Evidence map›Paper›PMID 28385679›Full record

ArticleJMIR public health and surveillance2017

Using Google Trends Data to Study Public Interest in Breast Cancer Screening in Brazil: Why Not a Pink February?

Paulo Roberto Vasconcellos-Silva, Dárlinton Barbosa Feres Carvalho, Valéria Trajano, Lucia Rodriguez de La Rocque, Anunciata Cristina Marins Braz Sawada, Leidjaira Lopes Juvanhol

Abstract read
In one paragraph

Article in JMIR public health and surveillance, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
–field-weighted citation impact
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

22 citing papers in PubMed.

  1. Article
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  5. Does Pink October really impact breast cancer screening?Public health in practice (Oxford, England) · 2022
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  6. Article
  7. Article
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  12. Article
  13. Article
  14. Article
  15. Infodemiology and Infoveillance: Scoping Review.Journal of medical Internet research · 2020
    Article
  16. Enhanced Public Interest in Response to the Refugee and Healthcare Crises in Greece.International journal of environmental research and public health · 2020
    Article
  17. Article
  18. Article
  19. Article
  20. Article
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.

Paulo Roberto Vasconcellos-Silva *Laboratory of Innovation in Therapies, Teaching and Bioproducts /LITEBOswaldo Cruz Institute/IOCOswaldo Cruz FoundationRio de JaneiroBrazil.ORCID 0000-0003-4646-3580
Dárlinton Barbosa Feres Carvalho *Department of Computer ScienceFederal University of São João del-ReiSão João del-ReiBrazil.ORCID 0000-0003-3844-0178
Valéria Trajano *Laboratory of Innovation in Therapies, Teaching and Bioproducts /LITEBOswaldo Cruz Institute/IOCOswaldo Cruz FoundationRio de JaneiroBrazil.ORCID 0000-0002-7972-7899
Lucia Rodriguez de La Rocque *Laboratory of Innovation in Therapies, Teaching and Bioproducts /LITEBOswaldo Cruz Institute/IOCOswaldo Cruz FoundationRio de JaneiroBrazil.ORCID 0000-0002-0113-3484
Anunciata Cristina Marins Braz Sawada *Laboratory of Innovation in Therapies, Teaching and Bioproducts /LITEBOswaldo Cruz Institute/IOCOswaldo Cruz FoundationRio de JaneiroBrazil.ORCID 0000-0002-1822-6679
Leidjaira Lopes Juvanhol *National School of Public HealthOswaldo Cruz FoundationRio de JaneiroBrazil.ORCID 0000-0001-8012-6006

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOne of the major challenges of the Brazilian Ministry of Health is to foster interest in breast cancer screening (BCS), especially among women at high risk. Strategies have been developed to promote the early identification of breast cancer mainly by Pink October campaigns. The massive number of queries conducted through Google creates traffic data that can be analyzed to show unrevealed interest cycles and their seasonalities.

objectivesUsing Google Trends, we studied cycles of public interest in queries toward mammography and breast cancer along the last 5 years. We hypothesize that these data may be correlated with collective interest cycles leveraged by national BCS campaigns such as Pink October.

methodsGoogle Trends was employed to normalize traffic data on a scale from 0 (<1% of the peak volume) to 100 (peak of traffic) presented as weekly relative search volume (RSV) concerning mammography and breast cancer as search terms. A time series covered the last 261 weeks (November 2011 to October 2016), and RSV of both terms were compared with their respective annual means. Polynomial trendlines (second order) were employed to estimate overall trends.

resultsWe found an upward trend for both terms over the 5 years, with almost parallel trendlines. Remarkable peaks were found along Pink October months- mammography and breast cancer searches were leveraged up reaching, respectively, 119.1% (2016) and 196.8% (2015) above annual means. Short downward RSVs along December-January months were also noteworthy along all the studied period. These trends traced an N-shaped pattern with higher peaks in Pink October months and sharp falls along subsequent December and January.

conclusionsConsidering these findings, it would be reasonable to bring Pink October to the beginning of each year, thereby extending the beneficial effect of the campaigns. It would be more appropriate to start screening campaigns at the beginning of the year, when new resolutions are taken and new projects are added to everyday routines. Our work raises attention to the study of traffic data to encourage health campaign analysts to undertake better analysis based on marketing practices.

Indexed as

breast cancercancer information seekingearly detection of cancerhealth communicationinfodemiologyinfoveillanceInternetmass screening

Identifiers

PMID28385679
PMCPMC5399222

What OpenQuestion holds

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LicenceCC BY
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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.