Effects of the COVID-19 Pandemic on the Interest of Google Queries in Cancer Screening and Cancers: A Retrospective Study

Kamińśki, Mikołaj; Skrzypczak, Piotr; Staszewski, R.; Roszak, Magdalena

doi:10.3390/cancers15030617

Cited by 2 publications

(1 citation statement)

References 45 publications

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“…Other notable examples of such trends include the interest in melanoma in relation to its prevalence in the population [26] and the awareness of the importance of colonoscopy in particular countries [27]. Most recently, Google query statistics have been leveraged to evaluate the decline in interest in cancer screening during the COVID-19 pandemic [28][29][30].…”

Section: Objectivesmentioning

confidence: 99%

The Characteristics, Uses, and Biases of Studies Related to Malignancies Using Google Trends: Systematic Review

Kamińśki¹,

Czarny²,

Skrzypczak³

et al. 2023

J Med Internet Res

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Background The internet is a primary source of health information for patients, supplementing physician care. Google Trends (GT), a popular tool, allows the exploration of public interest in health-related phenomena. Despite the growing volume of GT studies, none have focused explicitly on oncology, creating a need for a systematic review to bridge this gap. Objective We aimed to systematically characterize studies related to oncology using GT to describe its utilities and biases. Methods We included all studies that used GT to analyze Google searches related to malignancies. We excluded studies written in languages other than English. The search was performed using the PubMed engine on August 1, 2022. We used the following search input: “Google trends” AND (“oncology” OR “cancer” or “malignancy” OR “tumor” OR “lymphoma” OR “multiple myeloma” OR “leukemia”). We analyzed sources of bias that included using search terms instead of topics, lack of confrontation of GT statistics with real-world data, and absence of sensitivity analysis. We performed descriptive statistics. Results A total of 85 articles were included. The first study using GT for oncology research was published in 2013, and since then, the number of publications has increased annually. The studies were categorized as follows: 22% (19/85) were related to prophylaxis, 20% (17/85) pertained to awareness events, 11% (9/85) were celebrity-related, 13% (11/85) were related to COVID-19, and 47% (40/85) fell into other categories. The most frequently analyzed cancers were breast (n=28), prostate (n=26), lung (n=18), and colorectal cancers (n=18). We discovered that of the 85 studies, 17 (20%) acknowledged using GT topics instead of search terms, 79 (93%) disclosed all search input details necessary for replicating their results, and 34 (40%) compared GT statistics with real-world data. The most prevalent methods for analyzing the GT data were correlation analysis (55/85, 65%) and peak analysis (43/85, 51%). The authors of only 11% (9/85) of the studies performed a sensitivity analysis. Conclusions The number of studies related to oncology using GT data has increased annually. The studies included in this systematic review demonstrate a variety of concerning topics, search strategies, and statistical methodologies. The most frequently analyzed cancers were breast, prostate, lung, colorectal, skin, and cervical cancers, potentially reflecting their prevalence in the population or public interest. Although most researchers provided reproducible search inputs, only one-fifth used GT topics instead of search terms, and many studies lacked a sensitivity analysis. Scientists using GT for medical research should ensure the quality of studies by providing a transparent search strategy to reproduce results, preferring to use topics over search terms, and performing robust statistical calculations coupled with sensitivity analysis.

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Section: Objectivesmentioning

confidence: 99%

The Characteristics, Uses, and Biases of Studies Related to Malignancies Using Google Trends: Systematic Review

Kamińśki¹,

Czarny²,

Skrzypczak³

et al. 2023

J Med Internet Res

Self Cite

View full text Add to dashboard Cite

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The Characteristics, Uses, and Biases of Studies Related to Malignancies Using Google Trends: Systematic Review (Preprint)

Kamińśki¹,

Czarny²,

Skrzypczak³

et al. 2023

Preprint

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BACKGROUND Google Trends (GT) is a freely-available tool presenting Google search statistics. GT is becoming a feasible tool to analyze the interest of Google users in different health phenomena. However, there are a few reviews on GT, and none has contributed specifically to oncology. OBJECTIVE We aimed to systematically characterize studies related to oncology using GT to describe its utilities and biases. METHODS We included all studies utilizing GT to analyze Google searches related to malignancies. We excluded studies written in non-English. The search was done on the PubMed engine on 1st August 2022. We used the following search input: "Google trends" AND ("oncology" OR "cancer" OR "malignancy" OR "tumor" OR "lymphoma" OR "multiple myeloma" OR "leukemia"). We analyzed the following sources of bias: 1) using search terms instead of topics, 2) lack of confrontation with real-world data, and 3) absence of a sensitivity analysis. We performed descriptive statistics. RESULTS A total of n=85 articles were included. We classified n=19 (22.4%) studies as related to prophylaxis, n=17 (20.0%) as an awareness event, n=9 (10.6%) as celebrity-related, n=11 (12.9%) related to COVID-19 and n=40 (47.1%) as others. The most frequently analyzed cancers were: breast (n=28), prostate (n=26), lung, and colorectal (both: n=18). n=79 (92.9%) of the studies provided all search input details to reproduce their results, and n=34 (40%.0) studies confronted GT statistics with real-world data. Authors of only n = 9 (10.6%) studies performed sensitivity analysis. CONCLUSIONS The studies in this systematic review varied regarding topics, search strategy, and statistical methods. Most researchers provided reproducible search inputs, but many studies lacked sensitivity analysis.Scientists using GT for medical research should ensure the quality of studies by 1) providing a search strategy to reproduce results, 2) preferring using topics instead of search terms, and 3) performing robust statistical calculations and sensitivity analysis.

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Effects of the COVID-19 Pandemic on the Interest of Google Queries in Cancer Screening and Cancers: A Retrospective Study

Cited by 2 publications

References 45 publications

The Characteristics, Uses, and Biases of Studies Related to Malignancies Using Google Trends: Systematic Review

The Characteristics, Uses, and Biases of Studies Related to Malignancies Using Google Trends: Systematic Review

The Characteristics, Uses, and Biases of Studies Related to Malignancies Using Google Trends: Systematic Review (Preprint)

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