), "abnormal shadow" and "inflammatory findings" (40-50 years), "hypertension" and "abnormal shadow" (50-60 years), and "lung cancer" and "gastric cancer" (60-70 years).

conclusionsSearch and question frequencies showed similar tendencies, whereas search and clinical frequencies showed discrepancy. Low-clinical 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 included designated intractable diseases such as "ulcerative colitis," which has an incidence of less than 0.1% in the Japanese population. Therefore, it is generally worthwhile to pay attention not only to major diseases but also to minor diseases that users frequently seek information on, and more words will need to be analyzed in the future. Some characteristic words for certain age groups were observed (eg, 20-40 years: "cancer"; 40-60 years: diagnoses and diseases identified in health examinations; 60-70 years: diseases with late adulthood onset and "death"). Overall, this analysis demonstrates that medical professionals as information providers should be aware of clinical frequency, and medical information gaps between professionals and the general public should be bridged.

Indexed as

AdolescentAdultAnswering ServicesChildFemaleHumansInternetJapanMaleMedical Subject HeadingsMiddle AgedSearch EngineSurveys and QuestionnairesYoung Adultcommunity question answering servicehealth knowledgeinformation-seeking behaviorinternetsearch engine

Identifiers

PMID32281938
PMCPMC7186863
OpenAlexW3005026609

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.