Cargando…
Leveraging Big Data to Improve Health Awareness Campaigns: A Novel Evaluation of the Great American Smokeout
BACKGROUND: Awareness campaigns are ubiquitous, but little is known about their potential effectiveness because traditional evaluations are often unfeasible. For 40 years, the “Great American Smokeout” (GASO) has encouraged media coverage and popular engagement with smoking cessation on the third Th...
Autores principales: | , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2016
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4869240/ https://www.ncbi.nlm.nih.gov/pubmed/27227151 http://dx.doi.org/10.2196/publichealth.5304 |
_version_ | 1782432281056509952 |
---|---|
author | Ayers, John W Westmaas, J Lee Leas, Eric C Benton, Adrian Chen, Yunqi Dredze, Mark Althouse, Benjamin M |
author_facet | Ayers, John W Westmaas, J Lee Leas, Eric C Benton, Adrian Chen, Yunqi Dredze, Mark Althouse, Benjamin M |
author_sort | Ayers, John W |
collection | PubMed |
description | BACKGROUND: Awareness campaigns are ubiquitous, but little is known about their potential effectiveness because traditional evaluations are often unfeasible. For 40 years, the “Great American Smokeout” (GASO) has encouraged media coverage and popular engagement with smoking cessation on the third Thursday of November as the nation’s longest running awareness campaign. OBJECTIVE: We proposed a novel evaluation framework for assessing awareness campaigns using the GASO as a case study by observing cessation-related news reports and Twitter postings, and cessation-related help seeking via Google, Wikipedia, and government-sponsored quitlines. METHODS: Time trends (2009-2014) were analyzed using a quasi-experimental design to isolate spikes during the GASO by comparing observed outcomes on the GASO day with the simulated counterfactual had the GASO not occurred. RESULTS: Cessation-related news typically increased by 61% (95% CI 35-87) and tweets by 13% (95% CI −21 to 48) during the GASO compared with what was expected had the GASO not occurred. Cessation-related Google searches increased by 25% (95% CI 10-40), Wikipedia page visits by 22% (95% CI −26 to 67), and quitline calls by 42% (95% CI 19-64). Cessation-related news media positively coincided with cessation tweets, Internet searches, and Wikipedia visits; for example, a 50% increase in news for any year predicted a 28% (95% CI −2 to 59) increase in tweets for the same year. Increases on the day of the GASO rivaled about two-thirds of a typical New Year’s Day—the day that is assumed to see the greatest increases in cessation-related activity. In practical terms, there were about 61,000 more instances of help seeking on Google, Wikipedia, or quitlines on GASO each year than would normally be expected. CONCLUSIONS: These findings provide actionable intelligence to improve the GASO and model how to rapidly, cost-effectively, and efficiently evaluate hundreds of awareness campaigns, nearly all for the first time. |
format | Online Article Text |
id | pubmed-4869240 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-48692402016-05-25 Leveraging Big Data to Improve Health Awareness Campaigns: A Novel Evaluation of the Great American Smokeout Ayers, John W Westmaas, J Lee Leas, Eric C Benton, Adrian Chen, Yunqi Dredze, Mark Althouse, Benjamin M JMIR Public Health Surveill Original Paper BACKGROUND: Awareness campaigns are ubiquitous, but little is known about their potential effectiveness because traditional evaluations are often unfeasible. For 40 years, the “Great American Smokeout” (GASO) has encouraged media coverage and popular engagement with smoking cessation on the third Thursday of November as the nation’s longest running awareness campaign. OBJECTIVE: We proposed a novel evaluation framework for assessing awareness campaigns using the GASO as a case study by observing cessation-related news reports and Twitter postings, and cessation-related help seeking via Google, Wikipedia, and government-sponsored quitlines. METHODS: Time trends (2009-2014) were analyzed using a quasi-experimental design to isolate spikes during the GASO by comparing observed outcomes on the GASO day with the simulated counterfactual had the GASO not occurred. RESULTS: Cessation-related news typically increased by 61% (95% CI 35-87) and tweets by 13% (95% CI −21 to 48) during the GASO compared with what was expected had the GASO not occurred. Cessation-related Google searches increased by 25% (95% CI 10-40), Wikipedia page visits by 22% (95% CI −26 to 67), and quitline calls by 42% (95% CI 19-64). Cessation-related news media positively coincided with cessation tweets, Internet searches, and Wikipedia visits; for example, a 50% increase in news for any year predicted a 28% (95% CI −2 to 59) increase in tweets for the same year. Increases on the day of the GASO rivaled about two-thirds of a typical New Year’s Day—the day that is assumed to see the greatest increases in cessation-related activity. In practical terms, there were about 61,000 more instances of help seeking on Google, Wikipedia, or quitlines on GASO each year than would normally be expected. CONCLUSIONS: These findings provide actionable intelligence to improve the GASO and model how to rapidly, cost-effectively, and efficiently evaluate hundreds of awareness campaigns, nearly all for the first time. JMIR Publications 2016-03-31 /pmc/articles/PMC4869240/ /pubmed/27227151 http://dx.doi.org/10.2196/publichealth.5304 Text en ©John W Ayers, J Lee Westmaas, Eric C Leas, Adrian Benton, Yunqi Chen, Mark Dredze, Benjamin M Althouse. Originally published in JMIR Public Health and Surveillance (http://publichealth.jmir.org), 31.03.2016. https://creativecommons.org/licenses/by/2.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0/ (https://creativecommons.org/licenses/by/2.0/) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Public Health and Surveillance, is properly cited. The complete bibliographic information, a link to the original publication on http://publichealth.jmir.org, as well as this copyright and license information must be included. |
spellingShingle | Original Paper Ayers, John W Westmaas, J Lee Leas, Eric C Benton, Adrian Chen, Yunqi Dredze, Mark Althouse, Benjamin M Leveraging Big Data to Improve Health Awareness Campaigns: A Novel Evaluation of the Great American Smokeout |
title | Leveraging Big Data to Improve Health Awareness Campaigns: A Novel Evaluation of the Great American Smokeout |
title_full | Leveraging Big Data to Improve Health Awareness Campaigns: A Novel Evaluation of the Great American Smokeout |
title_fullStr | Leveraging Big Data to Improve Health Awareness Campaigns: A Novel Evaluation of the Great American Smokeout |
title_full_unstemmed | Leveraging Big Data to Improve Health Awareness Campaigns: A Novel Evaluation of the Great American Smokeout |
title_short | Leveraging Big Data to Improve Health Awareness Campaigns: A Novel Evaluation of the Great American Smokeout |
title_sort | leveraging big data to improve health awareness campaigns: a novel evaluation of the great american smokeout |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4869240/ https://www.ncbi.nlm.nih.gov/pubmed/27227151 http://dx.doi.org/10.2196/publichealth.5304 |
work_keys_str_mv | AT ayersjohnw leveragingbigdatatoimprovehealthawarenesscampaignsanovelevaluationofthegreatamericansmokeout AT westmaasjlee leveragingbigdatatoimprovehealthawarenesscampaignsanovelevaluationofthegreatamericansmokeout AT leasericc leveragingbigdatatoimprovehealthawarenesscampaignsanovelevaluationofthegreatamericansmokeout AT bentonadrian leveragingbigdatatoimprovehealthawarenesscampaignsanovelevaluationofthegreatamericansmokeout AT chenyunqi leveragingbigdatatoimprovehealthawarenesscampaignsanovelevaluationofthegreatamericansmokeout AT dredzemark leveragingbigdatatoimprovehealthawarenesscampaignsanovelevaluationofthegreatamericansmokeout AT althousebenjaminm leveragingbigdatatoimprovehealthawarenesscampaignsanovelevaluationofthegreatamericansmokeout |