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Leveraging Big Data for Exploring Occupational Diseases-Related Interest at the Level of Scientific Community, Media Coverage and Novel Data Streams: The Example of Silicosis as a Pilot Study
OBJECTIVE: Silicosis is an untreatable but preventable occupational disease, caused by exposure to silica. It can progressively evolve to lung impairment, respiratory failure and death, even after exposure has ceased. However, little is known about occupational diseases-related interest at the level...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5091866/ https://www.ncbi.nlm.nih.gov/pubmed/27806115 http://dx.doi.org/10.1371/journal.pone.0166051 |
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author | Bragazzi, Nicola Luigi Dini, Guglielmo Toletone, Alessandra Brigo, Francesco Durando, Paolo |
author_facet | Bragazzi, Nicola Luigi Dini, Guglielmo Toletone, Alessandra Brigo, Francesco Durando, Paolo |
author_sort | Bragazzi, Nicola Luigi |
collection | PubMed |
description | OBJECTIVE: Silicosis is an untreatable but preventable occupational disease, caused by exposure to silica. It can progressively evolve to lung impairment, respiratory failure and death, even after exposure has ceased. However, little is known about occupational diseases-related interest at the level of scientific community, media coverage and web behavior. This article aims at filling in this gap of knowledge, taking the silicosis as a case study. METHODS: We investigated silicosis-related web-activities using Google Trends (GT) for capturing the Internet behavior worldwide in the years 2004–2015. GT-generated data were, then, compared with the silicosis-related scientific production (i.e., PubMed and Google Scholar), the media coverage (i.e., Google news), the Wikipedia traffic (i.e, Wikitrends) and the usage of new media (i.e., YouTube and Twitter). RESULTS: A peak in silicosis-related web searches was noticed in 2010–2011: interestingly, both scientific articles production and media coverage markedly increased after these years in a statistically significant way. The public interest and the level of the public engagement were witnessed by an increase in likes, comments, hashtags, and re-tweets. However, it was found that only a small fraction of the posted/uploaded material contained accurate scientific information. CONCLUSIONS: GT could be useful to assess the reaction of the public and the level of public engagement both to novel risk-factors associated to occupational diseases, and possibly related changes in disease natural history, and to the effectiveness of preventive workplace practices and legislative measures adopted to improve occupational health. Further, occupational clinicians should become aware of the topics most frequently searched by patients and proactively address these concerns during the medical examination. Institutional bodies and organisms should be more present and active in digital tools and media to disseminate and communicate scientifically accurate information. This manuscript should be intended as preliminary, exploratory communication, paving the way for further studies. |
format | Online Article Text |
id | pubmed-5091866 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-50918662016-11-15 Leveraging Big Data for Exploring Occupational Diseases-Related Interest at the Level of Scientific Community, Media Coverage and Novel Data Streams: The Example of Silicosis as a Pilot Study Bragazzi, Nicola Luigi Dini, Guglielmo Toletone, Alessandra Brigo, Francesco Durando, Paolo PLoS One Research Article OBJECTIVE: Silicosis is an untreatable but preventable occupational disease, caused by exposure to silica. It can progressively evolve to lung impairment, respiratory failure and death, even after exposure has ceased. However, little is known about occupational diseases-related interest at the level of scientific community, media coverage and web behavior. This article aims at filling in this gap of knowledge, taking the silicosis as a case study. METHODS: We investigated silicosis-related web-activities using Google Trends (GT) for capturing the Internet behavior worldwide in the years 2004–2015. GT-generated data were, then, compared with the silicosis-related scientific production (i.e., PubMed and Google Scholar), the media coverage (i.e., Google news), the Wikipedia traffic (i.e, Wikitrends) and the usage of new media (i.e., YouTube and Twitter). RESULTS: A peak in silicosis-related web searches was noticed in 2010–2011: interestingly, both scientific articles production and media coverage markedly increased after these years in a statistically significant way. The public interest and the level of the public engagement were witnessed by an increase in likes, comments, hashtags, and re-tweets. However, it was found that only a small fraction of the posted/uploaded material contained accurate scientific information. CONCLUSIONS: GT could be useful to assess the reaction of the public and the level of public engagement both to novel risk-factors associated to occupational diseases, and possibly related changes in disease natural history, and to the effectiveness of preventive workplace practices and legislative measures adopted to improve occupational health. Further, occupational clinicians should become aware of the topics most frequently searched by patients and proactively address these concerns during the medical examination. Institutional bodies and organisms should be more present and active in digital tools and media to disseminate and communicate scientifically accurate information. This manuscript should be intended as preliminary, exploratory communication, paving the way for further studies. Public Library of Science 2016-11-02 /pmc/articles/PMC5091866/ /pubmed/27806115 http://dx.doi.org/10.1371/journal.pone.0166051 Text en © 2016 Bragazzi et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Bragazzi, Nicola Luigi Dini, Guglielmo Toletone, Alessandra Brigo, Francesco Durando, Paolo Leveraging Big Data for Exploring Occupational Diseases-Related Interest at the Level of Scientific Community, Media Coverage and Novel Data Streams: The Example of Silicosis as a Pilot Study |
title | Leveraging Big Data for Exploring Occupational Diseases-Related Interest at the Level of Scientific Community, Media Coverage and Novel Data Streams: The Example of Silicosis as a Pilot Study |
title_full | Leveraging Big Data for Exploring Occupational Diseases-Related Interest at the Level of Scientific Community, Media Coverage and Novel Data Streams: The Example of Silicosis as a Pilot Study |
title_fullStr | Leveraging Big Data for Exploring Occupational Diseases-Related Interest at the Level of Scientific Community, Media Coverage and Novel Data Streams: The Example of Silicosis as a Pilot Study |
title_full_unstemmed | Leveraging Big Data for Exploring Occupational Diseases-Related Interest at the Level of Scientific Community, Media Coverage and Novel Data Streams: The Example of Silicosis as a Pilot Study |
title_short | Leveraging Big Data for Exploring Occupational Diseases-Related Interest at the Level of Scientific Community, Media Coverage and Novel Data Streams: The Example of Silicosis as a Pilot Study |
title_sort | leveraging big data for exploring occupational diseases-related interest at the level of scientific community, media coverage and novel data streams: the example of silicosis as a pilot study |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5091866/ https://www.ncbi.nlm.nih.gov/pubmed/27806115 http://dx.doi.org/10.1371/journal.pone.0166051 |
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