Evidence map›Paper›PMID 36103221›Full record

ArticleJMIR formative research2022

Public Interest and Accessibility of Telehealth in Japan: Retrospective Analysis Using Google Trends and National Surveillance.

Takuya Kinoshita, Takehiro Matsumoto, Naota Taura, Tetsuya Usui, Nemu Matsuya, Mayumi Nishiguchi, Hozumi Horita, Kazuhiko Nakao

Abstract read
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Article in JMIR formative research, 2022. 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
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

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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

8 authors.

Takuya KinoshitaDepartment of Medical Informatics, Nagasaki University, Nagasaki, Japan.ORCID https://orcid.org/0000-0001-8204-0150
Takehiro MatsumotoDepartment of Medical Informatics, Nagasaki University, Nagasaki, Japan.ORCID https://orcid.org/0000-0002-0379-5334
Naota TauraDepartment of Medical Informatics, Nagasaki University Hospital, Nagasaki, Japan.ORCID https://orcid.org/0000-0002-0448-4941
Tetsuya UsuiDepartment of Laboratory Medicine, Nagasaki University Hospital, Nagasaki, Japan.ORCID https://orcid.org/0000-0001-9886-3805
Nemu MatsuyaDepartment of Neurology, National Hospital Organization Nagasaki Kawatana Medical Center, Kawatana, Japan.ORCID https://orcid.org/0000-0002-4302-1333
Mayumi NishiguchiDepartment of Medical Informatics, Nagasaki University, Nagasaki, Japan.ORCID https://orcid.org/0000-0002-3523-2472
Hozumi HoritaDepartment of Medical Informatics, Nagasaki University, Nagasaki, Japan.ORCID https://orcid.org/0000-0002-7462-4196
Kazuhiko NakaoDepartment of Medical Informatics, Nagasaki University, Nagasaki, Japan.ORCID https://orcid.org/0000-0002-7860-7123

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRecently, the use of telehealth for patient treatment under the COVID-19 pandemic has gained interest around the world. As a result, many infodemiology and infoveillance studies using web-based sources such as Google Trends were reported, focusing on the first wave of the COVID-19 pandemic. Although public interest in telehealth has increased in many countries during this time, the long-term interest has remained unknown among people living in Japan. Moreover, various mobile telehealth apps have become available for remote areas in the COVID-19 era, but the accessibility of these apps in epidemic versus nonepidemic regions is unknown.

objectiveWe aimed to investigate the public interest in telehealth during the first pandemic wave and after the wave in the first part of this study, and the accessibility of medical institutions using telehealth in the epidemic and nonepidemic regions, in the second part.

methodsWe examined and compared the first wave and after the wave with regards to severe cases, number of deaths, relative search volume (RSV) of telehealth and COVID-19, and the correlation between RSV and COVID-19 cases, using open sources such as Google Trends and the Japanese Ministry of Health, Labour and Welfare (JMHLW) data. The weekly mean and the week-over-week change rates of RSV and COVID-19 cases were used to examine the correlation coefficients. In the second part, the prevalence of COVID-19 cases, severe cases, number of deaths, and the telehealth accessibility rate were compared between epidemic regions and nonepidemic regions, using the JMHLW data. We also examined the regional correlation between telehealth accessibility and the prevalence of COVID-19 cases.

resultsAmong the 83 weeks with 5 pandemic waves, the overall mean for the RSV of telehealth and COVID-19 was 11.3 (95% CI 8.0-14.6) and 30.7 (95% CI 27.2-34.2), respectively. The proportion of severe cases (26.54% vs 18.16%; P<.001), deaths (5.33% vs 0.99%; P<.001), RSV of telehealth (mean 33.1, 95% CI 16.2-50.0 vs mean 7.3, 95% CI 6.7-8.0; P<.001), and RSV of COVID-19 (mean 52.1, 95% CI 38.3-65.9 vs mean 26.3, 95% CI 24.4-29.2; P<.001) was significantly higher in the first wave compared to after the wave. In the correlation analysis, the public interest in telehealth was 0.899 in the first wave and -0.300 overall. In Japan, the accessibility of telehealth using mobile apps was significantly higher in epidemic regions compared to nonepidemic regions in both hospitals (3.8% vs 2.0%; P=.004) and general clinics (5.2% vs 3.1%; P<.001). In the regional correlation analysis, telehealth accessibility using mobile apps was 0.497 in hospitals and 0.629 in general clinics.

conclusionsAlthough there was no long-term correlation between the public interest in telehealth and COVID-19, there was a regional correlation between mobile telehealth app accessibility in Japan, especially for general clinics. We also revealed that epidemic regions had higher mobile telehealth app accessibility. Further studies about the actual use of telehealth and its effect after the COVID-19 pandemic are necessary.

Indexed as

correlationCOVID-19Google Trendsinfodemiology, infoveillancemobile apppublic interestsurveillancetelehealthtelemedicine

Identifiers

PMID36103221
PMCPMC9520390

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

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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.